A fuzzy multiple reference model adaptive control scheme for flexible link robotic manipulator

Abstract

In this paper a novel fizy logic bused multiple reference model adaptive controller approach for the position control of a single link robotic manipulator is presented. The proposed fuzy logic scheme is used for generating multiple reference models, within the Model Reference Adaptive Control (MRAC)J?amework, in response to changes in modes of operation or modal swings due to manipulator tip load variation. Thus the scheme is utilized to generate dynamic reference model and the overall structure is coined as Fuzzy Multiple Reference Model Adaptive Controller (FM7LWC). Following a rule base the fu~y switching scheme effectively monitors changes in operating conditions due to tip load vnriation. A f i z z y inference engine then fires appropriate rules, which gives afuzzfied output value. Further defuzficarion is performed to switch the reference model in a predefined domain. The main contribution of the paper is that the proposed approach can be performed online and is very well suitable for plants showing sudden Yump' in operating conditions. Unlike, static multiple model algorithms for switching (noninteracting individual model-based filters) or switching dynamic algorithms (srrrceptible to numerical overflow), this scheme provides on interactive multiple model environment with soft swirching. l%is approach is found to be every effective and fault tolerant.

Study on Fuzzy Multiple Reference Model Adaptive Control Strategies

“…) where V(.) is fuzzy selection set function [9]; T fm represents a nonlinear mapping relationship between the fuzzy output and the reference model.…”

An intelligent paradigm for electric generator control based on supervisory loops

“…In this paper, a dynamic growing RBFNN [14]- [15] with a model reference adaptive controller for the control of nonlinear and changing systems is presented . Unlike the control schemes reported till now, the proposed scheme has mainly three advantages .…”

“…IEEE International Conference on Computational Intelligence for Measurements Systems and Applications, Boston USA July[14][15][16] 2004, pp.I74-179.…”