Dominant technology formation is the key for the hightech industry to“cross the chasm”and gain an established foothold in the market(and hence disrupt the regime).Therefore,a stimulus-response model is proposed to i...Dominant technology formation is the key for the hightech industry to“cross the chasm”and gain an established foothold in the market(and hence disrupt the regime).Therefore,a stimulus-response model is proposed to investigate the dominant technology by exploring its formation process and mechanism.Specifically,based on complex adaptive system theory and the basic stimulus-response model,we use a combination of agent-based modeling and system dynamics modeling to capture the interactions between dominant technology and the socio-technical landscape.The results indicate the following:(i)The dynamic interaction is“stimulus-reaction-selection”,which promotes the dominant technology’s formation.(ii)The dominant technology’s formation can be described as a dynamic process in which the adaptation intensity of technology standards increases continuously until it becomes the leading technology under the dual action of internal and external mechanisms.(iii)The dominant technology’s formation in the high-tech industry is influenced by learning ability,the number of adopting users and adaptability.Therein,a“critical scale”of learning ability exists to promote the formation of leading technology:a large number of adopting users can promote the dominant technology’s formation by influencing the adaptive response of technology standards to the socio-technical landscape and the choice of technology standards by the socio-technical landscape.There is a minimum threshold and a maximum threshold for the role of adaptability in the dominant technology’s formation.(iv)The socio-technical landscape can promote the leading technology’s shaping in the high-tech industry,and different elements have different effects.This study promotes research on the formation mechanism of dominant technology in the high-tech industry,presents new perspectives and methods for researchers,and provides essential enlightenment for managers to formulate technology strategies.展开更多
Language is a special social phenomenon and is always on the changing process with the development of society. During the evolving process of language, new language varieties will continuously emerge due to the change...Language is a special social phenomenon and is always on the changing process with the development of society. During the evolving process of language, new language varieties will continuously emerge due to the changes of some social and cultural factors. Cyber language is universally accepted as one type of the social language varieties. Basically, cyber language can be treated as a complex adaptive system which is influenced by the interaction between users’ cognition, social culture and the surrounding environments. Thus it is safe to say that cyber language is always undergoing a dynamic evolving process. With the usage-based language model as the theoretical foundation, this paper proposes a Complex Adaptive System (CAS) approach to analyze the expression of Appreciation to explore the complex, dynamic and nonlinear development of cyber language from the angle of meaning construction, grammaticalization and functional adaption respectively. It is found that the expression of Appreciation is experiencing adaptively a semantic connotations development and a process of grammatical functions expansion as well. This paper suggests that the emergence and development of cyber language is a novel and trendy social language phenomenon. Network language can achieve its process and evolution under the huge impact of social changes and social promotions. When faced with the changing surroundings, cyber language itself enjoys a timely adaption and responsive development to keep up with the new environments, which reflects the basic principle of language development, namely, language changes with the development of society.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
A design scheme of adaptive fuzzy controller for a class of uncertain MIMO nonlinear systems with unknown dead-zones and a triangular control structure is proposed in this pa-per.The design is based on the principle o...A design scheme of adaptive fuzzy controller for a class of uncertain MIMO nonlinear systems with unknown dead-zones and a triangular control structure is proposed in this pa-per.The design is based on the principle of sliding mode control and the property of Nussbaum function.The approach does not require a priori knowledge of the signs of the control gains and the upper bounds and lower bounds of dead-zone parameters to be known a priori.By introducing the integral-type Lyapunov function and adopting the adaptive compensation term of the upper bound of the optimal approximation error and the dead-zone disturbance,the closed-loop control system is proved to be semi-globally stable in the sense that all signals involved are bounded,with tracking errors converging to zero.展开更多
