The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and wi...The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and with multivariable nonlinear interaction of microwave and materials. The conventional PID control strategy incorporated with optimization GA was put forward to maintain the optimum drying temperature in order to keep the moisture content below 1%, whose adaptation ability included the cost function of optimization GA according to the output change. Simulations on five different industrial process models and practical temperature process control system for selenium-enriched slag drying intensively by using IMDRDWM were carried out systematically, indicating the reliability and effectiveness of control design. The parameters of proposed control design are all on-line implemented without iterative predictive calculations, and the closed-loop system stability is guaranteed, which makes the developed scheme simpler in its synthesis and application, providing the practical guidelines for the control implementation and the parameter design.展开更多
Double self-adaptive fuzzy PID algorithm-based control strategy was proposed to construct quasi-cascade control system to control the speed of the acid-pickling process of titanium plates and strips. It is very useful...Double self-adaptive fuzzy PID algorithm-based control strategy was proposed to construct quasi-cascade control system to control the speed of the acid-pickling process of titanium plates and strips. It is very useful in overcoming non-linear dynamic behavior, uncertain and time-varying parameters, un-modeled dynamics, and couples between the automatic turbulence control (ATC) and the automatic acid temperature control (AATC) with varying parameters during the operation process. The quasi-cascade control system of inner and outer loop self-adaptive fuzzy PID controller was built, which could effectively control the pickling speed of plates and strips. The simulated results and real application indicate that the plates and strips acid pickling speed control system has good performances of adaptively tracking the parameter variations and anti-disturbances, which ensures the match of acid pickling temperature and turbulence of flowing with acid pickling speed, improving the surface quality of plates and strips acid pickling, and energy efficiency.展开更多
Cooperative jamming weapon-target assignment （CJWTA） problem is a key issue in electronic countermeasures （ECM）. Some symbols which relevant to the CJWTA are defined firstly. Then, a formulation of jamming fitness...Cooperative jamming weapon-target assignment （CJWTA） problem is a key issue in electronic countermeasures （ECM）. Some symbols which relevant to the CJWTA are defined firstly. Then, a formulation of jamming fitness is presented. Final y, a model of the CJWTA problem is constructed. In order to solve the CJWTA problem efficiently, a self-adaptive learning based discrete differential evolution （SLDDE） algorithm is proposed by introduc-ing a self-adaptive learning mechanism into the traditional discrete differential evolution algorithm. The SLDDE algorithm steers four candidate solution generation strategies simultaneously in the framework of the self-adaptive learning mechanism. Computa-tional simulations are conducted on ten test instances of CJWTA problem. The experimental results demonstrate that the proposed SLDDE algorithm not only can generate better results than only one strategy based discrete differential algorithms, but also outper-forms two algorithms which are proposed recently for the weapon-target assignment problems.展开更多
An improved ensemble empirical mode decomposition(EEMD) algorithm is described in this work, in which the sifting and ensemble number are self-adaptive. In particular, the new algorithm can effectively avoid the mode ...An improved ensemble empirical mode decomposition(EEMD) algorithm is described in this work, in which the sifting and ensemble number are self-adaptive. In particular, the new algorithm can effectively avoid the mode mixing problem. The algorithm has been validated with a simulation signal and locomotive bearing vibration signal. The results show that the proposed self-adaptive EEMD algorithm has a better filtering performance compared with the conventional EEMD. The filter results further show that the feature of the signal can be distinguished clearly with the proposed algorithm, which implies that the fault characteristics of the locomotive bearing can be detected successfully.展开更多
The aim of this paper is to achieve the radio frequency stealth(RFS) during the course of tracking by controlling the radiation energy and the interval of a radar. Firstly, we build the model of probability of interce...The aim of this paper is to achieve the radio frequency stealth(RFS) during the course of tracking by controlling the radiation energy and the interval of a radar. Firstly, we build the model of probability of interception with the once radiation during the course of tracking. Secondly, we establish the model of the cumulative probability of interception to describe the effect of RFS throughout the tracking process and obtain two solutions that are minimizing the probability of interception and the radiation times to reduce the cumulative probability of interception. Thirdly, we propose a self-adapting radiation energy control method(SARE)to minimize the probability of interception. Fourthly, we propose a self-adapting radiation interval control method(SARI) to minimize radiation times. Fifthly, combining SARE with SARI, we propose a SARE-SARI control method(SAEI) during the course of tracking.Finally, we compare SAEI with two others by simulation, and the results show the effect of RFS of SAEI is better than the other two,but we have to make a trade-off between the ability of RFS and the effect of tracking.展开更多
In order to solve the non-linear and high-dimensional optimization problems more effectively, an improved self-adaptive membrane computing(ISMC) optimization algorithm was proposed. The proposed ISMC algorithm applied...In order to solve the non-linear and high-dimensional optimization problems more effectively, an improved self-adaptive membrane computing(ISMC) optimization algorithm was proposed. The proposed ISMC algorithm applied improved self-adaptive crossover and mutation formulae that can provide appropriate crossover operator and mutation operator based on different functions of the objects and the number of iterations. The performance of ISMC was tested by the benchmark functions. The simulation results for residue hydrogenating kinetics model parameter estimation show that the proposed method is superior to the traditional intelligent algorithms in terms of convergence accuracy and stability in solving the complex parameter optimization problems.展开更多
