Finite-Time Adaptive Fuzzy Control for Nonlinear Systems with Unknown Backlash-Like Hysteresis

AbstractThis study considers the tracking control problem of the nonstrict-feedback nonlinear system with unknown backlash-like hysteresis, and a finite-time adaptive fuzzy control scheme is developed to address this problem. More precisely, the fuzzy systems are employed to approximate the unknown nonlinearities, and the design difficulties caused by the nonlower triangular structure are also overcome by using the property of fuzzy systems. Besides, the effect of unknown hysteresis input is compensated by approximating an intermediate variable. With the aid of finite-time stability theory, the proposed control algorithm could guarantee that the tracking error converges to a smaller region. Finally, a simulation example is provided to further verify the above theoretical results.

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Adaptive Fuzzy Control for a SISO Nonlinear System

Journal of Advanced Computational Intelligence and Intelligent Informatics ◽

10.20965/jaciii.2003.p0086 ◽

2003 ◽

Vol 7 (2) ◽

pp. 86-91

Author(s):

Hugang Han ◽

◽

Shuta Murakami ◽

Keyword(s):

Control System ◽

Fuzzy Control ◽

Fuzzy Systems ◽

Fuzzy Controller ◽

Tracking Error ◽

Adaptive Fuzzy Control ◽

Switching Function ◽

Adaptive Fuzzy ◽

Synthesis Approach ◽

Unknown Case

When using the Lyapunov synthesis approach to construct an adaptive fuzzy control system, one important way is to regard the fuzzy systems as approximators to approximate the unknown functions in the system to be controlled. Concerning the unknownness, generally there are two cases: a completely unknown case, and a partly unknown case. However, most of the schemes presented so far have only focused on the former. Clearly, if an unknown function belongs to the latter, the knowledge available about the function should be utilized as much as possible in the development of the control system. In this paper, our goal is to design an adaptive fuzzy controller for a class of nonlinear systems with uncertainty, which can correspond to the either case. Also, we propose a unique way to deal with the uncertainty, i.e., adopt a switching function with an alterable coefficient, which is tuned by adaptive law based on the tracking error.

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Flatness-Based Adaptive Fuzzy Control Of Spark-Ignited Engines

Journal of Artificial Intelligence and Soft Computing Research ◽

10.1515/jaiscr-2015-0011 ◽

2014 ◽

Vol 4 (4) ◽

pp. 231-242 ◽

Cited By ~ 6

Author(s):

Gerasimos G. Rigatos ◽

P. Siano

Keyword(s):

Fuzzy Control ◽

Fuzzy Controller ◽

Tracking Error ◽

Adaptive Fuzzy Control ◽

Performance Criterion ◽

Tracking Performance ◽

System Stability ◽

Adaptive Fuzzy ◽

Neuro Fuzzy ◽

Control Scheme

Abstract An adaptive fuzzy controller is designed for spark-ignited (SI) engines, under the constraint that the system's model is unknown. The control algorithm aims at satisfying the H∞ tracking performance criterion, which means that the influence of the modeling errors and the external disturbances on the tracking error is attenuated to an arbitrary desirable level. After transforming the SI-engine model into the canonical form, the resulting control inputs are shown to contain nonlinear elements which depend on the system's parameters. The nonlinear terms which appear in the control inputs are approximated with the use of neuro-fuzzy networks. It is shown that a suitable learning law can be defined for the aforementioned neuro-fuzzy approximators so as to preserve the closed-loop system stability. With the use of Lyapunov stability analysis it is proven that the proposed adaptive fuzzy control scheme results in H∞ tracking performance. The efficiency of the proposed adaptive fuzzy control scheme is checked through simulation experiments.

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Adaptive Fuzzy Control for Stochastic Pure-Feedback Nonlinear Systems with Unknown Hysteresis and External Disturbance

Complexity ◽

10.1155/2018/1487134 ◽

2018 ◽

Vol 2018 ◽

pp. 1-11

Author(s):

Xikui Liu ◽

Yingying Ge ◽

Yan Li

Keyword(s):

Nonlinear Systems ◽

Fuzzy Control ◽

External Disturbance ◽

Tracking Error ◽

Adaptive Fuzzy Control ◽

Nonlinear Function ◽

Small Neighborhood ◽

Mean Value Theorem ◽

Adaptive Fuzzy ◽

Control Scheme

This paper solves the tracking control problem of a class of stochastic pure-feedback nonlinear systems with external disturbances and unknown hysteresis. By using the mean-value theorem, the problem of pure-feedback nonlinear function is solved. The direction-unknown hysteresis problem is solved with the aid of the Nussbaum function. The external disturbance problems can be solved by defining new Lyapunov functions. Using the backstepping technique, a new adaptive fuzzy control scheme is proposed. The results show that the proposed control scheme ensures that all signals of the closed-loop system are semiglobally uniformly bounded and the tracking error converges to the small neighborhood of origin in the sense of mean quartic value. Simulation results illustrate the effectiveness of the proposed control scheme.

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