A marine INS/GPS adaptive navigation system is presented. GPS with two antenna providing vessel＇ s altitude is selected as the auxiliary system fusing with INS to improve the performance of the hybrid system. The Kal...A marine INS/GPS adaptive navigation system is presented. GPS with two antenna providing vessel＇ s altitude is selected as the auxiliary system fusing with INS to improve the performance of the hybrid system. The Kalman filter is the most frequently used algorithm in the integrated navigation system, which is capable of estimating INS errors online based on the measured errors between INS and GPS. The standard Kalman filter （SKF） assumes that the statistics of the noise on each sensor are given. As long as the noise distributions do not change, the Kalman filter will give the optimal estimation. However GPS receiver will be disturbed easily and thus temporally changing measurement noise will join into the outputs of GPS, which will lead to performance degradation of the Kalman filter. Many researchers introduce fuzzy logic control method into innovation-based adaptive estimation adaptive Kalman filtering （IAE-AKF） algorithm, and accordingly propose various adaptive Kalman filters. However how to design the fuzzy logic controller is a very complicated problem still without a convincing solution. A novel IAE-AKF is proposed herein, which is based on the maximum likelihood criterion for the proper computation of the filter innovation covariance and hence of the filter gain. The approach is direct and simple without having to establish fuzzy inference rules. After having deduced the proposed IAEAKF algorithm theoretically in detail, the approach is tested by the simulation based on the system error model of the developed INS/GPS integrated marine navigation system. Simulation results show that the adaptive Kalman filter outperforms the SKF with higher accuracy, robustness and less computation. It is demonstra- ted that this proposed approach is a valid solution for the unknown changing measurement noise exited in the Kalman filter.展开更多
A control algorithm for improving vehicle handling was proposed by applying right angle to the steering wheel,based on the nonlinear adaptive optimal control(NAOC).A nonlinear 4-DOF model was initially developed,then ...A control algorithm for improving vehicle handling was proposed by applying right angle to the steering wheel,based on the nonlinear adaptive optimal control(NAOC).A nonlinear 4-DOF model was initially developed,then it was simplified to a 2-DOF model with reasonable assumptions to design observer and optimal controllers.Then a simplified model was developed for steering system.The numerical simulations were carried out using vehicle parameters for standard maneuvers in dry and wet road conditions.Moreover,the hardware in the loop method was implemented to prove the controller ability in realistic conditions.Simulation results obviously show the effectiveness of NAOC on vehicle handling and reveal that the proposed controller can significantly improve vehicle handling during severe maneuvers.展开更多
Inherent flaws in the extended Kalman filter(EKF) algorithm were pointed out and unscented Kalman filter(UKF) was put forward as an alternative.Furthermore,a novel adaptive unscented Kalman filter(AUKF) based on innov...Inherent flaws in the extended Kalman filter(EKF) algorithm were pointed out and unscented Kalman filter(UKF) was put forward as an alternative.Furthermore,a novel adaptive unscented Kalman filter(AUKF) based on innovation was developed.The three data-fusing approaches were analyzed and evaluated in a mathematically rigorous way.Field experiments conducted in lake further demonstrate that AUKF reduces the position error approximately by 65% compared with EKF and by 35% UKF and improves the robust performance.展开更多
Based on consideration of the differential relations between the immeasurable variables and measurable variables in electro-hydraulic servo system,adaptive dynamic recurrent fuzzy neural networks(ADRFNNs) were employe...Based on consideration of the differential relations between the immeasurable variables and measurable variables in electro-hydraulic servo system,adaptive dynamic recurrent fuzzy neural networks(ADRFNNs) were employed to identify the primary uncertainty and the mathematic model of the system was turned into an equivalent linear model with terms of secondary uncertainty.At the same time,gain adaptive sliding mode variable structure control(GASMVSC) was employed to synthesize the control effort.The results show that the unrealization problem caused by some system's immeasurable state variables in traditional fuzzy neural networks(TFNN) taking all state variables as its inputs is overcome.On the other hand,the identification by the ADRFNNs online with high accuracy and the adaptive function of the correction term's gain in the GASMVSC make the system possess strong robustness and improved steady accuracy,and the chattering phenomenon of the control effort is also suppressed effectively.展开更多
An adaptive robust approach for actuator fault-tolerant control of a class of uncertain nonlinear systems is proposed.The two chief ways in which the system performance can degrade following an actuator-fault are unde...An adaptive robust approach for actuator fault-tolerant control of a class of uncertain nonlinear systems is proposed.The two chief ways in which the system performance can degrade following an actuator-fault are undesirable transients and unacceptably large steady-state tracking errors.Adaptive control based schemes can achieve good final tracking accuracy in spite of change in system parameters following an actuator fault,and robust control based designs can achieve guaranteed transient response.However,neither adaptive control nor robust control based fault-tolerant designs can address both the issues associated with actuator faults.In the present work,an adaptive robust fault-tolerant control scheme is claimed to solve both the problems,as it seamlessly integrates adaptive and robust control design techniques.Comparative simulation studies are performed using a nonlinear hypersonic aircraft model to show the effectiveness of the proposed scheme over a robust adaptive control based faulttolerant scheme.展开更多
