In this paper, adaptive variable structure neural control is presented for a class of uncertain multi-input multi-output （MIMO） nonlinear systems with state time-varying delays and unknown nonlinear dead-zones. The ...In this paper, adaptive variable structure neural control is presented for a class of uncertain multi-input multi-output （MIMO） nonlinear systems with state time-varying delays and unknown nonlinear dead-zones. The unknown time-varying delay uncer- tainties are compensated for using appropriate Lyapunov-Krasovskii functionals in the design. The approach removes the assumption of linear function outside the deadband without necessarily constructing a dead-zone inverse as an added contribution. By utilizing the integral-type Lyapunov function and introducing an adaptive compensation term for the upper bound of the residual and optimal approximation error as well as the dead-zone disturbance, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded. In addition, a modified adaptive control algorithm is given in order to avoid the high-frequency chattering phenomenon. Simulation results demonstrate the effectiveness of the approach.展开更多
A neural-network-based adaptive variable structure control methodology isproposed for the tracking problem of nonlinear discrete-time input-output systems. The unknowndynamics of the system are approximated via radial...A neural-network-based adaptive variable structure control methodology isproposed for the tracking problem of nonlinear discrete-time input-output systems. The unknowndynamics of the system are approximated via radial basis function neural networks. The control lawis based on sliding modes and simple to implement. The discrete-time adaptive law for tuning theweight of neural networks is presented using the adaptive filtering algorithm with residueupper-bound compensation. The application of the proposed controller to engine idle speed controldesign is discussed. The results indicate the validation and effectiveness of this 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
The problem of adaptive fuzzy control for a class of large-scale, time-delayed systems with unknown nonlinear dead-zone is discussed here. Based on the principle of variable structure control, a design scheme of adapt...The problem of adaptive fuzzy control for a class of large-scale, time-delayed systems with unknown nonlinear dead-zone is discussed here. Based on the principle of variable structure control, a design scheme of adaptive, decentralized, variable structure control is proposed. The approach removes the conditions that the dead-zone slopes and boundaries are equal and symmetric, respectively. In addition, it does not require that the assumptions that all parameters of the nonlinear dead-zone model and the lumped uncertainty are known constants. The adaptive compensation terms of the approximation errors axe adopted to minimize the influence of modeling errors and parameter estimation errors. By theoretical analysis, the closed-loop control system is proved to be semiglobally uniformly ultimately bounded, with tracking errors converging to zero. Simulation results demonstrate the effectiveness of the approach.展开更多
The increasing demand on robotic system performance leads to the use of advanced control strategies. A variable structure model-following adaptive control design is presented for the nonlinear robot manipulator sys...The increasing demand on robotic system performance leads to the use of advanced control strategies. A variable structure model-following adaptive control design is presented for the nonlinear robot manipulator systems, when subjected to fast and wide ranges of unknown-but-bounded parameter variations and disturbances. The design does not require any knowledge of a nonlinear robotic system. The system is robust and insensitive to the parameter variation, disturbances, as well as to the unmodeled dynamics. This insensitive property enables the elimination of interactions among the various joints of the robotic manipulator. In the closed loop, the robotic system asymptotically converges to the reference trajectory with a Prescribed transient resPOnse. The problem of chattering is discussed with the introduction of the special approaches: boundary layer, smoothing law, and nonlinear compensation.展开更多
Considering the increase of structural disturbance caused by large thrust misalignment and lack of synchronism after installation of the solid booster on the rock,as well as the increase of external disturbance result...Considering the increase of structural disturbance caused by large thrust misalignment and lack of synchronism after installation of the solid booster on the rock,as well as the increase of external disturbance resulting from the installation of the configuration and tail,while also considering the parameter uncertainties,parameter perturbations,unmodeled dynamics and coupling between channels during modeling,this paper proposes the design method for the adaptive control of sliding mode variable structure,based on the model reference. The paper firstly establishes the attitude dynamics model for the solid strap-on launch vehicle; then proposes the design method for the adaptive control of the sliding mode variable structure based on the model reference,implements the design of attitude control system for the three channels respectively,and uses the Lyapunov function to prove the global asymptotic stability; and finally verifies,through numerical simulation,that the control method proposed in this paper can guarantee the attitude stability of rockets in the primary flight phase.展开更多
