This paper investigates interception missiles’trajectory tracking guidance problem under wind field and external disturbances in the boost phase.Indeed,the velocity control in such trajectory tracking guidance system...This paper investigates interception missiles’trajectory tracking guidance problem under wind field and external disturbances in the boost phase.Indeed,the velocity control in such trajectory tracking guidance systems of missiles is challenging.As our contribution,the velocity control channel is designed to deal with the intractable velocity problem and improve tracking accuracy.The global prescribed performance function,which guarantees the tracking error within the set range and the global convergence of the tracking guidance system,is first proposed based on the traditional PPF.Then,a tracking guidance strategy is derived using the integral sliding mode control techniques to make the sliding manifold and tracking errors converge to zero and avoid singularities.Meanwhile,an improved switching control law is introduced into the designed tracking guidance algorithm to deal with the chattering problem.A back propagation neural network(BPNN)extended state observer(BPNNESO)is employed in the inner loop to identify disturbances.The obtained results indicate that the proposed tracking guidance approach achieves the trajectory tracking guidance objective without and with disturbances and outperforms the existing tracking guidance schemes with the lowest tracking errors,convergence times,and overshoots.展开更多
A neural-network-based adaptive gain scheduling backstepping sliding mode control（NNAGS-BSMC） approach for a class of uncertain strict-feedback nonlinear system is proposed.First, the control problem of uncertain st...A neural-network-based adaptive gain scheduling backstepping sliding mode control（NNAGS-BSMC） approach for a class of uncertain strict-feedback nonlinear system is proposed.First, the control problem of uncertain strict-feedback nonlinear systems is formulated. Second, the detailed design of NNAGSBSMC is described. The sliding mode control（SMC） law is designed to track a referenced output via backstepping technique.To decrease chattering result from SMC, a radial basis function neural network（RBFNN） is employed to construct the NNAGSBSMC to facilitate adaptive gain scheduling, in which the gains are scheduled adaptively via neural network（NN）, with sliding surface and its differential as NN inputs and the gains as NN outputs. Finally, the verification example is given to show the effectiveness and robustness of the proposed approach. Contrasting simulation results indicate that the NNAGS-BSMC decreases the chattering effectively and has better control performance against the BSMC.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
Reasons and realities such as being non-linear of dynamical equations,being lightweight and unstable nature of quadrotor,along with internal and external disturbances and parametric uncertainties,have caused that the ...Reasons and realities such as being non-linear of dynamical equations,being lightweight and unstable nature of quadrotor,along with internal and external disturbances and parametric uncertainties,have caused that the controller design for these quadrotors is considered the challenging issue of the day.In this work,an adaptive sliding mode controller based on neural network is proposed to control the altitude of a quadrotor.The error and error derivative of the altitude of a quadrotor are the inputs of neural network and altitude sliding surface variable is its output.Neural network estimates the sliding surface variable adaptively according to the conditions of quadrotor and sets the altitude of a quadrotor equal to the desired value.The proposed controller stability has been proven by Lyapunov theory and it is shown that all system states reach to sliding surface and are remaining in it.The superiority of the proposed control method has been proven by comparison and simulation results.展开更多
An adaptive fuzzy sliding mode control （AFSMC） ap- proach is proposed for a robotic airship. First, the mathematical model of an airship is derived in the form of a nonlinear control system. Second, an AFSMC approac...An adaptive fuzzy sliding mode control （AFSMC） ap- proach is proposed for a robotic airship. First, the mathematical model of an airship is derived in the form of a nonlinear control system. Second, an AFSMC approach is proposed to design the attitude control system of airship, and the global stability of the closed-loop system is proved by using the Lyapunov stability theorem. Finally, simulation results verify the effectiveness and robustness of the proposed control approach in the presence of model uncertainties and external disturbances.展开更多