As a core part of the electronic warfare(EW) system,de-interleaving is used to separate interleaved radar signals. As interleaved radar pulses become more complex and denser, intelligent classification of radar signal...As a core part of the electronic warfare(EW) system,de-interleaving is used to separate interleaved radar signals. As interleaved radar pulses become more complex and denser, intelligent classification of radar signals has become very important. The self-organizing feature map(SOFM) is an excellent artificial neural network, which has huge advantages in intelligent classification of complex data. However, the de-interleaving process based on SOFM is faced with the problems that the initialization of the map size relies on prior information and the network topology cannot be adaptively adjusted. In this paper, an SOFM with self-adaptive network topology(SANT-SOFM) algorithm is proposed to solve the above problems. The SANT-SOFM algorithm first proposes an adaptive proliferation algorithm to adjust the map size, so that the initialization of the map size is no longer dependent on prior information but is gradually adjusted with the input data. Then,structural optimization algorithms are proposed to gradually optimize the topology of the SOFM network in the iterative process,constructing an optimal SANT. Finally, the optimized SOFM network is used for de-interleaving radar signals. Simulation results show that SANT-SOFM could get excellent performance in complex EW environments and the probability of getting the optimal map size is over 95% in the absence of priori information.展开更多
There are many population-based stochastic search algorithms for solving optimization problems. However, the universality and robustness of these algorithms are still unsatisfactory. This paper proposes an enhanced se...There are many population-based stochastic search algorithms for solving optimization problems. However, the universality and robustness of these algorithms are still unsatisfactory. This paper proposes an enhanced self-adaptiveevolutionary algorithm （ESEA） to overcome the demerits above. In the ESEA, four evolutionary operators are designed to enhance the evolutionary structure. Besides, the ESEA employs four effective search strategies under the framework of the self-adaptive learning. Four groups of the experiments are done to find out the most suitable parameter values for the ESEA. In order to verify the performance of the proposed algorithm, 26 state-of-the-art test functions are solved by the ESEA and its competitors. The experimental results demonstrate that the universality and robustness of the ESEA out-perform its competitors.展开更多
Region partition(RP) is the key technique to the finite element parallel computing(FEPC),and its performance has a decisive influence on the entire process of analysis and computation.The performance evaluation index ...Region partition(RP) is the key technique to the finite element parallel computing(FEPC),and its performance has a decisive influence on the entire process of analysis and computation.The performance evaluation index of RP method for the three-dimensional finite element model(FEM) has been given.By taking the electric field of aluminum reduction cell(ARC) as the research object,the performance of two classical RP methods,which are Al-NASRA and NGUYEN partition(ANP) algorithm and the multi-level partition(MLP) method,has been analyzed and compared.The comparison results indicate a sound performance of ANP algorithm,but to large-scale models,the computing time of ANP algorithm increases notably.This is because the ANP algorithm determines only one node based on the minimum weight and just adds the elements connected to the node into the sub-region during each iteration.To obtain the satisfied speed and the precision,an improved dynamic self-adaptive ANP(DSA-ANP) algorithm has been proposed.With consideration of model scale,complexity and sub-RP stage,the improved algorithm adaptively determines the number of nodes and selects those nodes with small enough weight,and then dynamically adds these connected elements.The proposed algorithm has been applied to the finite element analysis(FEA) of the electric field simulation of ARC.Compared with the traditional ANP algorithm,the computational efficiency of the proposed algorithm has been shortened approximately from 260 s to 13 s.This proves the superiority of the improved algorithm on computing time performance.展开更多
A fast self-adapting high-order sliding mode(FSHOSM)controller is designed for a class of nonlinear systems with unknown uncertainties.As for uncertainty-free nonlinear system,a new switching condition is introduced i...A fast self-adapting high-order sliding mode(FSHOSM)controller is designed for a class of nonlinear systems with unknown uncertainties.As for uncertainty-free nonlinear system,a new switching condition is introduced into the standard geometric homogeneity.Different from the existing geometric homogeneity method,both state variables and their derivatives are considered to bring a reasonable effective switching condition.As a result,a faster convergence rate of state variables is achieved.Furthermore,based on the integral sliding mode(ISM)and above geometric homogeneity,a self-adapting high-order sliding mode(HOSM)control law is proposed for a class of nonlinear systems with uncertainties.The resulting controller allows the closed-loop system to conduct with the expected properties of strong robustness and fast convergence.Stable analysis of the nonlinear system is also proved based on the Lyapunov approach.The effectiveness of the resulting controller is verified by several simulation results.展开更多
This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hype...This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hypersonic vehicles.In order to increase the control amount,this online control legislation makes use of model predictive control(MPC)that is based on the concept of iterative learning control(ILC).By using offline data to decrease the linearized model’s faults,the strategy may effectively increase the robustness of the control system and guarantee that disturbances can be suppressed.An adaptive fault observer is created based on the suggested ILMPC approach in order to enhance overall fault tolerance by estimating and compensating for actuator disturbance and fault degree.During the derivation process,a linearized model of longitudinal dynamics is established.The suggested ILMPC approach is likely to be used in the design of hypersonic vehicle control systems since numerical simulations have demonstrated that it can decrease tracking error and speed up convergence when compared to the offline controller.展开更多
