Shock wave caused by a sudden release of high-energy,such as explosion and blast,usually affects a significant range of areas.The utilization of a uniform fine mesh to capture sharp shock wave and to obtain precise re...Shock wave caused by a sudden release of high-energy,such as explosion and blast,usually affects a significant range of areas.The utilization of a uniform fine mesh to capture sharp shock wave and to obtain precise results is inefficient in terms of computational resource.This is particularly evident when large-scale fluid field simulations are conducted with significant differences in computational domain size.In this work,a variable-domain-size adaptive mesh enlargement(vAME)method is developed based on the proposed adaptive mesh enlargement(AME)method for modeling multi-explosives explosion problems.The vAME method reduces the division of numerous empty areas or unnecessary computational domains by adaptively suspending enlargement operation in one or two directions,rather than in all directions as in AME method.A series of numerical tests via AME and vAME with varying nonintegral enlargement ratios and different mesh numbers are simulated to verify the efficiency and order of accuracy.An estimate of speedup ratio is analyzed for further efficiency comparison.Several large-scale near-ground explosion experiments with single/multiple explosives are performed to analyze the shock wave superposition formed by the incident wave,reflected wave,and Mach wave.Additionally,the vAME method is employed to validate the accuracy,as well as to investigate the performance of the fluid field and shock wave propagation,considering explosive quantities ranging from 1 to 5 while maintaining a constant total mass.The results show a satisfactory correlation between the overpressure versus time curves for experiments and numerical simulations.The vAME method yields a competitive efficiency,increasing the computational speed to 3.0 and approximately 120,000 times in comparison to AME and the fully fine mesh method,respectively.It indicates that the vAME method reduces the computational cost with minimal impact on the results for such large-scale high-energy release problems with significant differences in computational domain size.展开更多
Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncerta...Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncertain systems characterized by unknown control directions and time-varying input delay lacks comprehensive solutions.In this paper,we propose an observerbased adaptive tracking controller to address this gap.Neural networks are utilized to handle uncertainty,and a unique coordinate transformation is employed to untangle the coupling between input delay and unknown control directions.Subsequently,a new auxiliary signal counters the impact of time-varying input delay,while a Nussbaum function is introduced to solve the problem of unknown control directions.The leverage of an advanced dynamic surface control technique avoids the“complexity explosion”and reduces boundary layer errors.Synthesizing these techniques ensures that all the closed-loop signals are semi-globally uniformly ultimately bounded(SGUUB),and the tracking error converges to a small region around the origin by selecting suitable parameters.Simulation examples are provided to demonstrate the feasibility of the proposed approach.展开更多
Range-azimuth imaging of ground targets via frequency-modulated continuous wave(FMCW)radar is crucial for effective target detection.However,when the pitch of the moving array constructed during motion exceeds the phy...Range-azimuth imaging of ground targets via frequency-modulated continuous wave(FMCW)radar is crucial for effective target detection.However,when the pitch of the moving array constructed during motion exceeds the physical array aperture,azimuth ambiguity occurs,making range-azimuth imaging on a moving platform challenging.To address this issue,we theoretically analyze azimuth ambiguity generation in sparse motion arrays and propose a dual-aperture adaptive processing(DAAP)method for suppressing azimuth ambiguity.This method combines spatial multiple-input multiple-output(MIMO)arrays with sparse motion arrays to achieve high-resolution range-azimuth imaging.In addition,an adaptive QR decomposition denoising method for sparse array signals based on iterative low-rank matrix approximation(LRMA)and regularized QR is proposed to preprocess sparse motion array signals.Simulations and experiments show that on a two-transmitter-four-receiver array,the signal-to-noise ratio(SNR)of the sparse motion array signal after noise suppression via adaptive QR decomposition can exceed 0 dB,and the azimuth ambiguity signal ratio(AASR)can be reduced to below-20 dB.展开更多
Solar radio burst(SRB)is one of the main natural interference sources of Global Positioning System(GPS)signals and can reduce the signal-to-noise ratio(SNR),directly affecting the tracking performance of GPS receivers...Solar radio burst(SRB)is one of the main natural interference sources of Global Positioning System(GPS)signals and can reduce the signal-to-noise ratio(SNR),directly affecting the tracking performance of GPS receivers.In this paper,a tracking algorithm based on the adaptive Kalman filter(AKF)with carrier-to-noise ratio estimation is proposed and compared with the conventional second-order phase-locked loop tracking algo-rithms and the improved Sage-Husa adaptive Kalman filter(SHAKF)algorithm.It is discovered that when the SRBs occur,the improved SHAKF and the AKF with carrier-to-noise ratio estimation enable stable tracking to loop signals.The conven-tional second-order phase-locked loop tracking algorithms fail to track the receiver signal.The standard deviation of the carrier phase error of the AKF with carrier-to-noise ratio estimation out-performs 50.51%of the improved SHAKF algorithm,showing less fluctuation and better stability.The proposed algorithm is proven to show more excellent adaptability in the severe envi-ronment caused by the SRB occurrence and has better tracking performance.展开更多
The problem on stabilization for the system with distributed delays is researched. The distributed time-delay under consideration is assumed to be a constant time-delay, but not known exactly. A design method is propo...The problem on stabilization for the system with distributed delays is researched. The distributed time-delay under consideration is assumed to be a constant time-delay, but not known exactly. A design method is proposed for a memory proportional and integral （PI） feedback controller with adaptation to distributed time-delay. The feedback controller with memory simultaneously contains the current state and the past distributed information of the addressed systems. The design for adaptation law to distributed delay is very concise. The controller can be derived by solving a set of linear matrix inequalities （LMIs）. Two numerical examples are given to illustrate the effectiveness of the design method.展开更多