A variable structure model reference adaptive control problem for the nonlinear system is studied in this paper. First, according to the relative degree concept of th nonlinear control system an error equation between...A variable structure model reference adaptive control problem for the nonlinear system is studied in this paper. First, according to the relative degree concept of th nonlinear control system an error equation between the outputs of the reference model and the controlled plant is derived. Then, by using the variable structrue control method, an algorithm of variable structure model reference adaptive control is deduced on the basis of a new concept of reaching law. The definition of the SISO system is introduced into the MIMO nonlinear system. Finally, as an example, a pendulum nonlinear control system is simulated to demonstrated the effectiveness of the method. The results show that the method has some advantages: the design is simple, intuitive and easy to be realized in engineering. Besides, it is of practical significance for the synthesis of nonlinear control systems.展开更多
In this paper, a neural-network-based variable structure control scheme is presented for a class of nonlinear systems with a general low triangular structure. The proposed variable structure controller is proved to be...In this paper, a neural-network-based variable structure control scheme is presented for a class of nonlinear systems with a general low triangular structure. The proposed variable structure controller is proved to be Cl, thus can be applied for backstepping design, which has extended the scope of previous nonlinear systems in the form of strict-feedback and pure-feedback. With the help of neural network approximator, H-∞ performance analysis of stability is given. The effectiveness of proposed control law is verified via simulation.展开更多
In this study an indirect adaptive sliding mode control (SMC) based on a fuzzy logic scheme is proposed to strengthen the tracking control performance of a general class of multi-input multi-output (MIMO) nonlinear un...In this study an indirect adaptive sliding mode control (SMC) based on a fuzzy logic scheme is proposed to strengthen the tracking control performance of a general class of multi-input multi-output (MIMO) nonlinear uncertain systems. Combining reaching law approach and fuzzy universal approximation theorem, the proposed design procedure combines the advantages of fuzzy logic control, adaptive control and sliding mode control. The stability of the control systems is proved in the sense of the Lyapunov second stability theorem. Two simulation studies are presented to demonstrate the effectiveness of our new hybrid control algorithm.展开更多
A design scheme of variable structure model reference control systems using only input and output measurements is presented for the systems with unmodeled dynamics and disturbances in input and output channels. The mo...A design scheme of variable structure model reference control systems using only input and output measurements is presented for the systems with unmodeled dynamics and disturbances in input and output channels. The modeled part of the systems has relative degree greater than one and unknown upper bound of degree. By introducing some auxiliary signals and normalized signals with memory functions and appropriate choice of controller parameters, the developed variable structure controller guarantees the global stability of the closed-loop system and the arbitrarily small tracking error.展开更多
A neural network (NN) based adaptive control law is proposed for the tracking control of an n link robot manipulator with unknown dynamic nonlinearities. Basis function like nets are employed to approximate the plant ...A neural network (NN) based adaptive control law is proposed for the tracking control of an n link robot manipulator with unknown dynamic nonlinearities. Basis function like nets are employed to approximate the plant nonlinearities, and the bound on the NN reconstruction error is assumed to be unknown. The proposed NN based adaptive control approach integrates an NN approach with an adaptive implementation of discrete variable structure control with a simple estimation law to estimate the upper bound on the NN reconstruction error and an additional control input to be updated as a function of the estimate. Lyapunov stability theory is used to prove the uniform ultimate boundedness of the tracking error.展开更多
基金supported by National Natural Science Foundationof China (No. 60774017 and No. 60874045)
文摘In this paper, adaptive variable structure neural control is presented for a class of uncertain multi-input multi-output （MIMO） nonlinear systems with state time-varying delays and unknown nonlinear dead-zones. The unknown time-varying delay uncer- tainties are compensated for using appropriate Lyapunov-Krasovskii functionals in the design. The approach removes the assumption of linear function outside the deadband without necessarily constructing a dead-zone inverse as an added contribution. By utilizing the integral-type Lyapunov function and introducing an adaptive compensation term for the upper bound of the residual and optimal approximation error as well as the dead-zone disturbance, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded. In addition, a modified adaptive control algorithm is given in order to avoid the high-frequency chattering phenomenon. Simulation results demonstrate the effectiveness of the approach.
基金This project is supported by National Natural Science Foundation of China (No.59806007)
文摘A neural-network-based adaptive variable structure control methodology isproposed for the tracking problem of nonlinear discrete-time input-output systems. The unknowndynamics of the system are approximated via radial basis function neural networks. The control lawis based on sliding modes and simple to implement. The discrete-time adaptive law for tuning theweight of neural networks is presented using the adaptive filtering algorithm with residueupper-bound compensation. The application of the proposed controller to engine idle speed controldesign is discussed. The results indicate the validation and effectiveness of this 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.
基金This project was supported by the National Natural Science Foundation of China (60074013)the Foundation of New Era Talent Engineering of Yangzhou University.