This paper presents an investigation on the target-guided coordinated control(TACC)of unmanned surface vehicles(USVs).In the scenario of tracking non-cooperative targets,the status information of the target can only b...This paper presents an investigation on the target-guided coordinated control(TACC)of unmanned surface vehicles(USVs).In the scenario of tracking non-cooperative targets,the status information of the target can only be obtained by some USVs.In order to achieve semi-encirclement tracking of noncooperative targets under maritime security conditions,a fixed-time tracking control method based on dynamic surface control(DSC)is proposed in this paper.Firstly,a novel TACC architecture with decoupled kinematic control law and decoupled kinetic control law was designed to reduce the complexity of control system design.Secondly,the proposed DSC-based target-guided kinematic control law including tracking points pre-allocation strategy and sigmoid artificial potential functions(SigAPFs)can avoid collisions during tracking process and optimize kinematic control output.Finally,a fixed-time TACC system was proposed to achieve fast convergence of kinematic and kinetics errors.The effectiveness of the proposed TACC approach in improving target tracking safety and reducing control output chattering was verified by simulation comparison results.展开更多
The present technical paper outlines the details of the controlled blasting techniques used to optimize blasting pattern for excavation of hard rock near the Bhira Earthen Dam in Maharashtra,India.In this connection,a...The present technical paper outlines the details of the controlled blasting techniques used to optimize blasting pattern for excavation of hard rock near the Bhira Earthen Dam in Maharashtra,India.In this connection,a series of experimental blasts were conducted by adjusting various blast design parameters at project site.The safe charge weight per delay was kept between 0.125 and 0.375 kg.The outcomes of these experimental blasts were analyzed to recommend optimized blasting patterns and methods for the overall excavation process during actual blasting operations.Blast design parameters,including the maximum quantity of explosive per delay,hole depth,burden and spacing between holes were optimized by using a site-specific attenuation equation,taking into account the proximity of the dam and tunnel from the blasting area.Peak particle velocity(PPV)level of 10 mm/s and 50 mm/s respectively were adopted as the safe vibration level for ensuring safety of the Bhira Earthen Dam and the nearby tunnel from the adverse effects of blast vibrations by analyzing the dominant frequency of ground vibrations observed and also by reviewing various international standards.Frequency of the ground vibrations observed on the dam and tunnel from majority of the blasts was found to be more than 10 Hz and 50 Hz respectively.During the entire period of blasting,the blast vibrations were recorded to be far lower than the safe vibration level set for these structures.Maximum Vibration level of about 0.8 mm/s and 35 mm/s were observed on dam and tunnel respectively which are far lower than the safe vibration level adopted for these structures.Hence,the entire excavation work was completed successfully and safely,without endangering the safety of dam or tunnel.展开更多
The liquid cooling system(LCS)of fuel cells is challenged by significant time delays,model uncertainties,pump and fan coupling,and frequent disturbances,leading to overshoot and control oscillations that degrade tempe...The liquid cooling system(LCS)of fuel cells is challenged by significant time delays,model uncertainties,pump and fan coupling,and frequent disturbances,leading to overshoot and control oscillations that degrade temperature regulation performance.To address these challenges,we propose a composite control scheme combining fuzzy logic and a variable-gain generalized supertwisting algorithm(VG-GSTA).Firstly,a one-dimensional(1D)fuzzy logic controler(FLC)for the pump ensures stable coolant flow,while a two-dimensional(2D)FLC for the fan regulates the stack temperature near the reference value.The VG-GSTA is then introduced to eliminate steady-state errors,offering resistance to disturbances and minimizing control oscillations.The equilibrium optimizer is used to fine-tune VG-GSTA parameters.Co-simulation verifies the effectiveness of our method,demonstrating its advantages in terms of disturbance immunity,overshoot suppression,tracking accuracy and response speed.展开更多
The operating environment of the diesel engine air path system is complex and may be affected by external random disturbances.Potentially leading to faults.This paper addresses the fault-tolerant control problem of th...The operating environment of the diesel engine air path system is complex and may be affected by external random disturbances.Potentially leading to faults.This paper addresses the fault-tolerant control problem of the diesel engine air path system,assuming that the system may simultaneously be affected by actuator faults and external random disturbances,a disturbance observer-based sliding mode controller is designed.Through the linear matrix inequality technique for solving observer and controller gains,optimal gain matrices can be obtained,eliminating the manual adjustment process of controller parameters and reducing the chattering phenomenon of the sliding mode surface.Finally,the effectiveness of the proposed method is verified through simulation analysis.展开更多
The graded density impactor(GDI)dynamic loading technique is crucial for acquiring the dynamic physical property parameters of materials used in weapons.The accuracy and timeliness of GDI structural design are key to ...The graded density impactor(GDI)dynamic loading technique is crucial for acquiring the dynamic physical property parameters of materials used in weapons.The accuracy and timeliness of GDI structural design are key to achieving controllable stress-strain rate loading.In this study,we have,for the first time,combined one-dimensional fluid computational software with machine learning methods.We first elucidated the mechanisms by which GDI structures control stress and strain rates.Subsequently,we constructed a machine learning model to create a structure-property response surface.The results show that altering the loading velocity and interlayer thickness has a pronounced regulatory effect on stress and strain rates.In contrast,the impedance distribution index and target thickness have less significant effects on stress regulation,although there is a matching relationship between target thickness and interlayer thickness.Compared with traditional design methods,the machine learning approach offers a10^(4)—10^(5)times increase in efficiency and the potential to achieve a global optimum,holding promise for guiding the design of GDI.展开更多
