Adaptive fuzzy systems and control design and stability analysis pdf

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adaptive fuzzy systems and control design and stability analysis pdf

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Adaptive Fuzzy Systems and Control: Design and Stability Analysis

MSC : 93B52, 93C Citation: Kunting Yu, Yongming Li. Adaptive fuzzy control for nonlinear systems with sampled data and time-varying input delay[J]. AIMS Mathematics, , 5 3 : Article views PDF downloads Cited by 2.

Figures Kunting Yu, Yongming Li. AIMS Mathematics , , 5 3 : Previous Article Next Article. Research article. Adaptive fuzzy control for nonlinear systems with sampled data and time-varying input delay. Download PDF. In this paper, an adaptive fuzzy backstepping control strategy is studied for nonlinear nonstrict feedback systems with sampled data and time-varying input delay.

Considering the practical application of the proposed control strategy, a time-varying signal transmission delay is investigated. By using fuzzy logic systems to approximate the unknown nonlinear functions, a fuzzy estimator FE model is proposed to estimate the states of the nonlinear plant, which is mainly utilized to support information of estimation states for the adaptive fuzzy controller.

In the proposed strategy, the constraint between the signal transmission delay and the time-varying input delay is given to ensure the stability of the closed-loop system, and the state vectors are transformed to address the problem of time-varying input delay. By using the backstepping control technique and the information of the FE model, an adaptive fuzzy backstepping controller is designed.

The proposed control strategy can guarantee that all signals of the closed-loop system are semi-globally uniformly ultimately bounded. Ultimately, a numerical simulation example is provided to verify the effectiveness of the proposed control method and theory. Related Papers:. Wang, Y. Zhang, J. Qiu, et al. Adaptive fuzzy backstepping control for a class of nonlinear systems with sampled and delayed measurements , IEEE T. Fuzzy Syst. Su, Z. Liu, G.

Lai, et al. Event-triggered adaptive fuzzy control for uncertain strictfeedback nonlinear systems with guaranteed transient performance , IEEE T. Zhang, X. Liu, Y. Li, Adaptive fuzzy tracking control for nonlinear strict-feedback systems with unmodeled dynamics via backstepping technique, Neurocomputing , IEEE T. Zhai, L. An, J.

Li, Simplified filtering-based adaptive fuzzy dynamic surface control approach for non-linear strict-feedback systems , IET Control Theory A. Li, X. Min, S. Zhou, C. Wu, P. Shi, Observer-based adaptive fuzzy tracking control of nonlinear systems with time delay and input saturation , Fuzzy Set. Chang, S. Tong, Y. Li, Adaptive fuzzy backstepping output constraint control of flexible manipulator with actuator saturation , Neur.

Chen, X. Liu, S. Tong, et al. Observer and adaptive fuzzy control design for nonlinear strict-feedback systems with unknown virtual control coe ffi cients , IEEE T. Li, S. Tong, T. Tong, K. Sun, S. Wang, B. Chen, C. Lin, Approximation-based adaptive fuzzy control for a class of nonstrict-feedback stochastic nonlinear systems , Sci. China Inform. Yao, M.

Tomizuka, Adaptive robust control of MIMO nonlinear systems in semi-strict feedback forms , Automatica, 37 , Ge, et al. Chen, K. Liu, X. Liu, et al. Cybernetics, 44 , Chen, Z. Guang, C. Cybernetics, 24 , Yin, P. Shi, H. Cybernetics, 46 , Na, Y. Huang, X. Wu, et al. Cybernetics, , In press. Li, L. Wang, H. Du, et al. Niu, L. Wu, X. Jing, et al. Adaptive fuzzy backstepping dynamic surface control for nonlinear input-delay systems , Neurocomputing, , Sun, P.