Aiming at a class of systems under parameter perturbations and unknown external disturbances, a method of fuzzy robust sliding mode control was proposed. Firstly, an integral sliding mode surface containing state feed...Aiming at a class of systems under parameter perturbations and unknown external disturbances, a method of fuzzy robust sliding mode control was proposed. Firstly, an integral sliding mode surface containing state feedback item was designed based on robust H∞ control theory. The robust state feedback control was utilized to substitute for the equivalent control of the traditional sliding mode control. Thus the robustness of systems sliding mode motion was improved even the initial states were unknown. Furthermore, when the upper bound of disturbance was unknown, the switching control logic was difficult to design, and the drawbacks of chattering in sliding mode control should also be considered simultaneously. To solve the above-mentioned problems, the fuzzy nonlinear method was applied to approximate the switching control term. Based on the Lyapunov stability theory, the parameter adaptive law which could guarantee the system stability was devised. The proposed control strategy could reduce the system chattering effectively. And the control input would not switch sharply, which improved the practicality of the sliding mode controller. Finally, simulation was conducted on system with parameter perturbations and unknown external disturbances. The result shows that the proposed method could enhance the approaching motion performance effectively. The chattering phenomenon is weakened, and the system possesses stronger robustness against parameter perturbations and external disturbances.展开更多
A robust sliding mode control algorithm is developed for a class of networked control system with packet dropouts in both sensor-controller channel and controller-actuator channel,and at the same time mismatched param...A robust sliding mode control algorithm is developed for a class of networked control system with packet dropouts in both sensor-controller channel and controller-actuator channel,and at the same time mismatched parametric uncertainty and external disturbance are also taken into consideration.A two-level Bernoulli process has been used to describe the packet dropouts existing in both channels.A novel integral sliding surface is proposed,based on which the H∞performance of system sliding mode motion is analyzed.Then the sufficient condition for system stability and robustness is derived in the form of linear matrix inequality(LMI).A sliding mode controller is designed which can guarantee a relatively ideal system dynamic performance and has certain robustness against unknown parameter perturbations and external disturbances.The results from numerical simulations are presented to corroborate the validity of the proposed controller.展开更多
In this paper, an adaptive dynamic control scheme based on a fuzzy neural network is presented, that presents utilizes both feed-forward and feedback controller elements. The former of the two elements comprises a neu...In this paper, an adaptive dynamic control scheme based on a fuzzy neural network is presented, that presents utilizes both feed-forward and feedback controller elements. The former of the two elements comprises a neural network with both identification and control role, and the latter is a fuzzy neural algorithm, which is introduced to provide additional control enhancement. The feedforward controller provides only coarse control, whereas the feedback controller can generate on-line conditional proposition rule automatically to improve the overall control action. These properties make the design very versatile and applicable to a range of industrial applications.展开更多
In this paper, a novel fuzzy sliding mode control（FSMC） guidance law with terminal constraints of miss distance, impact angle and acceleration is presented for a constant speed missile against the stationary or slow...In this paper, a novel fuzzy sliding mode control（FSMC） guidance law with terminal constraints of miss distance, impact angle and acceleration is presented for a constant speed missile against the stationary or slowly moving target. The proposed guidance law combines the sliding mode control algorithm with a fuzzy logic control scheme for the lag-free system and the first-order lag system. Through using Lyapunov stability theory, we prove the sliding surface converges to zero in finite time. Furthermore, considering the uncertain information and system disturbances, the guidance gains are on-line optimized by fuzzy logic technique. Numerical simulations are performed to demonstrate the performance of the FSMC guidance law and the results illustrate the validity and effectiveness of the proposed guidance law.展开更多
The direct torque control of the dual star induction motor(DTC-DSIM) using conventional PI controllers is characterized by unsatisfactory performance, such as high ripples of torque and flux, and sensitivity to parame...The direct torque control of the dual star induction motor(DTC-DSIM) using conventional PI controllers is characterized by unsatisfactory performance, such as high ripples of torque and flux, and sensitivity to parametric variations. Among the most evoked control strategies adopted in this field to overcome these drawbacks presented in classical drive, it is worth mentioning the use of the second order sliding mode control(SOSMC) based on the super twisting algorithm(STA) combined with the fuzzy logic control(FSOSMC). In order to realize the optimal control performance, the FSOSMC parameters are adjusted using an optimization algorithm based on the genetic algorithm(GA). The performances of the envisaged control scheme, called G-FSOSMC, are investigated against G-SOSMC, G-PI and BBO-FSOSMC algorithms. The proposed controller scheme is efficient in reducing the torque and flux ripples, and successfully suppresses chattering. The effects of parametric uncertainties do not affect system performance.展开更多