Projective synchronization problems of a drive system and a particular response network were investigated,where the drive system is an arbitrary system with n+1 dimensions;it may be a linear or nonlinear system,and ev...Projective synchronization problems of a drive system and a particular response network were investigated,where the drive system is an arbitrary system with n+1 dimensions;it may be a linear or nonlinear system,and even a chaotic or hyperchaotic system,the response network is complex system coupled by N nodes,and every node is showed by the approximately linear part of the drive system.Only controlling any one node of the response network by designed controller can achieve the projective synchronization.Some numerical examples were employed to verify the effectiveness and correctness of the designed controller.展开更多
OBJECTIVE To investigate the intervention effects of tissue-bone homeostasis manipulation(TBHM)on peripatellar biomechanical parameters and knee joint function in knee osteoarthritis(KOA)patients.METHODS Sixty patient...OBJECTIVE To investigate the intervention effects of tissue-bone homeostasis manipulation(TBHM)on peripatellar biomechanical parameters and knee joint function in knee osteoarthritis(KOA)patients.METHODS Sixty patients with KOA(Kellgren-Lawrence gradeⅡ-Ⅲ)were recruited from the Acupuncture-Moxibustion Rehabilitation Department,Anhui University of Chinese Medicine between October 2024 and May 2025.Participants were randomized into a TBHM group(n=30)or a transcutaneous electrical neuromuscular stimulation(TENS)group(n=30).Using two-way repeated measures ANOVA,biomechanical indicators,including rectus femoris tension,vastus medialis tension,vastus lateralis tension,patellar ligament tension,lateral patellar displacement(LPD),medial patellar displacement(MPD),normalized patellar mobility(LPD/patellar width[PW],MPD/PW),knee flexion range of motion,and functional indicators,including KOOS subscales,time up and go test(TUGT),were compared between groups at baseline and after 6 weeks of intervention.RESULTS After intervention,all biomechanical and knee joint function indicators in the TBHM group were significantly improved(P<0.05,P<0.01),while only the vastus medialis tension,TUGT and KOOS Pain,ADL and QoL scores in the control group were significantly improved(P<0.01).The improvement amplitudes of biomechanical indicators in the TBHM group,including rectus femoris tension,vastus lateralis tension,patellar ligament tension,MPD/PW,LPD/PW and knee flexion range of motion were better than those in the control group(P<0.05,P<0.01).In the functional evaluation,the interaction effects of the TBHM group in all dimensions of the KOOS score and TUGT were statistically significant(P<0.05,P<0.01).Post-hoc simple effect analysis confirmed that there were significant differences in the above indicators between the two groups after intervention(P<0.05),and all indicators showed a significant main effect of time(P<0.01),suggesting that the intervention measures had continuous and cumulative curative effects.CONCLUSION TBHM effectively improves joint function and quality of life in KOA patients by restoring dynamic equilibrium in soft tissue tension and patellar mobility,ultimately achieving the therapeutic goal of concurrent tissue-bone management.展开更多
In view of the deficiencies in aspects such as failure rate requirements and analysis assumptions of advisory circular,this paper investigates the sources of high safety requirements,and the top-down design method for...In view of the deficiencies in aspects such as failure rate requirements and analysis assumptions of advisory circular,this paper investigates the sources of high safety requirements,and the top-down design method for the flight control system life cycle.Correspondingly,measures are proposed,including enhancing the safety target value to 10^(−10)per flight hour and implementing development assurance.In view of the shortcomings of mainstream aircraft flight control systems,such as weak backup capability and complex fault reconfiguration logic,improvements have been made to the system’s operating modes,control channel allocation,and common mode failure mitigation schemes based on the existing flight control architecture.The flight control design trends and philosophies have been analyzed.A flight control system architecture scheme is proposed,which includes three operating modes and multi-level voters/monitors,three main control channels,and a backup system independent of the main control system,which has been confirmed through functional modeling simulations.The proposed method plays an important role in the architecture design of safety-critical flight control system.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
基金Project(51090385) supported by the Major Program of National Natural Science Foundation of ChinaProject(2011IB001) supported by Yunnan Provincial Science and Technology Program,China+1 种基金Project(2012DFA70570) supported by the International Science & Technology Cooperation Program of ChinaProject(2011IA004) supported by the Yunnan Provincial International Cooperative Program,China
文摘The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and with multivariable nonlinear interaction of microwave and materials. The conventional PID control strategy incorporated with optimization GA was put forward to maintain the optimum drying temperature in order to keep the moisture content below 1%, whose adaptation ability included the cost function of optimization GA according to the output change. Simulations on five different industrial process models and practical temperature process control system for selenium-enriched slag drying intensively by using IMDRDWM were carried out systematically, indicating the reliability and effectiveness of control design. The parameters of proposed control design are all on-line implemented without iterative predictive calculations, and the closed-loop system stability is guaranteed, which makes the developed scheme simpler in its synthesis and application, providing the practical guidelines for the control implementation and the parameter design.