For electro-discharge machining, only in the optimum state could the highest material removal rate be realized. In practical machining process, the timely elevation of the tool electrode is needed to eliminate chippin...For electro-discharge machining, only in the optimum state could the highest material removal rate be realized. In practical machining process, the timely elevation of the tool electrode is needed to eliminate chipping, which ordinarily occupies quite a lot of time. Therefore, besides the control of the machining parameters, the control of the optimum discharge gap and the conversion of different machining states is also needed. In this paper, the adaptive fuzzy control system of servomechanism for EDM combined with ultrasonic vibration is studied, the servomechanism of which is composed of the stepping motor comprising variable steps and the inductive synchronizer. The fuzzy control technology is used to realize the control of the frequency and the step of the servomechanism. The adaptive fuzzy controller has three inputs and two outputs, which can well meet the actual control requirements. The constitution of the fuzzy control regulation for the step frequency is the key to the design of the whole fuzzy control system of the servomechanism. The step frequency is mainly determined by the position error and the change rate of the position error. When the value of the position error is high or medium, the controlled parameters are selected to eliminate the error; when the position error is lower, the controlled parameters are selected to avoid the over-orientation and thus keep the stability of the system. According to these, a fuzzy control table is established in advanced, which is used to express the relations between the fuzzy input parameters and the fuzzy output parameters. The input parameters and the output parameters are all expressed by the level-values in fuzzy field. Therefore, the output parameters used for control can be obtained for the fuzzy control table according to the detected actual input parameters, by which the EDM combined with ultrasonic vibration is improved and the machining efficiency is increased. In addition, a stimulation program is designed by means of Microsoft Visual Basic展开更多
For a class of unknown nonlinear time-delay systems, an adaptive neural network （NN） control design approach is proposed. Backstepping, domination and adaptive bounding design technique are combined to construct a r...For a class of unknown nonlinear time-delay systems, an adaptive neural network （NN） control design approach is proposed. Backstepping, domination and adaptive bounding design technique are combined to construct a robust memoryless adaptive NN tracking controller. Unknown time-delay functions are approximated by NNs, such that the requirement on the nonlinear time-delay functions is relaxed. Based on Lyapunov-Krasoviskii functional, the sem-global uniformly ultimately boundedness （UUB） of all the signals in the closed-loop system is proved. The arbitrary output tracking accuracy is achieved by tuning the design parameters. The feasibility is investigated by an illustrative simulation example.展开更多
A new adaptive Type-2 （T2） fuzzy controller was developed and its potential performance advantage over adaptive Type-1 （T1） fuzzy control was also quantified in computer simulation. Base on the Lyapunov method, th...A new adaptive Type-2 （T2） fuzzy controller was developed and its potential performance advantage over adaptive Type-1 （T1） fuzzy control was also quantified in computer simulation. Base on the Lyapunov method, the adaptive laws with guaranteed system stability and convergence were developed. The controller updates its parameters online using the laws to control a system and tracks its output command trajectory. The simulation study involving the popular inverted pendulum control problem shows theoretically predicted system stability and good tracking performance. And the comparison simulation experiments subjected to white noige or step disturbance indicate that the T2 controller is better than the T1 controller by 0--18%, depending on the experiment condition and performance measure.展开更多
This paper puts forward an unprecedented avoidance-striking-arrival problem aiming to address the need for tank's uncertain mechanical systems on the intelligent battlefield.The associated system uncertainties(pos...This paper puts forward an unprecedented avoidance-striking-arrival problem aiming to address the need for tank's uncertain mechanical systems on the intelligent battlefield.The associated system uncertainties(possibly rapid)are time-varying but bounded(possibly unknown).The goal is to design a controller that enables the tank to aim at and attack the enemy tank while keeping itself(out of the enemy fire zone).The tank maintains this condition until reaching the predefined region.In this paper,an approximate constraint following control method is adopted to solve this problem,and the original constraints are creatively divided into two categories:the avoidance-tracking constraint and the striking-arrival constraint.An adaptive robust control method is proposed and consequently verified through simulation experiments.It is proved that the system fully obeys the avoidance-tracking-constraint and strictly obeys the striking-arrival constraint under the control input.Besides,the control of the tank vehicle running system and tank gun bidirectional stabilization system are unified to deal with the control signal delay caused by complex uncertainties on the battlefield.Overall,this paper reduced the delay of signal transmission in the system while solved the avoidance-striking-arrival problem.展开更多
