Adaptive Fuzzy Control for a SISO Nonlinear System

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.

scholarly journals Adaptive Fuzzy Control for a Class of Nonlinear Systems with State Observer

2006 ◽  
Vol 10 (2) ◽  
pp. 225-233 ◽  
Author(s):  
Hugang Han ◽  
Keyword(s):  
Fuzzy Control ◽  
Fuzzy Controller ◽  
Tracking Error ◽  
Adaptive Fuzzy Control ◽  
State Observer ◽  
Switching Function ◽  
Adaptive Law ◽  
The Stability ◽  
Synthesis Approach ◽  
Real State

This paper addresses the fuzzy control problem using the Lyapunov synthesis approach. In order to deal with cases where the system state is unavailable, a state observer is proposed. Consequently, the whole system behavior can be attributed to a kind of standard singularly perturbed form. At the same time, to deal with the gap, if any, between the real state and its estimated value from the state observer, we view it as a part of system disturbance, and propose a unique way to deal with the disturbance, i.e., adopt a switching function with an alterable coefficient, which is tuned by adaptive law based on the tracking error between the output of the considered system and the desired value. Finally, it is shown that the fuzzy controller proposed guarantees the tracking error will shrink to zero, while maintaining the stability of all signals involved in the system.

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

2021 ◽  
Author(s):  
Shuzhen Diao ◽  
Wei Sun ◽  
Le Wang ◽  
Jing Wu
Keyword(s):  
Fuzzy Control ◽  
Finite Time ◽  
Fuzzy Systems ◽  
Tracking Error ◽  
Adaptive Fuzzy Control ◽  
Finite Time Stability ◽  
Adaptive Fuzzy ◽  
Intermediate Variable ◽  
Control Scheme ◽  
Theoretical Results

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.

scholarly journals Flatness-Based Adaptive Fuzzy Control Of Spark-Ignited Engines

2014 ◽  
Vol 4 (4) ◽  
pp. 231-242 ◽  
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.

An adaptive fuzzy control system to maximize rough turning productivity and avoid the onset of instability

2010 ◽  
Vol 53 (1-4) ◽  
pp. 71-79 ◽  
Author(s):  
Juho Ratava ◽  
Mikko Rikkonen ◽  
Ville Ryynänen ◽  
Johanna Leppänen ◽  
Tuomo Lindh ◽  
...  
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Adaptive Fuzzy Control ◽  
Fuzzy Control System ◽  
Adaptive Fuzzy ◽  
Rough Turning

Application Research on H∞ Optimization Control of Permanent Magnet Linear Servo System Based on Adaptive Fuzzy Control Strategy

2013 ◽  
Vol 694-697 ◽  
pp. 2185-2189
Author(s):  
Xiao Ping Zhu ◽  
Xiu Ping Wang ◽  
Chun Yu Qu ◽  
Jun You Zhao
Keyword(s):  
Fuzzy Control ◽  
Control Strategy ◽  
Control Method ◽  
Fuzzy Controller ◽  
External Disturbance ◽  
Adaptive Fuzzy Control ◽  
Servo System ◽  
Robust Controller ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy

In order to against the uncertain disturbance of AC linear servo system, an H mixed sensitivity control method based on adaptive fuzzy control was putted forward in the paper. The controller is comprised of an adaptive fuzzy controller and a H robust controller, the adaptive fuzzy controller is used to approximate this ideal control law, H robust controller is designed for attenuating the approximation errors and the influence of the external disturbance. The experimental results show that this control strategy not only has a strong robustness to uncertainties of the linear system, but also has a good tracking performance, furthermore the control greatly improves the robust tracking precision of the direct drive linear servo system.

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