基金Project(51090385) supported by the National Natural Science Foundation of ChinaProject(2001IB001) supported by Yunnan Provincial Science and Technology Fund, China
文摘Double self-adaptive fuzzy PID algorithm-based control strategy was proposed to construct quasi-cascade control system to control the speed of the acid-pickling process of titanium plates and strips. It is very useful in overcoming non-linear dynamic behavior, uncertain and time-varying parameters, un-modeled dynamics, and couples between the automatic turbulence control (ATC) and the automatic acid temperature control (AATC) with varying parameters during the operation process. The quasi-cascade control system of inner and outer loop self-adaptive fuzzy PID controller was built, which could effectively control the pickling speed of plates and strips. The simulated results and real application indicate that the plates and strips acid pickling speed control system has good performances of adaptively tracking the parameter variations and anti-disturbances, which ensures the match of acid pickling temperature and turbulence of flowing with acid pickling speed, improving the surface quality of plates and strips acid pickling, and energy efficiency.
基金supported by the Fundamental Research Funds for the Central Universities(NZ2013306)the Funding of Jiangsu Innovation Program for Graduate Education(CXLX11 0203)
文摘Cooperative jamming weapon-target assignment （CJWTA） problem is a key issue in electronic countermeasures （ECM）. Some symbols which relevant to the CJWTA are defined firstly. Then, a formulation of jamming fitness is presented. Final y, a model of the CJWTA problem is constructed. In order to solve the CJWTA problem efficiently, a self-adaptive learning based discrete differential evolution （SLDDE） algorithm is proposed by introduc-ing a self-adaptive learning mechanism into the traditional discrete differential evolution algorithm. The SLDDE algorithm steers four candidate solution generation strategies simultaneously in the framework of the self-adaptive learning mechanism. Computa-tional simulations are conducted on ten test instances of CJWTA problem. The experimental results demonstrate that the proposed SLDDE algorithm not only can generate better results than only one strategy based discrete differential algorithms, but also outper-forms two algorithms which are proposed recently for the weapon-target assignment problems.
基金Project(61573381)supported by the National Natural Science Foundation of ChinaProject(2012AA051601)supported by the National High-tech Research and Development Program of China
文摘An improved ensemble empirical mode decomposition(EEMD) algorithm is described in this work, in which the sifting and ensemble number are self-adaptive. In particular, the new algorithm can effectively avoid the mode mixing problem. The algorithm has been validated with a simulation signal and locomotive bearing vibration signal. The results show that the proposed self-adaptive EEMD algorithm has a better filtering performance compared with the conventional EEMD. The filter results further show that the feature of the signal can be distinguished clearly with the proposed algorithm, which implies that the fault characteristics of the locomotive bearing can be detected successfully.
基金supported by the National Natural Science Foundation of China(61472441)
文摘The aim of this paper is to achieve the radio frequency stealth(RFS) during the course of tracking by controlling the radiation energy and the interval of a radar. Firstly, we build the model of probability of interception with the once radiation during the course of tracking. Secondly, we establish the model of the cumulative probability of interception to describe the effect of RFS throughout the tracking process and obtain two solutions that are minimizing the probability of interception and the radiation times to reduce the cumulative probability of interception. Thirdly, we propose a self-adapting radiation energy control method(SARE)to minimize the probability of interception. Fourthly, we propose a self-adapting radiation interval control method(SARI) to minimize radiation times. Fifthly, combining SARE with SARI, we propose a SARE-SARI control method(SAEI) during the course of tracking.Finally, we compare SAEI with two others by simulation, and the results show the effect of RFS of SAEI is better than the other two,but we have to make a trade-off between the ability of RFS and the effect of tracking.