A refractory gold concentrate with 19% arsenic was treated by a mixed moderately thermophiles in an airlift bioreactor through an adaptation protocol. The moderately thermophiles could respond well to 20%(w/v) pulp de...A refractory gold concentrate with 19% arsenic was treated by a mixed moderately thermophiles in an airlift bioreactor through an adaptation protocol. The moderately thermophiles could respond well to 20%(w/v) pulp density with less than 10% loss of productivity, and resist arsenic up to 15 g/L. There were a lot of jarosite, arsenolite and sulfur, but not scorodite and ferric arsenate in the bioleached residue. Jarosite passivation and lower sulfur-oxidizing activity of the cells due to the toxicity of the high concentrations of soluble arsenic and iron ions at low p H value should mainly response for the incomplete extraction at high pulp density. The initial bacterial community did not change in nature except for new found P aeruginosa ANSC, but sulfur-oxidizing microorganisms have been dominant microorganisms after a long time of adaptation. Pseudomonas aeruginosa originating from the gold concentrate should be closely relative to the metabolism of the organic matters contained in the refractory gold concentrate.展开更多
One of the challenges the world is facing today is global climate change and its associated impacts. Uganda is a climate sensitive country with over 90% of the population dependent on climate sensitive sectors.Gradual...One of the challenges the world is facing today is global climate change and its associated impacts. Uganda is a climate sensitive country with over 90% of the population dependent on climate sensitive sectors.Gradual and sudden variations in climatic parameters will therefore render the livelihoods of Ugandans very vulnerable.A number of approaches to enhance the resilience of communities to展开更多
Climate change is one of the most significant environment issues in the whole world today. And it is one of the most complex challenges of the humanities faced in the 21st century. Climate Change is impacted on our gl...Climate change is one of the most significant environment issues in the whole world today. And it is one of the most complex challenges of the humanities faced in the 21st century. Climate Change is impacted on our global; nobody can avoid the influence of climate change. The local adaptation strategies on climate change are very important to contribute the mitigation and poverty stricken situation, both in China and in the world. We chose a typical China＇s province as a case to analyze the impact of climate change on the region （such as agricultural, natural ecosystems, water resources, as well as local people healthy condition）, and how the local government and local residences face the impact of the climate change influence, and summarized several strategies on climate change of the area in a sustainable development way.展开更多
Mitigation and adaptation are two principle strategies for managing human-induced climate change. Agriculture plays a duet role in climate change. It has been a major source of greenhouse gases to the atmosphere. It i...Mitigation and adaptation are two principle strategies for managing human-induced climate change. Agriculture plays a duet role in climate change. It has been a major source of greenhouse gases to the atmosphere. It is also one of the sectors most vulnerable to the risks and impacts of global climate change. This paper first indentified the mitigative and adaptative options and potential in agriculture, then addressed the integrated analysis of mitigation and adaptation and its benefits for agriculture. Finally, it discussed the implications to Chinese agriculture in dealing with the global climate change.展开更多
The explanation and simulation of the natural and artificial intelligence are the central goals of the studies of Neuroscience, Psychology, Artificial Intelligence and Cognitive Science. This paper first gives an intr...The explanation and simulation of the natural and artificial intelligence are the central goals of the studies of Neuroscience, Psychology, Artificial Intelligence and Cognitive Science. This paper first gives an introduction to the core topics and approaches in the study. Then, GAF--a general adaptive framework for neural system is proposed. Interdisciplinary discussions around the adaptation of the human nervous system are presented. Rules describing the theory of adaptation of the nervous system are provided.展开更多
In Cross-cultural exchanges,there are existing differences between cultures;cultural rejection of psychological and cultural hegemony of thinking leads to widespread cultural conflict. It will cause conflict,including...In Cross-cultural exchanges,there are existing differences between cultures;cultural rejection of psychological and cultural hegemony of thinking leads to widespread cultural conflict. It will cause conflict,including cultural,forms and exchanges. Cultural conflict causes cross-cultural prejudices and opposition,which lead to cultural adaptation barriers; therefore cross-cultural exchanges must adhere to civilization dialogue on the basis of cultural awareness and self-confidence. Respect for cultural differences with equal attitude and advocate for solution to cultural conflict are needed to improve the cultural adaptability.展开更多
A tracking stability control problem for the vertical electric stabilization system of moving tank based on adaptive robust servo control is addressed.This paper mainly focuses on two types of possibly fast timevaryin...A tracking stability control problem for the vertical electric stabilization system of moving tank based on adaptive robust servo control is addressed.This paper mainly focuses on two types of possibly fast timevarying but bounded uncertainty within the vertical electric stabilization system:model parameter uncertainty and uncertain nonlinearity.First,the vertical electric stabilization system is constructed as an uncertain nonlinear dynamic system that can reflect the practical mechanics transfer process of the system.Second,the dynamical equation in the form of state space is established by designing the angular tracking error.Third,the comprehensive parameter of system uncertainty is designed to estimate the most conservative effects of uncertainty.Finally,an adaptive robust servo control which can effectively handle the combined effects of complex nonlinearity and uncertainty is proposed.The feasibility of the proposed control strategy under the practical physical condition is validated through the tests on the experimental platform.This paper pioneers the introduction of the internal nonlinearity and uncertainty of the vertical electric stabilization system into the settlement of the tracking stability control problem,and validates the advanced servo control strategy through experiment for the first time.展开更多