A nonlinear pressure controller was presented to track desired feeding pressure for the cutter feeding system(CFS) of trench cutter(TC) in the presence of unknown external disturbances.The feeding pressure control of ...A nonlinear pressure controller was presented to track desired feeding pressure for the cutter feeding system(CFS) of trench cutter(TC) in the presence of unknown external disturbances.The feeding pressure control of CFS is subjected to unknown load characteristics of rock or soil; in addition,the geological condition is time-varying.Due to the complex load characteristics of rock or soil,the feeding velocity of TC is related to geological conditions.What is worse,its dynamic model is subjected to uncertainties and its function is unknown.To deal with the particular characteristics of CFS,a novel adaptive fuzzy integral sliding mode control(AFISMC) was designed for feeding pressure control of CFS,which combines the robust characteristics of an integral sliding mode controller and the adaptive adjusting characteristics of an adaptive fuzzy controller.The AFISMC feeding pressure controller is synthesized using the backstepping technique.The stability of the overall closed-loop system consisting of the adaptive fuzzy inference system,integral sliding mode controller and the cutter feeding system is proved using Lyapunov theory.Experiments are conducted on a TC test bench with the AFISMC under different operating conditions.The experimental results demonstrate that the proposed AFISMC feeding pressure controller for CFS gives a superior and robust pressure tracking performance with maximum pressure tracking error within ?0.3 MPa.展开更多
A fuzzy sliding-mode control (FSMC) scheme based on T-S fuzzy models was proposed for the permanent magnet synchronous motor (PMSM) drive system to solve the speed tracking problem. A T-S fuzzy model was firstly forme...A fuzzy sliding-mode control (FSMC) scheme based on T-S fuzzy models was proposed for the permanent magnet synchronous motor (PMSM) drive system to solve the speed tracking problem. A T-S fuzzy model was firstly formed to represent the nonlinear system of PMSM. For converting the tracking control into a stabilization problem, a new control design was proposed to define the internal desired states. Then, the FSMC controller for PMSM system with parameter variation and load disturbance was designed based on the fuzzy model. The performance of the proposed controller was verified by experimental results on PMSM system. The results show that the FSMC scheme can drive the dynamics of PMSM into a designated sliding surface in finite time and guarantee the property of asymptotical stability. The information of upper bound of modeling errors as well as perturbations is not required when using the FSMC controller.展开更多
Non-linearity and parameter time-variety are inherent properties of lateral motions of a vehicle. How to effectively control intelligent vehicle (IV) lateral motions is a challenging task. Controller design can be reg...Non-linearity and parameter time-variety are inherent properties of lateral motions of a vehicle. How to effectively control intelligent vehicle (IV) lateral motions is a challenging task. Controller design can be regarded as a process of searching optimal structure from controller structure space and searching optimal parameters from parameter space. Based on this view, an intelligent vehicle lateral motions controller was designed. The controller structure was constructed by T-S fuzzy-neural network (FNN). Its parameters were searched and selected with genetic algorithm (GA). The simulation results indicate that the controller designed has strong robustness, high precision and good ride quality, and it can effectively resolve IV lateral motion non-linearity and time-variant parameters problem.展开更多
The problem of direct adaptive neural network control for a class of large-scale systems with unknown function control gains and the high-order interconneetions is studied in this paper. Based on the principle of slid...The problem of direct adaptive neural network control for a class of large-scale systems with unknown function control gains and the high-order interconneetions is studied in this paper. Based on the principle of sliding mode control and the approximation capability of multilayer neural networks, a design scheme of decentralized di- rect adaptive sliding mode controller is proposed. The plant dynamic uncertainty and modeling errors are adaptively compensated by adjusted the weights and sliding mode gains on-line for each subsystem using only local informa- tion. According to the Lyapunov method, the closed-loop adaptive control system is proven to be globally stable, with tracking errors converging to a neighborhood of zero. Simulation results demonstrate the effectiveness of the proposed approach.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
In this paper, a modeling algorithm developed by transferring the adaptive fuzzy inference neural network into an on-line real time algorithm, combining the algorithm with conventional system identification method and...In this paper, a modeling algorithm developed by transferring the adaptive fuzzy inference neural network into an on-line real time algorithm, combining the algorithm with conventional system identification method and applying them to separate identification of nonlinear multi-variable systems is introduced and discussed.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
基金the National Natural Science Foundation of China(Grant No.12072090).