The purpose of this paper is the design of neural network-based adaptive sliding mode controller for uncertain unknown nonlinear systems. A special architecture adaptive neural network, with hyperbolic tangent activat...The purpose of this paper is the design of neural network-based adaptive sliding mode controller for uncertain unknown nonlinear systems. A special architecture adaptive neural network, with hyperbolic tangent activation functions, is used to emulate the equivalent and switching control terms of the classic sliding mode control （SMC）. Lyapunov stability theory is used to guarantee a uniform ultimate boundedness property for the tracking error, as well as of all other signals in the closed loop. In addition to keeping the stability and robustness properties of the SMC, the neural network-based adaptive sliding mode controller exhibits perfect rejection of faults arising during the system operating. Simulation studies are used to illustrate and clarify the theoretical results.展开更多
The electro-hydraulic servo system was studied to cancel the amplitude attenuation and phase delay of its sinusoidal response,by developing a network using normalized least-mean-square (LMS) adaptive filtering algorit...The electro-hydraulic servo system was studied to cancel the amplitude attenuation and phase delay of its sinusoidal response,by developing a network using normalized least-mean-square (LMS) adaptive filtering algorithm.The command input was corrected by weights to generate the desired input for the algorithm,and the feedback was brought into the feedback correction,whose output was the weighted feedback.The weights of the normalized LMS adaptive filtering algorithm were updated on-line according to the estimation error between the desired input and the weighted feedback.Thus,the updated weights were copied to the input correction.The estimation error was forced to zero by the normalized LMS adaptive filtering algorithm such that the weighted feedback was equal to the desired input,making the feedback track the command.The above concept was used as a basis for the development of amplitude phase control.The method has good real-time performance without estimating the system model.The simulation and experiment results show that the proposed amplitude phase control can efficiently cancel the amplitude attenuation and phase delay with high precision.展开更多
An adaptive control scheme is developed for a class of single-input nonlinear systems preceded by unknown hysteresis, which is a non-differentiable and multi-value mapping nonlinearity. The controller based on the thr...An adaptive control scheme is developed for a class of single-input nonlinear systems preceded by unknown hysteresis, which is a non-differentiable and multi-value mapping nonlinearity. The controller based on the three-layer neural network （NN）, whose weights are derived from Lyapunov stability analysis, guarantees closed-loop semiglobal stability and convergence of the tracking errors to a small residual set. An example is used to confirm the effectiveness of the proposed control scheme.展开更多
A robust adaptive trajectory linearization control （RATLC） algorithm for a class of nonlinear systems with uncertainty and disturbance based on the T-S fuzzy system is presented. The unknown disturbance and uncertai...A robust adaptive trajectory linearization control （RATLC） algorithm for a class of nonlinear systems with uncertainty and disturbance based on the T-S fuzzy system is presented. The unknown disturbance and uncertainty are estimated by the T-S fuzzy system, and a robust adaptive control law is designed by the Lyapunov theory. Irrespective of whether the dimensions of the system and the rules of the fuzzy system are large or small, there is only one parameter adjusting on line. Uniformly ultimately boundedness of all signals of the composite closed-loop system are proved by theory analysis. Finally, a numerical example is studied based on the proposed method. The simulation results demonstrate the effectiveness and robustness of the control scheme.展开更多
In order to achieve the improvement of the driving comfort and energy efficiency,an new e-CVT flexible full hybrid electric system(E2FHS) is proposed,which uses an integrated main drive motor and generator to take the...In order to achieve the improvement of the driving comfort and energy efficiency,an new e-CVT flexible full hybrid electric system(E2FHS) is proposed,which uses an integrated main drive motor and generator to take the place of the original automatic or manual transmission to realize the functions of continuously variable transmission(e-CVT).The design and prototype realization of the E2FHS system for a plug-in hybrid vehicle(PHEV) is performed.In order to analyze and optimize the parameters and the power flux between different parts of the E2FHS,simulation software is developed.Especially,in order to optimize the performance of the energy economy improvement of the E2FHS,the effect of the different energy management controllers is investigated,and an adaptive online-optimal energy management controller for the E2FHS is built and validated by the prototype PHEV.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