The phenomenon of a target echo peak overlapping with the backscattered echo peak significantly undermines the detection range and precision of underwater laser fuzes.To overcome this issue,we propose a four-quadrant ...The phenomenon of a target echo peak overlapping with the backscattered echo peak significantly undermines the detection range and precision of underwater laser fuzes.To overcome this issue,we propose a four-quadrant dual-beam circumferential scanning laser fuze to distinguish various interference signals and provide more real-time data for the backscatter filtering algorithm.This enhances the algorithm loading capability of the fuze.In order to address the problem of insufficient filtering capacity in existing linear backscatter filtering algorithms,we develop a nonlinear backscattering adaptive filter based on the spline adaptive filter least mean square(SAF-LMS)algorithm.We also designed an algorithm pause module to retain the original trend of the target echo peak,improving the time discrimination accuracy and anti-interference capability of the fuze.Finally,experiments are conducted with varying signal-to-noise ratios of the original underwater target echo signals.The experimental results show that the average signal-to-noise ratio before and after filtering can be improved by more than31 d B,with an increase of up to 76%in extreme detection distance.展开更多
This paper mainly focuses on the development of a learning-based controller for a class of uncertain mechanical systems modeled by the Euler-Lagrange formulation.The considered system can depict the behavior of a larg...This paper mainly focuses on the development of a learning-based controller for a class of uncertain mechanical systems modeled by the Euler-Lagrange formulation.The considered system can depict the behavior of a large class of engineering systems,such as vehicular systems,robot manipulators and satellites.All these systems are often characterized by highly nonlinear characteristics,heavy modeling uncertainties and unknown perturbations,therefore,accurate-model-based nonlinear control approaches become unavailable.Motivated by the challenge,a reinforcement learning(RL)adaptive control methodology based on the actor-critic framework is investigated to compensate the uncertain mechanical dynamics.The approximation inaccuracies caused by RL and the exogenous unknown disturbances are circumvented via a continuous robust integral of the sign of the error(RISE)control approach.Different from a classical RISE control law,a tanh(·)function is utilized instead of a sign(·)function to acquire a more smooth control signal.The developed controller requires very little prior knowledge of the dynamic model,is robust to unknown dynamics and exogenous disturbances,and can achieve asymptotic output tracking.Eventually,co-simulations through ADAMS and MATLAB/Simulink on a three degrees-of-freedom(3-DOF)manipulator and experiments on a real-time electromechanical servo system are performed to verify the performance of the proposed approach.展开更多
Yes, we perceive that the environment in which comp an ies operate, is changing at higher speeds then before. Globalisation, higher inn ovation rates, customisation, more intense competition, technological developmen ...Yes, we perceive that the environment in which comp an ies operate, is changing at higher speeds then before. Globalisation, higher inn ovation rates, customisation, more intense competition, technological developmen ts account for these changes effecting the way industrial companies operate and eventually their structures and processes. Companies have to adapt themselves to these changes. The question arose whether the approach of the Section Industria l Organisation and Management that it has practised for redesign of processes an d organisational structures also withholds in this era of continuous change. Sec ondly, firms are also looking for contingencies in processes and structures to i mprove their chances for survival. These two questions into the processes and st ructures within the firm that it needs to support adaptation to the ever-changi ng environment direct this research. Industrial companies will have to increase to their Complexity Handling Capabili ty, the ability to cope with changes in its environment and imposed complexity p ouring in from the environment. To do so, they might decrease their internal com plexity through redefining their organisations and product structure. The effect of these measurements seems limited; more might be won by learning to increase its base of capabilities. The increase of capabilities holds parallels to the de velopment of species in biology and paleontology for which two models exist: the punctuated equilibrium and the phyletic gradualism. The punctuated equilibr ium supposes that periods of turmoil are interchanged by periods of fermentation giving rise to new variants and products (for companies). The phyletic graduali sm relies on the development of characteristics in species that are initially ha rd to detect but will lead at the end to new species. Whatever might be true for biology and palaeontology, these two models appear as a possibility for cla ssifying the theories of organisational change. Also, these theories put forward insights in the development of organisations that stretch beyond the classical insights on the adaptation of organisations based on one-time interventions ass uming balance between demands from the environment and internal structure. Little research has been done so far in this field of adaptation of companies to the dynamics of the environment. Most literature does not address the internal processes and structures necessary for coping with change. This paper will prese nt initial findings of case studies of graduation theses that took place to generate data on the validity of the evolutionary models. This way the research should not only lead to a theoretical framework but also to practical implicatio ns for industrial companies.展开更多