基金Projects(61203020,61403190)supported by the National Natural Science Foundation of ChinaProject(BK20141461)supported by the Jiangsu Province Natural Science Foundation,China
文摘In order to solve the non-linear and high-dimensional optimization problems more effectively, an improved self-adaptive membrane computing(ISMC) optimization algorithm was proposed. The proposed ISMC algorithm applied improved self-adaptive crossover and mutation formulae that can provide appropriate crossover operator and mutation operator based on different functions of the objects and the number of iterations. The performance of ISMC was tested by the benchmark functions. The simulation results for residue hydrogenating kinetics model parameter estimation show that the proposed method is superior to the traditional intelligent algorithms in terms of convergence accuracy and stability in solving the complex parameter optimization problems.
基金supported by the National Natural Science Foundation of China(61571043)the 111 Project of China(B14010)。
文摘As a core part of the electronic warfare(EW) system,de-interleaving is used to separate interleaved radar signals. As interleaved radar pulses become more complex and denser, intelligent classification of radar signals has become very important. The self-organizing feature map(SOFM) is an excellent artificial neural network, which has huge advantages in intelligent classification of complex data. However, the de-interleaving process based on SOFM is faced with the problems that the initialization of the map size relies on prior information and the network topology cannot be adaptively adjusted. In this paper, an SOFM with self-adaptive network topology(SANT-SOFM) algorithm is proposed to solve the above problems. The SANT-SOFM algorithm first proposes an adaptive proliferation algorithm to adjust the map size, so that the initialization of the map size is no longer dependent on prior information but is gradually adjusted with the input data. Then,structural optimization algorithms are proposed to gradually optimize the topology of the SOFM network in the iterative process,constructing an optimal SANT. Finally, the optimized SOFM network is used for de-interleaving radar signals. Simulation results show that SANT-SOFM could get excellent performance in complex EW environments and the probability of getting the optimal map size is over 95% in the absence of priori information.
基金supported by the Aviation Science Funds of China(2010ZC13012)the Fund of Jiangsu Innovation Program for Graduate Education (CXLX11 0203)
文摘There are many population-based stochastic search algorithms for solving optimization problems. However, the universality and robustness of these algorithms are still unsatisfactory. This paper proposes an enhanced self-adaptiveevolutionary algorithm （ESEA） to overcome the demerits above. In the ESEA, four evolutionary operators are designed to enhance the evolutionary structure. Besides, the ESEA employs four effective search strategies under the framework of the self-adaptive learning. Four groups of the experiments are done to find out the most suitable parameter values for the ESEA. In order to verify the performance of the proposed algorithm, 26 state-of-the-art test functions are solved by the ESEA and its competitors. The experimental results demonstrate that the universality and robustness of the ESEA out-perform its competitors.
基金Project(61273187)supported by the National Natural Science Foundation of ChinaProject(61321003)supported by the Foundation for Innovative Research Groups of the National Natural Science Foundation of China
文摘Region partition(RP) is the key technique to the finite element parallel computing(FEPC),and its performance has a decisive influence on the entire process of analysis and computation.The performance evaluation index of RP method for the three-dimensional finite element model(FEM) has been given.By taking the electric field of aluminum reduction cell(ARC) as the research object,the performance of two classical RP methods,which are Al-NASRA and NGUYEN partition(ANP) algorithm and the multi-level partition(MLP) method,has been analyzed and compared.The comparison results indicate a sound performance of ANP algorithm,but to large-scale models,the computing time of ANP algorithm increases notably.This is because the ANP algorithm determines only one node based on the minimum weight and just adds the elements connected to the node into the sub-region during each iteration.To obtain the satisfied speed and the precision,an improved dynamic self-adaptive ANP(DSA-ANP) algorithm has been proposed.With consideration of model scale,complexity and sub-RP stage,the improved algorithm adaptively determines the number of nodes and selects those nodes with small enough weight,and then dynamically adds these connected elements.The proposed algorithm has been applied to the finite element analysis(FEA) of the electric field simulation of ARC.Compared with the traditional ANP algorithm,the computational efficiency of the proposed algorithm has been shortened approximately from 260 s to 13 s.This proves the superiority of the improved algorithm on computing time performance.
基金supported by the National Natural Science Foundation of China(61433003,60904003,11602019).
文摘A fast self-adapting high-order sliding mode(FSHOSM)controller is designed for a class of nonlinear systems with unknown uncertainties.As for uncertainty-free nonlinear system,a new switching condition is introduced into the standard geometric homogeneity.Different from the existing geometric homogeneity method,both state variables and their derivatives are considered to bring a reasonable effective switching condition.As a result,a faster convergence rate of state variables is achieved.Furthermore,based on the integral sliding mode(ISM)and above geometric homogeneity,a self-adapting high-order sliding mode(HOSM)control law is proposed for a class of nonlinear systems with uncertainties.The resulting controller allows the closed-loop system to conduct with the expected properties of strong robustness and fast convergence.Stable analysis of the nonlinear system is also proved based on the Lyapunov approach.The effectiveness of the resulting controller is verified by several simulation results.