A novel H∞ tracking-based decentralized indirect adaptive output feedback fuzzy controller for a class of uncertain large-scale nonlinear systems is developed. By virtue of the proper filtering of the observation err...A novel H∞ tracking-based decentralized indirect adaptive output feedback fuzzy controller for a class of uncertain large-scale nonlinear systems is developed. By virtue of the proper filtering of the observation error dynamics, the observer-based decentralized indirect adaptive fuzzy control scheme is presented for a class of large-scale nonlinear systems using the combination of H∞ tracking technique, a fuzzy adaptive observer and fuzzy inference systems. The output feedback and adaptation mechanisms are both robust and implementable indeed owing to their freedom from the unavailable observation error vector. All the signals of the closed-loop largescale system are guaranteed to stay uniformly bounded and the output errors take on H∞ tracking performance. Simulation results substantiate the effectiveness of the proposed scheme.展开更多
基金supported by the Shanghai Philosophy and Social Science Foundation(2022ECK004)Shanghai Soft Science Research Project(23692123400)。
文摘Dominant technology formation is the key for the hightech industry to“cross the chasm”and gain an established foothold in the market(and hence disrupt the regime).Therefore,a stimulus-response model is proposed to investigate the dominant technology by exploring its formation process and mechanism.Specifically,based on complex adaptive system theory and the basic stimulus-response model,we use a combination of agent-based modeling and system dynamics modeling to capture the interactions between dominant technology and the socio-technical landscape.The results indicate the following:(i)The dynamic interaction is“stimulus-reaction-selection”,which promotes the dominant technology’s formation.(ii)The dominant technology’s formation can be described as a dynamic process in which the adaptation intensity of technology standards increases continuously until it becomes the leading technology under the dual action of internal and external mechanisms.(iii)The dominant technology’s formation in the high-tech industry is influenced by learning ability,the number of adopting users and adaptability.Therein,a“critical scale”of learning ability exists to promote the formation of leading technology:a large number of adopting users can promote the dominant technology’s formation by influencing the adaptive response of technology standards to the socio-technical landscape and the choice of technology standards by the socio-technical landscape.There is a minimum threshold and a maximum threshold for the role of adaptability in the dominant technology’s formation.(iv)The socio-technical landscape can promote the leading technology’s shaping in the high-tech industry,and different elements have different effects.This study promotes research on the formation mechanism of dominant technology in the high-tech industry,presents new perspectives and methods for researchers,and provides essential enlightenment for managers to formulate technology strategies.
文摘Language is a special social phenomenon and is always on the changing process with the development of society. During the evolving process of language, new language varieties will continuously emerge due to the changes of some social and cultural factors. Cyber language is universally accepted as one type of the social language varieties. Basically, cyber language can be treated as a complex adaptive system which is influenced by the interaction between users’ cognition, social culture and the surrounding environments. Thus it is safe to say that cyber language is always undergoing a dynamic evolving process. With the usage-based language model as the theoretical foundation, this paper proposes a Complex Adaptive System (CAS) approach to analyze the expression of Appreciation to explore the complex, dynamic and nonlinear development of cyber language from the angle of meaning construction, grammaticalization and functional adaption respectively. It is found that the expression of Appreciation is experiencing adaptively a semantic connotations development and a process of grammatical functions expansion as well. This paper suggests that the emergence and development of cyber language is a novel and trendy social language phenomenon. Network language can achieve its process and evolution under the huge impact of social changes and social promotions. When faced with the changing surroundings, cyber language itself enjoys a timely adaption and responsive development to keep up with the new environments, which reflects the basic principle of language development, namely, language changes with the development of society.
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 National Natural Science Foundation of P.R.China(60074013),the Foundation of the Education Bureau of JiangsuProvince(KK0310067&05KJB520152),and the Foundation of Infor-mation Science Subject Group of Yangzhou University(ISG 030606).
文摘A design scheme of adaptive fuzzy controller for a class of uncertain MIMO nonlinear systems with unknown dead-zones and a triangular control structure is proposed in this pa-per.The design is based on the principle of sliding mode control and the property of Nussbaum function.The approach does not require a priori knowledge of the signs of the control gains and the upper bounds and lower bounds of dead-zone parameters to be known a priori.By introducing the integral-type Lyapunov function and adopting the adaptive compensation term of the upper bound of the optimal approximation error and the dead-zone disturbance,the closed-loop control system is proved to be semi-globally stable in the sense that all signals involved are bounded,with tracking errors converging to zero.