Since backlash nonlinearity is inevitably existing in actuators for bidirectional stabilization system of allelectric tank,it behaves more drastically in high maneuvering environments.In this work,the accurate trackin...Since backlash nonlinearity is inevitably existing in actuators for bidirectional stabilization system of allelectric tank,it behaves more drastically in high maneuvering environments.In this work,the accurate tracking control for bidirectional stabilization system of moving all-electric tank with actuator backlash and unmodeled disturbance is solved.By utilizing the smooth adaptive backlash inverse model,a nonlinear robust adaptive feedback control scheme is presented.The unknown parameters and unmodelled disturbance are addressed separately through the derived parametric adaptive function and the continuous nonlinear robust term.Because the unknown backlash parameters are updated via adaptive function and the backlash effect can be suppressed successfully by inverse operation,which ensures the system stability.Meanwhile,the system disturbance in the high maneuverable environment can be estimated with the constructed adaptive law online improving the engineering practicality.Finally,Lyapunov-based analysis proves that the developed controller can ensure the tracking error asymptotically converges to zero even with unmodeled disturbance and unknown actuator backlash.Contrast co-simulations and experiments illustrate the advantages of the proposed approach.展开更多
In engineering application,there is only one adaptive weights estimated by most of traditional early warning radars for adaptive interference suppression in a pulse reputation interval(PRI).Therefore,if the training s...In engineering application,there is only one adaptive weights estimated by most of traditional early warning radars for adaptive interference suppression in a pulse reputation interval(PRI).Therefore,if the training samples used to calculate the weight vector does not contain the jamming,then the jamming cannot be removed by adaptive spatial filtering.If the weight vector is constantly updated in the range dimension,the training data may contain target echo signals,resulting in signal cancellation effect.To cope with the situation that the training samples are contaminated by target signal,an iterative training sample selection method based on non-homogeneous detector(NHD)is proposed in this paper for updating the weight vector in entire range dimension.The principle is presented,and the validity is proven by simulation results.展开更多
This study aimed to address the challenge of accurately and reliably detecting tomatoes in dense planting environments,a critical prerequisite for the automation implementation of robotic harvesting.However,the heavy ...This study aimed to address the challenge of accurately and reliably detecting tomatoes in dense planting environments,a critical prerequisite for the automation implementation of robotic harvesting.However,the heavy reliance on extensive manually annotated datasets for training deep learning models still poses significant limitations to their application in real-world agricultural production environments.To overcome these limitations,we employed domain adaptive learning approach combined with the YOLOv5 model to develop a novel tomato detection model called as TDA-YOLO(tomato detection domain adaptation).We designated the normal illumination scenes in dense planting environments as the source domain and utilized various other illumination scenes as the target domain.To construct bridge mechanism between source and target domains,neural preset for color style transfer is introduced to generate a pseudo-dataset,which served to deal with domain discrepancy.Furthermore,this study combines the semi-supervised learning method to enable the model to extract domain-invariant features more fully,and uses knowledge distillation to improve the model's ability to adapt to the target domain.Additionally,for purpose of promoting inference speed and low computational demand,the lightweight FasterNet network was integrated into the YOLOv5's C3 module,creating a modified C3_Faster module.The experimental results demonstrated that the proposed TDA-YOLO model significantly outperformed original YOLOv5s model,achieving a mAP(mean average precision)of 96.80%for tomato detection across diverse scenarios in dense planting environments,increasing by 7.19 percentage points;Compared with the latest YOLOv8 and YOLOv9,it is also 2.17 and 1.19 percentage points higher,respectively.The model's average detection time per image was an impressive 15 milliseconds,with a FLOPs(floating point operations per second)count of 13.8 G.After acceleration processing,the detection accuracy of the TDA-YOLO model on the Jetson Xavier NX development board is 90.95%,the mAP value is 91.35%,and the detection time of each image is 21 ms,which can still meet the requirements of real-time detection of tomatoes in dense planting environment.The experimental results show that the proposed TDA-YOLO model can accurately and quickly detect tomatoes in dense planting environment,and at the same time avoid the use of a large number of annotated data,which provides technical support for the development of automatic harvesting systems for tomatoes and other fruits.展开更多
To improve the hit probability of tank at high speed,a prediction method of projectile-target intersection based on adaptive robust constraint-following control and interval uncertainty analysis is proposed.The method...To improve the hit probability of tank at high speed,a prediction method of projectile-target intersection based on adaptive robust constraint-following control and interval uncertainty analysis is proposed.The method proposed provides a novel way to predict the impact point of projectile for moving tank.First,bidirectional stability constraints and stability constraint-following error are constructed using the Udwadia-Kalaba theory,and an adaptive robust constraint-following controller is designed considering uncertainties.Second,the exterior ballistic ordinary differential equation with uncertainties is integrated into the controller,and the pointing control of stability system is extended to the impact-point control of projectile.Third,based on the interval uncertainty analysis method combining Chebyshev polynomial expansion and affine arithmetic,a prediction method of projectile-target intersection is proposed.Finally,the co-simulation experiment is performed by establishing the multi-body system dynamic model of tank and mathematical model of control system.The results demonstrate that the prediction method of projectile-target intersection based on uncertainty analysis can effectively decrease the uncertainties of system,improve the prediction accuracy,and increase the hit probability.The adaptive robust constraint-following control can effectively restrain the uncertainties caused by road excitation and model error.展开更多
