scispace - formally typeset
Journal ArticleDOI

H/sup /spl infin// tracking design of uncertain nonlinear SISO systems: adaptive fuzzy approach

TLDR
Computer simulation results confirm that the effect of both the fuzzy approximation error and external disturbance on the tracking error can be attenuated efficiently by the proposed adaptive fuzzy control algorithm.
Abstract
A fuzzy logic controller equipped with a training (adaptive) algorithm is proposed in this work to achieve H/sup /spl infin// tracking performance for a class of uncertain (model free) nonlinear single-input single-output (SISO) systems with external disturbances. An attempt is also made to create a bridge between two important control design techniques, i.e., H/sup /spl infin// control design and fuzzy control design, so as to supply H/sup /spl infin// control design with more intelligence and fuzzy control design with better performance. The perfect matching of parameters in an adaptive fuzzy logic system is generally deemed impossible. Therefore, a desired tracking performance cannot be guaranteed in the conventional adaptive fuzzy control systems. In this study, the influence of both fuzzy logic approximation error and external disturbance on the tracking error is attenuated to a prescribed level. Both indirect and direct adaptive fuzzy controllers are employed to treat this H/sup /spl infin// tracking problem. The authors' results indicate that arbitrarily small attenuation level can be achieved via the proposed adaptive fuzzy control algorithm if a weighting factor of control variable is adequately chosen. The proposed design method is also useful for the robust tracking control design of the nonlinear systems with external disturbances and a large uncertainty or unknown variation in plant parameters and structures. Furthermore, only smooth control signals are needed via the proposed control designs. Two simulation examples are given finally to illustrate the performance of the proposed methods. Computer simulation results confirm that the effect of both the fuzzy approximation error and external disturbance on the tracking error can be attenuated efficiently by the proposed method.

read more

Citations
More filters
Journal ArticleDOI

A Survey on Analysis and Design of Model-Based Fuzzy Control Systems

TL;DR: A survey on recent developments (or state of the art) of analysis and design of model based fuzzy control systems based on the so-called Takagi-Sugeno fuzzy models or fuzzy dynamic models.
Journal ArticleDOI

Brief paper: Direct adaptive fuzzy control of nonlinear strict-feedback systems

TL;DR: This paper focuses on adaptive fuzzy tracking control for a class of uncertain single-input /single-output nonlinear strict-feedback systems and a novel direct adaptive fuzzy Tracking controller is constructed via backstepping.
Journal ArticleDOI

Fuzzy tracking control design for nonlinear dynamic systems via T-S fuzzy model

TL;DR: This study introduces a fuzzy control design method for nonlinear systems with a guaranteed H/sub /spl infin// model reference tracking performance using the Takagi and Sugeno (TS) fuzzy model to represent a nonlinear system.
Journal ArticleDOI

Mixed H/sub 2//H/sub /spl infin// fuzzy output feedback control design for nonlinear dynamic systems: an LMI approach

TL;DR: This study introduces a mixed H/sub 2//H/sub /spl infin// fuzzy output feedback control design method for nonlinear systems with guaranteed control performance using the Takagi-Sugeno fuzzy model to approximate a nonlinear system.
Journal ArticleDOI

Observer-based fuzzy adaptive control for strict-feedback nonlinear systems

TL;DR: It is proven that the proposed fuzzy adaptive control approach guarantees the semi-global boundedness property for all the signals and the tracking error to a small neighborhood of the origin.
References
More filters
Book

Fuzzy sets

TL;DR: A separation theorem for convex fuzzy sets is proved without requiring that the fuzzy sets be disjoint.
Book

Applied Nonlinear Control

TL;DR: Covers in a progressive fashion a number of analysis tools and design techniques directly applicable to nonlinear control problems in high performance systems (in aerospace, robotics and automotive areas).
Journal ArticleDOI

Fuzzy logic in control systems: fuzzy logic controller. II

TL;DR: The basic aspects of the FLC (fuzzy logic controller) decision-making logic are examined and several issues, including the definitions of a fuzzy implication, compositional operators, the interpretations of the sentence connectives 'and' and 'also', and fuzzy inference mechanisms, are investigated.
Journal ArticleDOI

State-space solutions to standard H/sub 2/ and H/sub infinity / control problems

TL;DR: In this article, simple state-space formulas are derived for all controllers solving the following standard H/sub infinity / problem: for a given number gamma > 0, find all controllers such that the H/ sub infinity / norm of the closed-loop transfer function is (strictly) less than gamma.
Book

Optimal Control: Linear Quadratic Methods

TL;DR: In this article, an augmented edition of a respected text teaches the reader how to use linear quadratic Gaussian methods effectively for the design of control systems, with step-by-step explanations that show clearly how to make practical use of the material.