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

Abstract

In this paper a novel fuzzy logic based multiple reference model adaptive controller approach for the position control of a single link robotic manipulator is presented. The proposed fuzzy logic scheme is used for generating multiple reference models, within the model reference adaptive control (MRAC) framework, 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 (FMRMAC). Following a rule base the fuzzy switching scheme effectively monitors changes in operating conditions due to tip load variation. A fuzzy inference engine then fires appropriate rules, which gives a fuzzified output value. Further defuzzification 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 'jump' in operating conditions. Unlike, static multiple model algorithms for switching (noninteracting individual model-based filters) or switching dynamic algorithms (susceptible to numerical overflow), this scheme provides an interactive multiple model environment with soft switching. This approach is found to be every effective and fault tolerant.