Shi, et al. Control design of interval type-2 fuzzy systems with actuator fault: sampled-data control approach , Inform. Ali, N. Gunasekaran, Q. Zhu, State estimation of T-S fuzzy delayed neural networks with Markovian jumping parameters using sampled-data control , Fuzzy Set. Liu, B. Guo, J. Park, et al. Nonfragile exponential synchronization of delayed complex dynamical networks with memory sampled-data control , IEEE T. Xiao, H. Lian, K. Teo, et al.

A new Lyapunov functional approach to sampled-data synchronization control for delayed neural networks , J. Franklin I. Li, K. Xing, et al.

Synchronization for distributed parameter NNs with mixed delays via sampled-data control , Neurocomping, , Fu, T. Li, T.

Adaptive fuzzy systems and control - design and stability analysis

Outputfeedback adaptive fuzzy control for a class of non. The design procedure aims at rendering stable fuzzy controllers. Design and stability analysis of fuzzy identifiers of nonlinear. During the controller design procedure, novel lyapunov. Passino, senior member, ieee abstract adaptive control for nonlinear timevarying systems is of both theoretical and practical importance. First, we show the concept of fuzzy blocks and consider the connection problems of fuzzy blocks diagrams. Fuzzy sets and systems 45 5 northholland stability analysis and design of fuzzy control systems kazuo tanaka and michio sugeno department of systems science, tokyo institute of technology, nagatsuta, midoriku, yokohama , japan received november revised may abstract.

Adaptive fuzzy control for nonlinear systems with sampled data and time-varying input delay

This paper considers the problem of observer-based adaptive fuzzy sliding mode control for switched uncertain nonlinear systems with dead-zone input in strict-feedback form. The explored switched systems include unknown nonlinearities, dead-zone and immeasurable states. Fuzzy logic systems are used to approximate unknown nonlinear functions of the dynamic system and unknown upper bounds of uncertainties, respectively. A state observer based on state variable filters is developed to estimate the immeasurable states. Adaptive technique and sliding mode control method are utilized to construct a controller.

In order to solve the precision and stability control problems of nonlinear uncertain systems applied in machining systems, in this paper, a robust adaptive fuzzy control technique based on Dynamic Surface Control DSC method is proposed for the generalized single-input single-output SISO uncertain nonlinear system. The designed robust adaptive fuzzy controller is applied to the 3D elliptical vibration cutting 3D EVC device system model, and the effectiveness of the controller design is verified by analysis of position tracking, speed tracking, and tracking error. The results of studies show that the robust adaptive fuzzy controller can effectively suppress the jitter problem of the three-dimensional elliptical vibration cutting device so that the control object can be stabilized quickly even if it has a little jitter at the beginning.

Article Info.

In the adaptive fuzzy control field for affine nonlinear systems, there are two basic configurations: direct and indirect. It is well known that the direct configuration needs more restrictions on the control gain than the indirect configuration. In general, these restrictions are difficult to check in practice where mathematical models of plant are not available. In this paper, using a simple extension of the universal approximation theorem, we show that the only required constraint on the control gain is that its sign is known.

MSC : 93B52, 93C Citation: Kunting Yu, Yongming Li. Adaptive fuzzy control for nonlinear systems with sampled data and time-varying input delay[J]. AIMS Mathematics, , 5 3 : Article views PDF downloads Cited by 2. Figures

In this paper, control of uncertain fractional-order financial chaotic system with input saturation and external disturbance is investigated. To handle the fuzzy approximation error and the estimation error of the unknown upper bound of the external disturbance, fractional-order adaptation laws are constructed. Based on fractional Lyapunov stability theorem, an adaptive fuzzy controller is designed, and the asymptotical stability can be guaranteed. Finally, simulation studies are given to indicate the effectiveness of the proposed method. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Competing interests: The author has declared that no competing interests exist. Thirty years ago, Stutzer, an economist, first obtained the chaotic behavior in financial system [ 1 ].

Adaptive Fuzzy Systems And Control Design And Stability Analysis

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Li Xin Wang's Adaptive Fuzzy Systems and Control: Design and Stability Analysis

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