This paper focuses on the adaptive detection of range and Doppler dual-spread targets in non-homogeneous and nonGaussian sea clutter.The sea clutter from two polarimetric channels is modeled as a compound-Gaussian mod...This paper focuses on the adaptive detection of range and Doppler dual-spread targets in non-homogeneous and nonGaussian sea clutter.The sea clutter from two polarimetric channels is modeled as a compound-Gaussian model with different parameters,and the target is modeled as a subspace rangespread target model.The persymmetric structure is used to model the clutter covariance matrix,in order to reduce the reliance on secondary data of the designed detectors.Three adaptive polarimetric persymmetric detectors are designed based on the generalized likelihood ratio test(GLRT),Rao test,and Wald test.All the proposed detectors have constant falsealarm rate property with respect to the clutter texture,the speckle covariance matrix.Experimental results on simulated and measured data show that three adaptive detectors outperform the competitors in different clutter environments,and the proposed GLRT detector has the best detection performance under different parameters.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.12302435 and 12221002)。
文摘Shock wave caused by a sudden release of high-energy,such as explosion and blast,usually affects a significant range of areas.The utilization of a uniform fine mesh to capture sharp shock wave and to obtain precise results is inefficient in terms of computational resource.This is particularly evident when large-scale fluid field simulations are conducted with significant differences in computational domain size.In this work,a variable-domain-size adaptive mesh enlargement(vAME)method is developed based on the proposed adaptive mesh enlargement(AME)method for modeling multi-explosives explosion problems.The vAME method reduces the division of numerous empty areas or unnecessary computational domains by adaptively suspending enlargement operation in one or two directions,rather than in all directions as in AME method.A series of numerical tests via AME and vAME with varying nonintegral enlargement ratios and different mesh numbers are simulated to verify the efficiency and order of accuracy.An estimate of speedup ratio is analyzed for further efficiency comparison.Several large-scale near-ground explosion experiments with single/multiple explosives are performed to analyze the shock wave superposition formed by the incident wave,reflected wave,and Mach wave.Additionally,the vAME method is employed to validate the accuracy,as well as to investigate the performance of the fluid field and shock wave propagation,considering explosive quantities ranging from 1 to 5 while maintaining a constant total mass.The results show a satisfactory correlation between the overpressure versus time curves for experiments and numerical simulations.The vAME method yields a competitive efficiency,increasing the computational speed to 3.0 and approximately 120,000 times in comparison to AME and the fully fine mesh method,respectively.It indicates that the vAME method reduces the computational cost with minimal impact on the results for such large-scale high-energy release problems with significant differences in computational domain size.
基金National Natural Science Foundation of China(62373102)Jiangsu Natural Science Foundation(BK20221455)Anhui Provincial Key Research and Development Project(2022i01020013)。
文摘Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncertain systems characterized by unknown control directions and time-varying input delay lacks comprehensive solutions.In this paper,we propose an observerbased adaptive tracking controller to address this gap.Neural networks are utilized to handle uncertainty,and a unique coordinate transformation is employed to untangle the coupling between input delay and unknown control directions.Subsequently,a new auxiliary signal counters the impact of time-varying input delay,while a Nussbaum function is introduced to solve the problem of unknown control directions.The leverage of an advanced dynamic surface control technique avoids the“complexity explosion”and reduces boundary layer errors.Synthesizing these techniques ensures that all the closed-loop signals are semi-globally uniformly ultimately bounded(SGUUB),and the tracking error converges to a small region around the origin by selecting suitable parameters.Simulation examples are provided to demonstrate the feasibility of the proposed approach.
基金supported by the National Natural Science Foundation of China under Grant 62301051.
文摘Range-azimuth imaging of ground targets via frequency-modulated continuous wave(FMCW)radar is crucial for effective target detection.However,when the pitch of the moving array constructed during motion exceeds the physical array aperture,azimuth ambiguity occurs,making range-azimuth imaging on a moving platform challenging.To address this issue,we theoretically analyze azimuth ambiguity generation in sparse motion arrays and propose a dual-aperture adaptive processing(DAAP)method for suppressing azimuth ambiguity.This method combines spatial multiple-input multiple-output(MIMO)arrays with sparse motion arrays to achieve high-resolution range-azimuth imaging.In addition,an adaptive QR decomposition denoising method for sparse array signals based on iterative low-rank matrix approximation(LRMA)and regularized QR is proposed to preprocess sparse motion array signals.Simulations and experiments show that on a two-transmitter-four-receiver array,the signal-to-noise ratio(SNR)of the sparse motion array signal after noise suppression via adaptive QR decomposition can exceed 0 dB,and the azimuth ambiguity signal ratio(AASR)can be reduced to below-20 dB.
基金supported by the Foundation of Key Laboratory of Micro-inertial Instrument and Advanced Navigation Technology,Ministry of Education,Chinathe National Natural Science Foundation of China (61873064)
文摘Solar radio burst(SRB)is one of the main natural interference sources of Global Positioning System(GPS)signals and can reduce the signal-to-noise ratio(SNR),directly affecting the tracking performance of GPS receivers.In this paper,a tracking algorithm based on the adaptive Kalman filter(AKF)with carrier-to-noise ratio estimation is proposed and compared with the conventional second-order phase-locked loop tracking algo-rithms and the improved Sage-Husa adaptive Kalman filter(SHAKF)algorithm.It is discovered that when the SRBs occur,the improved SHAKF and the AKF with carrier-to-noise ratio estimation enable stable tracking to loop signals.The conven-tional second-order phase-locked loop tracking algorithms fail to track the receiver signal.The standard deviation of the carrier phase error of the AKF with carrier-to-noise ratio estimation out-performs 50.51%of the improved SHAKF algorithm,showing less fluctuation and better stability.The proposed algorithm is proven to show more excellent adaptability in the severe envi-ronment caused by the SRB occurrence and has better tracking performance.