基金supported by the National Natural Science Foundation of China(12072090).
文摘This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hypersonic vehicles.In order to increase the control amount,this online control legislation makes use of model predictive control(MPC)that is based on the concept of iterative learning control(ILC).By using offline data to decrease the linearized model’s faults,the strategy may effectively increase the robustness of the control system and guarantee that disturbances can be suppressed.An adaptive fault observer is created based on the suggested ILMPC approach in order to enhance overall fault tolerance by estimating and compensating for actuator disturbance and fault degree.During the derivation process,a linearized model of longitudinal dynamics is established.The suggested ILMPC approach is likely to be used in the design of hypersonic vehicle control systems since numerical simulations have demonstrated that it can decrease tracking error and speed up convergence when compared to the offline controller.
文摘This paper presents an investigation on the target-guided coordinated control(TACC)of unmanned surface vehicles(USVs).In the scenario of tracking non-cooperative targets,the status information of the target can only be obtained by some USVs.In order to achieve semi-encirclement tracking of noncooperative targets under maritime security conditions,a fixed-time tracking control method based on dynamic surface control(DSC)is proposed in this paper.Firstly,a novel TACC architecture with decoupled kinematic control law and decoupled kinetic control law was designed to reduce the complexity of control system design.Secondly,the proposed DSC-based target-guided kinematic control law including tracking points pre-allocation strategy and sigmoid artificial potential functions(SigAPFs)can avoid collisions during tracking process and optimize kinematic control output.Finally,a fixed-time TACC system was proposed to achieve fast convergence of kinematic and kinetics errors.The effectiveness of the proposed TACC approach in improving target tracking safety and reducing control output chattering was verified by simulation comparison results.
文摘The present technical paper outlines the details of the controlled blasting techniques used to optimize blasting pattern for excavation of hard rock near the Bhira Earthen Dam in Maharashtra,India.In this connection,a series of experimental blasts were conducted by adjusting various blast design parameters at project site.The safe charge weight per delay was kept between 0.125 and 0.375 kg.The outcomes of these experimental blasts were analyzed to recommend optimized blasting patterns and methods for the overall excavation process during actual blasting operations.Blast design parameters,including the maximum quantity of explosive per delay,hole depth,burden and spacing between holes were optimized by using a site-specific attenuation equation,taking into account the proximity of the dam and tunnel from the blasting area.Peak particle velocity(PPV)level of 10 mm/s and 50 mm/s respectively were adopted as the safe vibration level for ensuring safety of the Bhira Earthen Dam and the nearby tunnel from the adverse effects of blast vibrations by analyzing the dominant frequency of ground vibrations observed and also by reviewing various international standards.Frequency of the ground vibrations observed on the dam and tunnel from majority of the blasts was found to be more than 10 Hz and 50 Hz respectively.During the entire period of blasting,the blast vibrations were recorded to be far lower than the safe vibration level set for these structures.Maximum Vibration level of about 0.8 mm/s and 35 mm/s were observed on dam and tunnel respectively which are far lower than the safe vibration level adopted for these structures.Hence,the entire excavation work was completed successfully and safely,without endangering the safety of dam or tunnel.
基金Supported by the Major Science and Technology Project of Jilin Province(20220301010GX)the International Scientific and Technological Cooperation(20240402071GH).
文摘The liquid cooling system(LCS)of fuel cells is challenged by significant time delays,model uncertainties,pump and fan coupling,and frequent disturbances,leading to overshoot and control oscillations that degrade temperature regulation performance.To address these challenges,we propose a composite control scheme combining fuzzy logic and a variable-gain generalized supertwisting algorithm(VG-GSTA).Firstly,a one-dimensional(1D)fuzzy logic controler(FLC)for the pump ensures stable coolant flow,while a two-dimensional(2D)FLC for the fan regulates the stack temperature near the reference value.The VG-GSTA is then introduced to eliminate steady-state errors,offering resistance to disturbances and minimizing control oscillations.The equilibrium optimizer is used to fine-tune VG-GSTA parameters.Co-simulation verifies the effectiveness of our method,demonstrating its advantages in terms of disturbance immunity,overshoot suppression,tracking accuracy and response speed.
基金Supported by the National Key R&D Program of China(2021YFB2011300)the National Natural Science Foundation of China(52275044,52205299)+1 种基金the Zhejiang Provincial Natural Science Foundation of China(Z23E050032)the China Postdoctoral Science Foundation(2022M710304).