基金This project was supported by the National Natural Science Foundation of China (40125013 &40376011)
文摘A marine INS/GPS adaptive navigation system is presented. GPS with two antenna providing vessel＇ s altitude is selected as the auxiliary system fusing with INS to improve the performance of the hybrid system. The Kalman filter is the most frequently used algorithm in the integrated navigation system, which is capable of estimating INS errors online based on the measured errors between INS and GPS. The standard Kalman filter （SKF） assumes that the statistics of the noise on each sensor are given. As long as the noise distributions do not change, the Kalman filter will give the optimal estimation. However GPS receiver will be disturbed easily and thus temporally changing measurement noise will join into the outputs of GPS, which will lead to performance degradation of the Kalman filter. Many researchers introduce fuzzy logic control method into innovation-based adaptive estimation adaptive Kalman filtering （IAE-AKF） algorithm, and accordingly propose various adaptive Kalman filters. However how to design the fuzzy logic controller is a very complicated problem still without a convincing solution. A novel IAE-AKF is proposed herein, which is based on the maximum likelihood criterion for the proper computation of the filter innovation covariance and hence of the filter gain. The approach is direct and simple without having to establish fuzzy inference rules. After having deduced the proposed IAEAKF algorithm theoretically in detail, the approach is tested by the simulation based on the system error model of the developed INS/GPS integrated marine navigation system. Simulation results show that the adaptive Kalman filter outperforms the SKF with higher accuracy, robustness and less computation. It is demonstra- ted that this proposed approach is a valid solution for the unknown changing measurement noise exited in the Kalman filter.
文摘A control algorithm for improving vehicle handling was proposed by applying right angle to the steering wheel,based on the nonlinear adaptive optimal control(NAOC).A nonlinear 4-DOF model was initially developed,then it was simplified to a 2-DOF model with reasonable assumptions to design observer and optimal controllers.Then a simplified model was developed for steering system.The numerical simulations were carried out using vehicle parameters for standard maneuvers in dry and wet road conditions.Moreover,the hardware in the loop method was implemented to prove the controller ability in realistic conditions.Simulation results obviously show the effectiveness of NAOC on vehicle handling and reveal that the proposed controller can significantly improve vehicle handling during severe maneuvers.
基金Projects(2009AA093302,2002AA401003)supported by the National High-Tech Research and Development Program of ChinaProject(YYYJ-0917)supported by the Knowledge Innovation of Chinese Academy of Sciences+1 种基金Projects(61273334,61233013)supported by the National Natural Science Foundation of ChinaProject(2011010025-401)supported by the Natural Science Foundation of Liaoning Province,China
文摘Inherent flaws in the extended Kalman filter(EKF) algorithm were pointed out and unscented Kalman filter(UKF) was put forward as an alternative.Furthermore,a novel adaptive unscented Kalman filter(AUKF) based on innovation was developed.The three data-fusing approaches were analyzed and evaluated in a mathematically rigorous way.Field experiments conducted in lake further demonstrate that AUKF reduces the position error approximately by 65% compared with EKF and by 35% UKF and improves the robust performance.
基金Project(60634020) supported by the National Natural Science Foundation of China
文摘Based on consideration of the differential relations between the immeasurable variables and measurable variables in electro-hydraulic servo system,adaptive dynamic recurrent fuzzy neural networks(ADRFNNs) were employed to identify the primary uncertainty and the mathematic model of the system was turned into an equivalent linear model with terms of secondary uncertainty.At the same time,gain adaptive sliding mode variable structure control(GASMVSC) was employed to synthesize the control effort.The results show that the unrealization problem caused by some system's immeasurable state variables in traditional fuzzy neural networks(TFNN) taking all state variables as its inputs is overcome.On the other hand,the identification by the ADRFNNs online with high accuracy and the adaptive function of the correction term's gain in the GASMVSC make the system possess strong robustness and improved steady accuracy,and the chattering phenomenon of the control effort is also suppressed effectively.
基金supported by the US National Science Foundation (CMMI-1052872)the Ministry of Education of China
文摘An adaptive robust approach for actuator fault-tolerant control of a class of uncertain nonlinear systems is proposed.The two chief ways in which the system performance can degrade following an actuator-fault are undesirable transients and unacceptably large steady-state tracking errors.Adaptive control based schemes can achieve good final tracking accuracy in spite of change in system parameters following an actuator fault,and robust control based designs can achieve guaranteed transient response.However,neither adaptive control nor robust control based fault-tolerant designs can address both the issues associated with actuator faults.In the present work,an adaptive robust fault-tolerant control scheme is claimed to solve both the problems,as it seamlessly integrates adaptive and robust control design techniques.Comparative simulation studies are performed using a nonlinear hypersonic aircraft model to show the effectiveness of the proposed scheme over a robust adaptive control based faulttolerant scheme.