基金supported by the National Natural Science Foundation of China (60804017 60835001+3 种基金 60904020 60974120)the Foundation of Doctor (20070286039 20070286001)
文摘The problem on stabilization for the system with distributed delays is researched. The distributed time-delay under consideration is assumed to be a constant time-delay, but not known exactly. A design method is proposed for a memory proportional and integral （PI） feedback controller with adaptation to distributed time-delay. The feedback controller with memory simultaneously contains the current state and the past distributed information of the addressed systems. The design for adaptation law to distributed delay is very concise. The controller can be derived by solving a set of linear matrix inequalities （LMIs）. Two numerical examples are given to illustrate the effectiveness of the design method.
基金Project(2010CB630903)supported by the National Basic Research Program of ChinaProject(31200382)supported by the Chinese Science Foundation for Distinguished Group,China
文摘A refractory gold concentrate with 19% arsenic was treated by a mixed moderately thermophiles in an airlift bioreactor through an adaptation protocol. The moderately thermophiles could respond well to 20%(w/v) pulp density with less than 10% loss of productivity, and resist arsenic up to 15 g/L. There were a lot of jarosite, arsenolite and sulfur, but not scorodite and ferric arsenate in the bioleached residue. Jarosite passivation and lower sulfur-oxidizing activity of the cells due to the toxicity of the high concentrations of soluble arsenic and iron ions at low p H value should mainly response for the incomplete extraction at high pulp density. The initial bacterial community did not change in nature except for new found P aeruginosa ANSC, but sulfur-oxidizing microorganisms have been dominant microorganisms after a long time of adaptation. Pseudomonas aeruginosa originating from the gold concentrate should be closely relative to the metabolism of the organic matters contained in the refractory gold concentrate.
文摘One of the challenges the world is facing today is global climate change and its associated impacts. Uganda is a climate sensitive country with over 90% of the population dependent on climate sensitive sectors.Gradual and sudden variations in climatic parameters will therefore render the livelihoods of Ugandans very vulnerable.A number of approaches to enhance the resilience of communities to
文摘Climate change is one of the most significant environment issues in the whole world today. And it is one of the most complex challenges of the humanities faced in the 21st century. Climate Change is impacted on our global; nobody can avoid the influence of climate change. The local adaptation strategies on climate change are very important to contribute the mitigation and poverty stricken situation, both in China and in the world. We chose a typical China＇s province as a case to analyze the impact of climate change on the region （such as agricultural, natural ecosystems, water resources, as well as local people healthy condition）, and how the local government and local residences face the impact of the climate change influence, and summarized several strategies on climate change of the area in a sustainable development way.
文摘Mitigation and adaptation are two principle strategies for managing human-induced climate change. Agriculture plays a duet role in climate change. It has been a major source of greenhouse gases to the atmosphere. It is also one of the sectors most vulnerable to the risks and impacts of global climate change. This paper first indentified the mitigative and adaptative options and potential in agriculture, then addressed the integrated analysis of mitigation and adaptation and its benefits for agriculture. Finally, it discussed the implications to Chinese agriculture in dealing with the global climate change.
基金This work is partly supported by China 863 Project Foundation
文摘The explanation and simulation of the natural and artificial intelligence are the central goals of the studies of Neuroscience, Psychology, Artificial Intelligence and Cognitive Science. This paper first gives an introduction to the core topics and approaches in the study. Then, GAF--a general adaptive framework for neural system is proposed. Interdisciplinary discussions around the adaptation of the human nervous system are presented. Rules describing the theory of adaptation of the nervous system are provided.
基金China Education Association Professional Committee of Foreign Language Teaching Five-Year Plan Research Fund Projects(No.NAFLE0314057)State Language Commission research base of Chinese Foreign Strategy Research Center research(No.WYZ L201401)
文摘In Cross-cultural exchanges,there are existing differences between cultures;cultural rejection of psychological and cultural hegemony of thinking leads to widespread cultural conflict. It will cause conflict,including cultural,forms and exchanges. Cultural conflict causes cross-cultural prejudices and opposition,which lead to cultural adaptation barriers; therefore cross-cultural exchanges must adhere to civilization dialogue on the basis of cultural awareness and self-confidence. Respect for cultural differences with equal attitude and advocate for solution to cultural conflict are needed to improve the cultural adaptability.
基金supported in part by the Nation Natural Science Foundation of China under Grant No.52175099China Postdoctoral Science Foundation under Grant No.2020M671494Jiangsu Planned Projects for Postdoctoral Research Funds under Grant No.2020Z179。
文摘A tracking stability control problem for the vertical electric stabilization system of moving tank based on adaptive robust servo control is addressed.This paper mainly focuses on two types of possibly fast timevarying but bounded uncertainty within the vertical electric stabilization system:model parameter uncertainty and uncertain nonlinearity.First,the vertical electric stabilization system is constructed as an uncertain nonlinear dynamic system that can reflect the practical mechanics transfer process of the system.Second,the dynamical equation in the form of state space is established by designing the angular tracking error.Third,the comprehensive parameter of system uncertainty is designed to estimate the most conservative effects of uncertainty.Finally,an adaptive robust servo control which can effectively handle the combined effects of complex nonlinearity and uncertainty is proposed.The feasibility of the proposed control strategy under the practical physical condition is validated through the tests on the experimental platform.This paper pioneers the introduction of the internal nonlinearity and uncertainty of the vertical electric stabilization system into the settlement of the tracking stability control problem,and validates the advanced servo control strategy through experiment for the first time.