文摘This paper investigates interception missiles’trajectory tracking guidance problem under wind field and external disturbances in the boost phase.Indeed,the velocity control in such trajectory tracking guidance systems of missiles is challenging.As our contribution,the velocity control channel is designed to deal with the intractable velocity problem and improve tracking accuracy.The global prescribed performance function,which guarantees the tracking error within the set range and the global convergence of the tracking guidance system,is first proposed based on the traditional PPF.Then,a tracking guidance strategy is derived using the integral sliding mode control techniques to make the sliding manifold and tracking errors converge to zero and avoid singularities.Meanwhile,an improved switching control law is introduced into the designed tracking guidance algorithm to deal with the chattering problem.A back propagation neural network(BPNN)extended state observer(BPNNESO)is employed in the inner loop to identify disturbances.The obtained results indicate that the proposed tracking guidance approach achieves the trajectory tracking guidance objective without and with disturbances and outperforms the existing tracking guidance schemes with the lowest tracking errors,convergence times,and overshoots.
基金supported by the National Natural Science Foundation of China(11502288)the Natural Science Foundation of Hunan Province(2016JJ3019)+1 种基金the Aeronautical Science Foundation of China(2017ZA88001)the Scientific Research Project of National University of Defense Technology(ZK17-03-32)
文摘A neural-network-based adaptive gain scheduling backstepping sliding mode control（NNAGS-BSMC） approach for a class of uncertain strict-feedback nonlinear system is proposed.First, the control problem of uncertain strict-feedback nonlinear systems is formulated. Second, the detailed design of NNAGSBSMC is described. The sliding mode control（SMC） law is designed to track a referenced output via backstepping technique.To decrease chattering result from SMC, a radial basis function neural network（RBFNN） is employed to construct the NNAGSBSMC to facilitate adaptive gain scheduling, in which the gains are scheduled adaptively via neural network（NN）, with sliding surface and its differential as NN inputs and the gains as NN outputs. Finally, the verification example is given to show the effectiveness and robustness of the proposed approach. Contrasting simulation results indicate that the NNAGS-BSMC decreases the chattering effectively and has better control performance against the BSMC.
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authorities of East Tehran Branch,Islamic Azad University,Tehran,Iran,for providing support and necessary facilities
文摘Reasons and realities such as being non-linear of dynamical equations,being lightweight and unstable nature of quadrotor,along with internal and external disturbances and parametric uncertainties,have caused that the controller design for these quadrotors is considered the challenging issue of the day.In this work,an adaptive sliding mode controller based on neural network is proposed to control the altitude of a quadrotor.The error and error derivative of the altitude of a quadrotor are the inputs of neural network and altitude sliding surface variable is its output.Neural network estimates the sliding surface variable adaptively according to the conditions of quadrotor and sets the altitude of a quadrotor equal to the desired value.The proposed controller stability has been proven by Lyapunov theory and it is shown that all system states reach to sliding surface and are remaining in it.The superiority of the proposed control method has been proven by comparison and simulation results.
基金supported by the Hunan Provincial Innovation Foundation for Postgraduate (CX2011B005)the National University of Defense Technlolgy Innovation Foundation for Postgraduate (B110105)
文摘An adaptive fuzzy sliding mode control （AFSMC） ap- proach is proposed for a robotic airship. First, the mathematical model of an airship is derived in the form of a nonlinear control system. Second, an AFSMC approach is proposed to design the attitude control system of airship, and the global stability of the closed-loop system is proved by using the Lyapunov stability theorem. Finally, simulation results verify the effectiveness and robustness of the proposed control approach in the presence of model uncertainties and external disturbances.
