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.

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 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.

scholarly journals Novel Approach to Direct Adaptive Fuzzy Control Applied to the Asynchronous Machine

2015 ◽  
Vol 55 ◽  
pp. 136-149
Author(s):  
M. Fodil ◽  
S. Barkat ◽  
B.D. Boukhetala
Keyword(s):  
Fuzzy Control ◽  
Fuzzy System ◽  
Tracking Error ◽  
Adaptive Fuzzy Control ◽  
Asynchronous Machine ◽  
Adaptive Fuzzy ◽  
Novel Approach ◽  
The Stability ◽  
Adaptation Law ◽  
Direct Adaptive Fuzzy Control

This paper presents an advanced direct adaptive fuzzy control for asynchronous machine which uses the theory of approximation and the theory of Lyapunov to establish a parametric adaptation law ensuring the stability and boundedness of all the control signals and the tracking error. In the direct approach, the fuzzy system is used to describe directly the control law and the parameters of the fuzzy system are directly adjusted to achieve the control objectives. Through the obtained results, stable direct adaptive fuzzy control generalized has proved a great effectiveness and a strong robustness in the presence of parameter variations and disturbances.

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.

Energy Management System Optimal Strategy for Pure Electric Vehicle Based on the Dynamic Programming

2014 ◽  
Vol 556-562 ◽  
pp. 1472-1475 ◽  
Author(s):  
Bing Dong ◽  
Yan Tao Tian ◽  
Chang Jiu Zhou
Keyword(s):  
Dynamic Programming ◽  
Fuzzy Control ◽  
Electric Vehicle ◽  
Energy Management ◽  
Management System ◽  
Control Method ◽  
Fuzzy Controller ◽  
Adaptive Fuzzy Control ◽  
Energy Management System ◽  
Fuzzy Control Strategy

This thesis puts forward one optimal adaptive fuzzy control method based on the pure electric vehicle energy management system of the fuzzy control which has been founded already. By adding an optimizing researching model based on the conventional fuzzy control strategy, the thesis can pick up the valuable control rules based on the dynamic programming theory and also can adjust the parameter of the fuzzy controller automatically according to the system operating. These can make the sum of the energy loss reduce to the min. The experiment points out that this method makes the vehicle possess good economic performance in the same driving cycle.

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.

scholarly journals Optimal Robust Adaptive FuzzyH∞Tracking Control without Reaching Phase for Nonlinear System

2013 ◽  
Vol 2013 ◽  
pp. 1-7
Author(s):  
El Mehdi Mellouli ◽  
Siham Massou ◽  
Ismail Boumhidi
Keyword(s):  
Fuzzy Controller ◽  
Tracking Error ◽  
Gain Control ◽  
High Gain ◽  
Control Input ◽  
Optimal Value ◽  
Robust Adaptive ◽  
Indirect Adaptive Fuzzy Controller ◽  
The Stability ◽  
Interval Type

An optimalH∞tracking-based indirect adaptive fuzzy controller for a class of perturbed uncertain affine nonlinear systems without reaching phase is being developed in this paper. First a practical Interval Type-2 (IT2) fuzzy system is used in an adaptive scheme to approximate the system using a nonlinear model and to determine the optimal value of theH∞gain control. Secondly, to eliminate the trade-off betweenH∞tracking performance and high gain at the control input, a modified output tracking error has been used. The stability is ensured through Lyapunov synthesis and the effectiveness of the proposed method is proved and the simulation is also given to illustrate the superiority of the proposed approach.

Backstepping Adaptive Fuzzy Control for Permanent Magnet Synchronous Motor Servo Systems

2012 ◽  
Vol 591-593 ◽  
pp. 1483-1489 ◽  
Author(s):  
Ren Hui Du ◽  
Yi Fei Wu ◽  
Wei Chen ◽  
Qing Wei Chen
Keyword(s):  
Fuzzy Control ◽  
Permanent Magnet ◽  
Permanent Magnet Synchronous Motor ◽  
Tracking Error ◽  
Adaptive Fuzzy Control ◽  
Synchronous Motor ◽  
Position Tracking ◽  
Servo Systems ◽  
Nonlinear Part ◽  
Adaptive Fuzzy

An adaptive fuzzy controller based on the backstepping method is developed for permanent magnet synchronous motor (PMSM) servo systems with unknown parameters, nonlinear friction and other load torque disturbances. The adaptive fuzzy logic system is used to approximate the nonlinear part of the system online, which can eliminate the influence of uncertainties and nonlinear factors effectively and realize the high-precision position tracking. By adopting the Lyapunov method, it is proved that the position tracking error converges exponentially. Compared with the traditional backstepping adaptive control (BAC), the simulation results show that the backstepping adaptive fuzzy control (BAFC) has better robustness and accuracy.

scholarly journals Observer-Based Robust Adaptive Fuzzy Control for MIMO Nonlinear Uncertain Systems with Delayed Output

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Chiang Cheng Chiang
Keyword(s):  
Nonlinear System ◽  
Fuzzy Control ◽  
Robust Stability ◽  
Uncertain Systems ◽  
Fuzzy Controller ◽  
Adaptive Fuzzy Control ◽  
Controlled System ◽  
Adaptive Fuzzy ◽  
Nonlinear Uncertain Systems ◽  
Robust Adaptive

An observer-based robust adaptive fuzzy control scheme is presented to tackle the problem of the robust stability and the tracking control for a class of multiinput multioutput (MIMO) nonlinear uncertain systems with delayed output. Because the nonlinear system functions and the uncertainties of the controlled system including structural uncertainties are supposed to be unknown, fuzzy logic systems are utilized to approximate these nonlinear system functions and the upper bounded functions of the uncertainties. Moreover, the upper bound of uncertainties caused by these fuzzy modeling errors is also estimated. In addition, the state observer based on state variable filters is designed to estimate all states which are not available for measurement in the controlled system. By constructing an appropriate Lyapunov function and using strictly positive-real (SPR) stability theorem, the proposed robust adaptive fuzzy controller not only guarantees the robust stability of a class of multivariable nonlinear uncertain systems with delayed output but also maintains a good tracking performance. Finally, some simulation results are illustrated to verify the effectiveness of the proposed control approach.

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