基金supported by the 2021 Open Project Fund of Science and Technology on Electromechanical Dynamic Control Laboratory,grant number 212-C-J-F-QT-2022-0020China Postdoctoral Science Foundation,grant number 2021M701713+1 种基金Postgraduate Research&Practice Innovation Program of Jiangsu Province,grant number KYCX23_0511the Jiangsu Funding Program for Excellent Postdoctoral Talent,grant number 20220ZB245。
文摘The phenomenon of a target echo peak overlapping with the backscattered echo peak significantly undermines the detection range and precision of underwater laser fuzes.To overcome this issue,we propose a four-quadrant dual-beam circumferential scanning laser fuze to distinguish various interference signals and provide more real-time data for the backscatter filtering algorithm.This enhances the algorithm loading capability of the fuze.In order to address the problem of insufficient filtering capacity in existing linear backscatter filtering algorithms,we develop a nonlinear backscattering adaptive filter based on the spline adaptive filter least mean square(SAF-LMS)algorithm.We also designed an algorithm pause module to retain the original trend of the target echo peak,improving the time discrimination accuracy and anti-interference capability of the fuze.Finally,experiments are conducted with varying signal-to-noise ratios of the original underwater target echo signals.The experimental results show that the average signal-to-noise ratio before and after filtering can be improved by more than31 d B,with an increase of up to 76%in extreme detection distance.
基金supported in part by the National Key R&D Program of China under Grant 2021YFB2011300the National Natural Science Foundation of China under Grant 52075262。
文摘This paper mainly focuses on the development of a learning-based controller for a class of uncertain mechanical systems modeled by the Euler-Lagrange formulation.The considered system can depict the behavior of a large class of engineering systems,such as vehicular systems,robot manipulators and satellites.All these systems are often characterized by highly nonlinear characteristics,heavy modeling uncertainties and unknown perturbations,therefore,accurate-model-based nonlinear control approaches become unavailable.Motivated by the challenge,a reinforcement learning(RL)adaptive control methodology based on the actor-critic framework is investigated to compensate the uncertain mechanical dynamics.The approximation inaccuracies caused by RL and the exogenous unknown disturbances are circumvented via a continuous robust integral of the sign of the error(RISE)control approach.Different from a classical RISE control law,a tanh(·)function is utilized instead of a sign(·)function to acquire a more smooth control signal.The developed controller requires very little prior knowledge of the dynamic model,is robust to unknown dynamics and exogenous disturbances,and can achieve asymptotic output tracking.Eventually,co-simulations through ADAMS and MATLAB/Simulink on a three degrees-of-freedom(3-DOF)manipulator and experiments on a real-time electromechanical servo system are performed to verify the performance of the proposed approach.
文摘Yes, we perceive that the environment in which comp an ies operate, is changing at higher speeds then before. Globalisation, higher inn ovation rates, customisation, more intense competition, technological developmen ts account for these changes effecting the way industrial companies operate and eventually their structures and processes. Companies have to adapt themselves to these changes. The question arose whether the approach of the Section Industria l Organisation and Management that it has practised for redesign of processes an d organisational structures also withholds in this era of continuous change. Sec ondly, firms are also looking for contingencies in processes and structures to i mprove their chances for survival. These two questions into the processes and st ructures within the firm that it needs to support adaptation to the ever-changi ng environment direct this research. Industrial companies will have to increase to their Complexity Handling Capabili ty, the ability to cope with changes in its environment and imposed complexity p ouring in from the environment. To do so, they might decrease their internal com plexity through redefining their organisations and product structure. The effect of these measurements seems limited; more might be won by learning to increase its base of capabilities. The increase of capabilities holds parallels to the de velopment of species in biology and paleontology for which two models exist: the punctuated equilibrium and the phyletic gradualism. The punctuated equilibr ium supposes that periods of turmoil are interchanged by periods of fermentation giving rise to new variants and products (for companies). The phyletic graduali sm relies on the development of characteristics in species that are initially ha rd to detect but will lead at the end to new species. Whatever might be true for biology and palaeontology, these two models appear as a possibility for cla ssifying the theories of organisational change. Also, these theories put forward insights in the development of organisations that stretch beyond the classical insights on the adaptation of organisations based on one-time interventions ass uming balance between demands from the environment and internal structure. Little research has been done so far in this field of adaptation of companies to the dynamics of the environment. Most literature does not address the internal processes and structures necessary for coping with change. This paper will prese nt initial findings of case studies of graduation theses that took place to generate data on the validity of the evolutionary models. This way the research should not only lead to a theoretical framework but also to practical implicatio ns for industrial companies.
基金the National Natural Science Foundation of China(No.52275062)and(No.52075262).
文摘Since backlash nonlinearity is inevitably existing in actuators for bidirectional stabilization system of allelectric tank,it behaves more drastically in high maneuvering environments.In this work,the accurate tracking control for bidirectional stabilization system of moving all-electric tank with actuator backlash and unmodeled disturbance is solved.By utilizing the smooth adaptive backlash inverse model,a nonlinear robust adaptive feedback control scheme is presented.The unknown parameters and unmodelled disturbance are addressed separately through the derived parametric adaptive function and the continuous nonlinear robust term.Because the unknown backlash parameters are updated via adaptive function and the backlash effect can be suppressed successfully by inverse operation,which ensures the system stability.Meanwhile,the system disturbance in the high maneuverable environment can be estimated with the constructed adaptive law online improving the engineering practicality.Finally,Lyapunov-based analysis proves that the developed controller can ensure the tracking error asymptotically converges to zero even with unmodeled disturbance and unknown actuator backlash.Contrast co-simulations and experiments illustrate the advantages of the proposed approach.