基金Project(51476187)supported by the National Natural Science Foundation of China
文摘Aiming at a class of systems under parameter perturbations and unknown external disturbances, a method of fuzzy robust sliding mode control was proposed. Firstly, an integral sliding mode surface containing state feedback item was designed based on robust H∞ control theory. The robust state feedback control was utilized to substitute for the equivalent control of the traditional sliding mode control. Thus the robustness of systems sliding mode motion was improved even the initial states were unknown. Furthermore, when the upper bound of disturbance was unknown, the switching control logic was difficult to design, and the drawbacks of chattering in sliding mode control should also be considered simultaneously. To solve the above-mentioned problems, the fuzzy nonlinear method was applied to approximate the switching control term. Based on the Lyapunov stability theory, the parameter adaptive law which could guarantee the system stability was devised. The proposed control strategy could reduce the system chattering effectively. And the control input would not switch sharply, which improved the practicality of the sliding mode controller. Finally, simulation was conducted on system with parameter perturbations and unknown external disturbances. The result shows that the proposed method could enhance the approaching motion performance effectively. The chattering phenomenon is weakened, and the system possesses stronger robustness against parameter perturbations and external disturbances.
基金Projects(51476187,51506221,51606219) supported by the National Natural Science Foundation of China
文摘A robust sliding mode control algorithm is developed for a class of networked control system with packet dropouts in both sensor-controller channel and controller-actuator channel,and at the same time mismatched parametric uncertainty and external disturbance are also taken into consideration.A two-level Bernoulli process has been used to describe the packet dropouts existing in both channels.A novel integral sliding surface is proposed,based on which the H∞performance of system sliding mode motion is analyzed.Then the sufficient condition for system stability and robustness is derived in the form of linear matrix inequality(LMI).A sliding mode controller is designed which can guarantee a relatively ideal system dynamic performance and has certain robustness against unknown parameter perturbations and external disturbances.The results from numerical simulations are presented to corroborate the validity of the proposed controller.
基金China Postdoctoral Science Foundation and Natural Science of Heibei Province!698004
文摘In this paper, an adaptive dynamic control scheme based on a fuzzy neural network is presented, that presents utilizes both feed-forward and feedback controller elements. The former of the two elements comprises a neural network with both identification and control role, and the latter is a fuzzy neural algorithm, which is introduced to provide additional control enhancement. The feedforward controller provides only coarse control, whereas the feedback controller can generate on-line conditional proposition rule automatically to improve the overall control action. These properties make the design very versatile and applicable to a range of industrial applications.
基金supported by the National Natural Science Foundation of China(6130422461305018+1 种基金61472423)the National Advanced Research Project of China(51301010206)
文摘In this paper, a novel fuzzy sliding mode control（FSMC） guidance law with terminal constraints of miss distance, impact angle and acceleration is presented for a constant speed missile against the stationary or slowly moving target. The proposed guidance law combines the sliding mode control algorithm with a fuzzy logic control scheme for the lag-free system and the first-order lag system. Through using Lyapunov stability theory, we prove the sliding surface converges to zero in finite time. Furthermore, considering the uncertain information and system disturbances, the guidance gains are on-line optimized by fuzzy logic technique. Numerical simulations are performed to demonstrate the performance of the FSMC guidance law and the results illustrate the validity and effectiveness of the proposed guidance law.
基金Project supported by the LEB Research LaboratoryDepartment of Electrical Engineering,University of Batna 2, Algeria。
文摘The direct torque control of the dual star induction motor(DTC-DSIM) using conventional PI controllers is characterized by unsatisfactory performance, such as high ripples of torque and flux, and sensitivity to parametric variations. Among the most evoked control strategies adopted in this field to overcome these drawbacks presented in classical drive, it is worth mentioning the use of the second order sliding mode control(SOSMC) based on the super twisting algorithm(STA) combined with the fuzzy logic control(FSOSMC). In order to realize the optimal control performance, the FSOSMC parameters are adjusted using an optimization algorithm based on the genetic algorithm(GA). The performances of the envisaged control scheme, called G-FSOSMC, are investigated against G-SOSMC, G-PI and BBO-FSOSMC algorithms. The proposed controller scheme is efficient in reducing the torque and flux ripples, and successfully suppresses chattering. The effects of parametric uncertainties do not affect system performance.
