Open AccessModel-Based Evolution of a Fast Hybrid Fuzzy Adaptive Controller for a Pneumatic Muscle Actuator
Author(s) -
Alexander Hošovský,
Jozef Novák-Marcinčin,
Ján Piteľ,
Jana Boržíková,
Kamil Židek
Publication year - 2012
Publication title -
international journal of advanced robotic systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.394
H-Index - 46
eISSN - 1729-8814
pISSN - 1729-8806
DOI - 10.5772/50347
Subject(s) - control theory (sociology) , computer science , robustness (evolution) , fuzzy logic , pneumatic artificial muscles , controller (irrigation) , actuator , inertia , fuzzy control system , artificial muscle , nonlinear system , control engineering , artificial intelligence , control (management) , engineering , chemistry , physics , classical mechanics , quantum mechanics , biochemistry , biology , agronomy , gene
Pneumatic artificial muscle-based robotic systems usually necessitate the use of various nonlinear control techniques in order to improve their performance. Their robustness to parameter variation, which is generally difficult to predict, should also be tested. Here a fast hybrid adaptive control is proposed, where a conventional PD controller is placed into the feedforward branch and a fuzzy controller is placed into the adaptation branch. The fuzzy controller compensates for the actions of the PD controller under conditions of inertia moment variation. The fuzzy controller of Takagi-Sugeno type is evolved through a genetic algorithm using the dynamic model of a pneumatic muscle actuator. The results confirm the capability of the designed system to provide robust performance under the conditions of varying inertia
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