文摘The problem of adaptive fuzzy control for a class of large-scale, time-delayed systems with unknown nonlinear dead-zone is discussed here. Based on the principle of variable structure control, a design scheme of adaptive, decentralized, variable structure control is proposed. The approach removes the conditions that the dead-zone slopes and boundaries are equal and symmetric, respectively. In addition, it does not require that the assumptions that all parameters of the nonlinear dead-zone model and the lumped uncertainty are known constants. The adaptive compensation terms of the approximation errors axe adopted to minimize the influence of modeling errors and parameter estimation errors. By theoretical analysis, the closed-loop control system is proved to be semiglobally uniformly ultimately bounded, with tracking errors converging to zero. Simulation results demonstrate the effectiveness of the approach.
文摘The increasing demand on robotic system performance leads to the use of advanced control strategies. A variable structure model-following adaptive control design is presented for the nonlinear robot manipulator systems, when subjected to fast and wide ranges of unknown-but-bounded parameter variations and disturbances. The design does not require any knowledge of a nonlinear robotic system. The system is robust and insensitive to the parameter variation, disturbances, as well as to the unmodeled dynamics. This insensitive property enables the elimination of interactions among the various joints of the robotic manipulator. In the closed loop, the robotic system asymptotically converges to the reference trajectory with a Prescribed transient resPOnse. The problem of chattering is discussed with the introduction of the special approaches: boundary layer, smoothing law, and nonlinear compensation.
文摘Considering the increase of structural disturbance caused by large thrust misalignment and lack of synchronism after installation of the solid booster on the rock,as well as the increase of external disturbance resulting from the installation of the configuration and tail,while also considering the parameter uncertainties,parameter perturbations,unmodeled dynamics and coupling between channels during modeling,this paper proposes the design method for the adaptive control of sliding mode variable structure,based on the model reference. The paper firstly establishes the attitude dynamics model for the solid strap-on launch vehicle; then proposes the design method for the adaptive control of the sliding mode variable structure based on the model reference,implements the design of attitude control system for the three channels respectively,and uses the Lyapunov function to prove the global asymptotic stability; and finally verifies,through numerical simulation,that the control method proposed in this paper can guarantee the attitude stability of rockets in the primary flight phase.
文摘A variable structure model reference adaptive control problem for the nonlinear system is studied in this paper. First, according to the relative degree concept of th nonlinear control system an error equation between the outputs of the reference model and the controlled plant is derived. Then, by using the variable structrue control method, an algorithm of variable structure model reference adaptive control is deduced on the basis of a new concept of reaching law. The definition of the SISO system is introduced into the MIMO nonlinear system. Finally, as an example, a pendulum nonlinear control system is simulated to demonstrated the effectiveness of the method. The results show that the method has some advantages: the design is simple, intuitive and easy to be realized in engineering. Besides, it is of practical significance for the synthesis of nonlinear control systems.
基金Shanghai Leading Academic Discipline Project(B504)
文摘In this paper, a neural-network-based variable structure control scheme is presented for a class of nonlinear systems with a general low triangular structure. The proposed variable structure controller is proved to be Cl, thus can be applied for backstepping design, which has extended the scope of previous nonlinear systems in the form of strict-feedback and pure-feedback. With the help of neural network approximator, H-∞ performance analysis of stability is given. The effectiveness of proposed control law is verified via simulation.
文摘In this study an indirect adaptive sliding mode control (SMC) based on a fuzzy logic scheme is proposed to strengthen the tracking control performance of a general class of multi-input multi-output (MIMO) nonlinear uncertain systems. Combining reaching law approach and fuzzy universal approximation theorem, the proposed design procedure combines the advantages of fuzzy logic control, adaptive control and sliding mode control. The stability of the control systems is proved in the sense of the Lyapunov second stability theorem. Two simulation studies are presented to demonstrate the effectiveness of our new hybrid control algorithm.
文摘A design scheme of variable structure model reference control systems using only input and output measurements is presented for the systems with unmodeled dynamics and disturbances in input and output channels. The modeled part of the systems has relative degree greater than one and unknown upper bound of degree. By introducing some auxiliary signals and normalized signals with memory functions and appropriate choice of controller parameters, the developed variable structure controller guarantees the global stability of the closed-loop system and the arbitrarily small tracking error.
文摘A neural network (NN) based adaptive control law is proposed for the tracking control of an n link robot manipulator with unknown dynamic nonlinearities. Basis function like nets are employed to approximate the plant nonlinearities, and the bound on the NN reconstruction error is assumed to be unknown. The proposed NN based adaptive control approach integrates an NN approach with an adaptive implementation of discrete variable structure control with a simple estimation law to estimate the upper bound on the NN reconstruction error and an additional control input to be updated as a function of the estimate. Lyapunov stability theory is used to prove the uniform ultimate boundedness of the tracking error.