基金Supported by National High Technology Research and Development Program of China （863 Program） （2007AA04Z239） and National Natural Science Foundation of China （60621001, 60975060）
基金Project(2012AA041801)supported by the High-tech Research and Development Program of China
文摘A nonlinear pressure controller was presented to track desired feeding pressure for the cutter feeding system(CFS) of trench cutter(TC) in the presence of unknown external disturbances.The feeding pressure control of CFS is subjected to unknown load characteristics of rock or soil; in addition,the geological condition is time-varying.Due to the complex load characteristics of rock or soil,the feeding velocity of TC is related to geological conditions.What is worse,its dynamic model is subjected to uncertainties and its function is unknown.To deal with the particular characteristics of CFS,a novel adaptive fuzzy integral sliding mode control(AFISMC) was designed for feeding pressure control of CFS,which combines the robust characteristics of an integral sliding mode controller and the adaptive adjusting characteristics of an adaptive fuzzy controller.The AFISMC feeding pressure controller is synthesized using the backstepping technique.The stability of the overall closed-loop system consisting of the adaptive fuzzy inference system,integral sliding mode controller and the cutter feeding system is proved using Lyapunov theory.Experiments are conducted on a TC test bench with the AFISMC under different operating conditions.The experimental results demonstrate that the proposed AFISMC feeding pressure controller for CFS gives a superior and robust pressure tracking performance with maximum pressure tracking error within ?0.3 MPa.
基金Project (60835004) supported by the National Natural Science Foundation of China
文摘A fuzzy sliding-mode control (FSMC) scheme based on T-S fuzzy models was proposed for the permanent magnet synchronous motor (PMSM) drive system to solve the speed tracking problem. A T-S fuzzy model was firstly formed to represent the nonlinear system of PMSM. For converting the tracking control into a stabilization problem, a new control design was proposed to define the internal desired states. Then, the FSMC controller for PMSM system with parameter variation and load disturbance was designed based on the fuzzy model. The performance of the proposed controller was verified by experimental results on PMSM system. The results show that the FSMC scheme can drive the dynamics of PMSM into a designated sliding surface in finite time and guarantee the property of asymptotical stability. The information of upper bound of modeling errors as well as perturbations is not required when using the FSMC controller.
文摘Non-linearity and parameter time-variety are inherent properties of lateral motions of a vehicle. How to effectively control intelligent vehicle (IV) lateral motions is a challenging task. Controller design can be regarded as a process of searching optimal structure from controller structure space and searching optimal parameters from parameter space. Based on this view, an intelligent vehicle lateral motions controller was designed. The controller structure was constructed by T-S fuzzy-neural network (FNN). Its parameters were searched and selected with genetic algorithm (GA). The simulation results indicate that the controller designed has strong robustness, high precision and good ride quality, and it can effectively resolve IV lateral motion non-linearity and time-variant parameters problem.
基金This project was supported by the National Natural Science Foundation (60074013 &10371106)the Natural ScienceFoundation of Education Bureau of Jiangsu (KK0310067) the Foundation of Information Science Subject Group of YangzhouUniversity (ISG030606)
文摘The problem of direct adaptive neural network control for a class of large-scale systems with unknown function control gains and the high-order interconneetions is studied in this paper. Based on the principle of sliding mode control and the approximation capability of multilayer neural networks, a design scheme of decentralized di- rect adaptive sliding mode controller is proposed. The plant dynamic uncertainty and modeling errors are adaptively compensated by adjusted the weights and sliding mode gains on-line for each subsystem using only local informa- tion. According to the Lyapunov method, the closed-loop adaptive control system is proven to be globally stable, with tracking errors converging to a neighborhood of zero. Simulation results demonstrate the effectiveness of the proposed approach.
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.
文摘In this paper, a modeling algorithm developed by transferring the adaptive fuzzy inference neural network into an on-line real time algorithm, combining the algorithm with conventional system identification method and applying them to separate identification of nonlinear multi-variable systems is introduced and discussed.
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.