文摘For electro-discharge machining, only in the optimum state could the highest material removal rate be realized. In practical machining process, the timely elevation of the tool electrode is needed to eliminate chipping, which ordinarily occupies quite a lot of time. Therefore, besides the control of the machining parameters, the control of the optimum discharge gap and the conversion of different machining states is also needed. In this paper, the adaptive fuzzy control system of servomechanism for EDM combined with ultrasonic vibration is studied, the servomechanism of which is composed of the stepping motor comprising variable steps and the inductive synchronizer. The fuzzy control technology is used to realize the control of the frequency and the step of the servomechanism. The adaptive fuzzy controller has three inputs and two outputs, which can well meet the actual control requirements. The constitution of the fuzzy control regulation for the step frequency is the key to the design of the whole fuzzy control system of the servomechanism. The step frequency is mainly determined by the position error and the change rate of the position error. When the value of the position error is high or medium, the controlled parameters are selected to eliminate the error; when the position error is lower, the controlled parameters are selected to avoid the over-orientation and thus keep the stability of the system. According to these, a fuzzy control table is established in advanced, which is used to express the relations between the fuzzy input parameters and the fuzzy output parameters. The input parameters and the output parameters are all expressed by the level-values in fuzzy field. Therefore, the output parameters used for control can be obtained for the fuzzy control table according to the detected actual input parameters, by which the EDM combined with ultrasonic vibration is improved and the machining efficiency is increased. In addition, a stimulation program is designed by means of Microsoft Visual Basic
基金This project was supported by the National Natural Science Foundation of China (69974028 60374015)
文摘For a class of unknown nonlinear time-delay systems, an adaptive neural network （NN） control design approach is proposed. Backstepping, domination and adaptive bounding design technique are combined to construct a robust memoryless adaptive NN tracking controller. Unknown time-delay functions are approximated by NNs, such that the requirement on the nonlinear time-delay functions is relaxed. Based on Lyapunov-Krasoviskii functional, the sem-global uniformly ultimately boundedness （UUB） of all the signals in the closed-loop system is proved. The arbitrary output tracking accuracy is achieved by tuning the design parameters. The feasibility is investigated by an illustrative simulation example.
基金Project(51005253) supported by the National Natural Science Foundation of ChinaProject(2007AA04Z344) supported by the National High Technology Research and Development Program of China
文摘A new adaptive Type-2 （T2） fuzzy controller was developed and its potential performance advantage over adaptive Type-1 （T1） fuzzy control was also quantified in computer simulation. Base on the Lyapunov method, the adaptive laws with guaranteed system stability and convergence were developed. The controller updates its parameters online using the laws to control a system and tracks its output command trajectory. The simulation study involving the popular inverted pendulum control problem shows theoretically predicted system stability and good tracking performance. And the comparison simulation experiments subjected to white noige or step disturbance indicate that the T2 controller is better than the T1 controller by 0--18%, depending on the experiment condition and performance measure.
基金This work was partially supported by the Provincial Natural Science Foundation of Jiangsu(Project no.BK20180474)the Natural Science Foundation of China(Project no.51805263,no.51705253,no.11572158).
文摘This paper puts forward an unprecedented avoidance-striking-arrival problem aiming to address the need for tank's uncertain mechanical systems on the intelligent battlefield.The associated system uncertainties(possibly rapid)are time-varying but bounded(possibly unknown).The goal is to design a controller that enables the tank to aim at and attack the enemy tank while keeping itself(out of the enemy fire zone).The tank maintains this condition until reaching the predefined region.In this paper,an approximate constraint following control method is adopted to solve this problem,and the original constraints are creatively divided into two categories:the avoidance-tracking constraint and the striking-arrival constraint.An adaptive robust control method is proposed and consequently verified through simulation experiments.It is proved that the system fully obeys the avoidance-tracking-constraint and strictly obeys the striking-arrival constraint under the control input.Besides,the control of the tank vehicle running system and tank gun bidirectional stabilization system are unified to deal with the control signal delay caused by complex uncertainties on the battlefield.Overall,this paper reduced the delay of signal transmission in the system while solved the avoidance-striking-arrival problem.