文摘The operating environment of the diesel engine air path system is complex and may be affected by external random disturbances.Potentially leading to faults.This paper addresses the fault-tolerant control problem of the diesel engine air path system,assuming that the system may simultaneously be affected by actuator faults and external random disturbances,a disturbance observer-based sliding mode controller is designed.Through the linear matrix inequality technique for solving observer and controller gains,optimal gain matrices can be obtained,eliminating the manual adjustment process of controller parameters and reducing the chattering phenomenon of the sliding mode surface.Finally,the effectiveness of the proposed method is verified through simulation analysis.
基金supported by the Guangdong Major Project of Basic and Applied Basic Research(Grant No.2021B0301030001)the National Key Research and Development Program of China(Grant No.2021YFB3802300)the Foundation of National Key Laboratory of Shock Wave and Detonation Physics(Grant No.JCKYS2022212004)。
文摘The graded density impactor(GDI)dynamic loading technique is crucial for acquiring the dynamic physical property parameters of materials used in weapons.The accuracy and timeliness of GDI structural design are key to achieving controllable stress-strain rate loading.In this study,we have,for the first time,combined one-dimensional fluid computational software with machine learning methods.We first elucidated the mechanisms by which GDI structures control stress and strain rates.Subsequently,we constructed a machine learning model to create a structure-property response surface.The results show that altering the loading velocity and interlayer thickness has a pronounced regulatory effect on stress and strain rates.In contrast,the impedance distribution index and target thickness have less significant effects on stress regulation,although there is a matching relationship between target thickness and interlayer thickness.Compared with traditional design methods,the machine learning approach offers a10^(4)—10^(5)times increase in efficiency and the potential to achieve a global optimum,holding promise for guiding the design of GDI.
基金Supported by the National Natural Science Foundation of China (11161027)。
文摘Projective synchronization problems of a drive system and a particular response network were investigated,where the drive system is an arbitrary system with n+1 dimensions;it may be a linear or nonlinear system,and even a chaotic or hyperchaotic system,the response network is complex system coupled by N nodes,and every node is showed by the approximately linear part of the drive system.Only controlling any one node of the response network by designed controller can achieve the projective synchronization.Some numerical examples were employed to verify the effectiveness and correctness of the designed controller.
文摘OBJECTIVE To investigate the intervention effects of tissue-bone homeostasis manipulation(TBHM)on peripatellar biomechanical parameters and knee joint function in knee osteoarthritis(KOA)patients.METHODS Sixty patients with KOA(Kellgren-Lawrence gradeⅡ-Ⅲ)were recruited from the Acupuncture-Moxibustion Rehabilitation Department,Anhui University of Chinese Medicine between October 2024 and May 2025.Participants were randomized into a TBHM group(n=30)or a transcutaneous electrical neuromuscular stimulation(TENS)group(n=30).Using two-way repeated measures ANOVA,biomechanical indicators,including rectus femoris tension,vastus medialis tension,vastus lateralis tension,patellar ligament tension,lateral patellar displacement(LPD),medial patellar displacement(MPD),normalized patellar mobility(LPD/patellar width[PW],MPD/PW),knee flexion range of motion,and functional indicators,including KOOS subscales,time up and go test(TUGT),were compared between groups at baseline and after 6 weeks of intervention.RESULTS After intervention,all biomechanical and knee joint function indicators in the TBHM group were significantly improved(P<0.05,P<0.01),while only the vastus medialis tension,TUGT and KOOS Pain,ADL and QoL scores in the control group were significantly improved(P<0.01).The improvement amplitudes of biomechanical indicators in the TBHM group,including rectus femoris tension,vastus lateralis tension,patellar ligament tension,MPD/PW,LPD/PW and knee flexion range of motion were better than those in the control group(P<0.05,P<0.01).In the functional evaluation,the interaction effects of the TBHM group in all dimensions of the KOOS score and TUGT were statistically significant(P<0.05,P<0.01).Post-hoc simple effect analysis confirmed that there were significant differences in the above indicators between the two groups after intervention(P<0.05),and all indicators showed a significant main effect of time(P<0.01),suggesting that the intervention measures had continuous and cumulative curative effects.CONCLUSION TBHM effectively improves joint function and quality of life in KOA patients by restoring dynamic equilibrium in soft tissue tension and patellar mobility,ultimately achieving the therapeutic goal of concurrent tissue-bone management.
文摘In view of the deficiencies in aspects such as failure rate requirements and analysis assumptions of advisory circular,this paper investigates the sources of high safety requirements,and the top-down design method for the flight control system life cycle.Correspondingly,measures are proposed,including enhancing the safety target value to 10^(−10)per flight hour and implementing development assurance.In view of the shortcomings of mainstream aircraft flight control systems,such as weak backup capability and complex fault reconfiguration logic,improvements have been made to the system’s operating modes,control channel allocation,and common mode failure mitigation schemes based on the existing flight control architecture.The flight control design trends and philosophies have been analyzed.A flight control system architecture scheme is proposed,which includes three operating modes and multi-level voters/monitors,three main control channels,and a backup system independent of the main control system,which has been confirmed through functional modeling simulations.The proposed method plays an important role in the architecture design of safety-critical flight control system.
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.