基金supported by the National Natural Science Foundation of China(62371049)。
文摘In engineering application,there is only one adaptive weights estimated by most of traditional early warning radars for adaptive interference suppression in a pulse reputation interval(PRI).Therefore,if the training samples used to calculate the weight vector does not contain the jamming,then the jamming cannot be removed by adaptive spatial filtering.If the weight vector is constantly updated in the range dimension,the training data may contain target echo signals,resulting in signal cancellation effect.To cope with the situation that the training samples are contaminated by target signal,an iterative training sample selection method based on non-homogeneous detector(NHD)is proposed in this paper for updating the weight vector in entire range dimension.The principle is presented,and the validity is proven by simulation results.
基金The National Natural Science Foundation of China (32371993)The Natural Science Research Key Project of Anhui Provincial University(2022AH040125&2023AH040135)The Key Research and Development Plan of Anhui Province (202204c06020022&2023n06020057)。
文摘This study aimed to address the challenge of accurately and reliably detecting tomatoes in dense planting environments,a critical prerequisite for the automation implementation of robotic harvesting.However,the heavy reliance on extensive manually annotated datasets for training deep learning models still poses significant limitations to their application in real-world agricultural production environments.To overcome these limitations,we employed domain adaptive learning approach combined with the YOLOv5 model to develop a novel tomato detection model called as TDA-YOLO(tomato detection domain adaptation).We designated the normal illumination scenes in dense planting environments as the source domain and utilized various other illumination scenes as the target domain.To construct bridge mechanism between source and target domains,neural preset for color style transfer is introduced to generate a pseudo-dataset,which served to deal with domain discrepancy.Furthermore,this study combines the semi-supervised learning method to enable the model to extract domain-invariant features more fully,and uses knowledge distillation to improve the model's ability to adapt to the target domain.Additionally,for purpose of promoting inference speed and low computational demand,the lightweight FasterNet network was integrated into the YOLOv5's C3 module,creating a modified C3_Faster module.The experimental results demonstrated that the proposed TDA-YOLO model significantly outperformed original YOLOv5s model,achieving a mAP(mean average precision)of 96.80%for tomato detection across diverse scenarios in dense planting environments,increasing by 7.19 percentage points;Compared with the latest YOLOv8 and YOLOv9,it is also 2.17 and 1.19 percentage points higher,respectively.The model's average detection time per image was an impressive 15 milliseconds,with a FLOPs(floating point operations per second)count of 13.8 G.After acceleration processing,the detection accuracy of the TDA-YOLO model on the Jetson Xavier NX development board is 90.95%,the mAP value is 91.35%,and the detection time of each image is 21 ms,which can still meet the requirements of real-time detection of tomatoes in dense planting environment.The experimental results show that the proposed TDA-YOLO model can accurately and quickly detect tomatoes in dense planting environment,and at the same time avoid the use of a large number of annotated data,which provides technical support for the development of automatic harvesting systems for tomatoes and other fruits.
基金financially supported by the National Natural Science Foundation of China(Grant 52175099)the China Postdoctoral Science Foundation(Grant No.2020M671494)+1 种基金the Jiangsu Planned Projects for Postdoctoral Research Funds(Grant No.2020Z179)the Nanjing University of Science and Technology Independent Research Program(Grant No.30920021105)。
文摘To improve the hit probability of tank at high speed,a prediction method of projectile-target intersection based on adaptive robust constraint-following control and interval uncertainty analysis is proposed.The method proposed provides a novel way to predict the impact point of projectile for moving tank.First,bidirectional stability constraints and stability constraint-following error are constructed using the Udwadia-Kalaba theory,and an adaptive robust constraint-following controller is designed considering uncertainties.Second,the exterior ballistic ordinary differential equation with uncertainties is integrated into the controller,and the pointing control of stability system is extended to the impact-point control of projectile.Third,based on the interval uncertainty analysis method combining Chebyshev polynomial expansion and affine arithmetic,a prediction method of projectile-target intersection is proposed.Finally,the co-simulation experiment is performed by establishing the multi-body system dynamic model of tank and mathematical model of control system.The results demonstrate that the prediction method of projectile-target intersection based on uncertainty analysis can effectively decrease the uncertainties of system,improve the prediction accuracy,and increase the hit probability.The adaptive robust constraint-following control can effectively restrain the uncertainties caused by road excitation and model error.
基金supported by the National Natural Science Foundation of China(62371382,62071346)the Science,Technology&Innovation Project of Xiong’an New Area(2022XAGG0181)the Special Funds for Creative Research(2022C61540)。
文摘This paper focuses on the adaptive detection of range and Doppler dual-spread targets in non-homogeneous and nonGaussian sea clutter.The sea clutter from two polarimetric channels is modeled as a compound-Gaussian model with different parameters,and the target is modeled as a subspace rangespread target model.The persymmetric structure is used to model the clutter covariance matrix,in order to reduce the reliance on secondary data of the designed detectors.Three adaptive polarimetric persymmetric detectors are designed based on the generalized likelihood ratio test(GLRT),Rao test,and Wald test.All the proposed detectors have constant falsealarm rate property with respect to the clutter texture,the speckle covariance matrix.Experimental results on simulated and measured data show that three adaptive detectors outperform the competitors in different clutter environments,and the proposed GLRT detector has the best detection performance under different parameters.