文摘The purpose of this paper is the design of neural network-based adaptive sliding mode controller for uncertain unknown nonlinear systems. A special architecture adaptive neural network, with hyperbolic tangent activation functions, is used to emulate the equivalent and switching control terms of the classic sliding mode control （SMC）. Lyapunov stability theory is used to guarantee a uniform ultimate boundedness property for the tracking error, as well as of all other signals in the closed loop. In addition to keeping the stability and robustness properties of the SMC, the neural network-based adaptive sliding mode controller exhibits perfect rejection of faults arising during the system operating. Simulation studies are used to illustrate and clarify the theoretical results.
基金Project(50905037) supported by the National Natural Science Foundation of ChinaProject(20092304120014) supported by Specialized Research Fund for the Doctoral Program of Higher Education of China+2 种基金 Project(20100471021) supported by the China Postdoctoral Science Foundation Project(LBH-Q09134) supported by Heilongjiang Postdoctoral Science-Research Foundation,China Project (HEUFT09013) supported by the Foundation of Harbin Engineering University,China
文摘The electro-hydraulic servo system was studied to cancel the amplitude attenuation and phase delay of its sinusoidal response,by developing a network using normalized least-mean-square (LMS) adaptive filtering algorithm.The command input was corrected by weights to generate the desired input for the algorithm,and the feedback was brought into the feedback correction,whose output was the weighted feedback.The weights of the normalized LMS adaptive filtering algorithm were updated on-line according to the estimation error between the desired input and the weighted feedback.Thus,the updated weights were copied to the input correction.The estimation error was forced to zero by the normalized LMS adaptive filtering algorithm such that the weighted feedback was equal to the desired input,making the feedback track the command.The above concept was used as a basis for the development of amplitude phase control.The method has good real-time performance without estimating the system model.The simulation and experiment results show that the proposed amplitude phase control can efficiently cancel the amplitude attenuation and phase delay with high precision.
文摘An adaptive control scheme is developed for a class of single-input nonlinear systems preceded by unknown hysteresis, which is a non-differentiable and multi-value mapping nonlinearity. The controller based on the three-layer neural network （NN）, whose weights are derived from Lyapunov stability analysis, guarantees closed-loop semiglobal stability and convergence of the tracking errors to a small residual set. An example is used to confirm the effectiveness of the proposed control scheme.
基金the National Natural Science Foundation of China (90716028 and 90405011).
文摘A robust adaptive trajectory linearization control （RATLC） algorithm for a class of nonlinear systems with uncertainty and disturbance based on the T-S fuzzy system is presented. The unknown disturbance and uncertainty are estimated by the T-S fuzzy system, and a robust adaptive control law is designed by the Lyapunov theory. Irrespective of whether the dimensions of the system and the rules of the fuzzy system are large or small, there is only one parameter adjusting on line. Uniformly ultimately boundedness of all signals of the composite closed-loop system are proved by theory analysis. Finally, a numerical example is studied based on the proposed method. The simulation results demonstrate the effectiveness and robustness of the control scheme.
基金Project(2007CB209707) supported by the National Basic Research Program of China
文摘In order to achieve the improvement of the driving comfort and energy efficiency,an new e-CVT flexible full hybrid electric system(E2FHS) is proposed,which uses an integrated main drive motor and generator to take the place of the original automatic or manual transmission to realize the functions of continuously variable transmission(e-CVT).The design and prototype realization of the E2FHS system for a plug-in hybrid vehicle(PHEV) is performed.In order to analyze and optimize the parameters and the power flux between different parts of the E2FHS,simulation software is developed.Especially,in order to optimize the performance of the energy economy improvement of the E2FHS,the effect of the different energy management controllers is investigated,and an adaptive online-optimal energy management controller for the E2FHS is built and validated by the prototype PHEV.
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 National Natural Science Foundation of China(90510010).
文摘A novel H∞ tracking-based decentralized indirect adaptive output feedback fuzzy controller for a class of uncertain large-scale nonlinear systems is developed. By virtue of the proper filtering of the observation error dynamics, the observer-based decentralized indirect adaptive fuzzy control scheme is presented for a class of large-scale nonlinear systems using the combination of H∞ tracking technique, a fuzzy adaptive observer and fuzzy inference systems. The output feedback and adaptation mechanisms are both robust and implementable indeed owing to their freedom from the unavailable observation error vector. All the signals of the closed-loop largescale system are guaranteed to stay uniformly bounded and the output errors take on H∞ tracking performance. Simulation results substantiate the effectiveness of the proposed scheme.
