Design of the Fuzzy Control Systems Based on Genetic Algorithm for Intelligent Robots

• Published in: Interdisciplinary Description of Complex Systems Vol. 12; no. 3; pp. 245 - 254
• Main Author: Mester, Gyula
• Format: Journal Article Paper
• Language: English
• Published: Zagreb Croatian Interdisciplinary Society 01.01.2014; Hrvatsko interdisciplinarno društvo
• Subjects: 4 DOF SCARA robot; Adaptability; Computer simulation; Control systems; Control systems design; Fuzzy control; fuzzy controller; Fuzzy logic; Fuzzy sets; Fuzzy systems; genetic algorithm; Genetic algorithms; MATLAB environment; Optimization; Robot control; Robots; Scaling; Scaling factors; structure optimization
• ISSN: 1334-4684; 1334-4676
• DOI: 10.7906/indecs.12.3.4

This paper gives the structure optimization of fuzzy control systems based on genetic algorithm in the MATLAB environment. The genetic algorithm is a powerful tool for structure optimization of the fuzzy controllers, therefore, in this paper, integration and synthesis of fuzzy logic and genetic algorithm has been proposed. The genetic algorithms are applied for fuzzy rules set, scaling factors and membership functions optimization. The fuzzy control structure initial consist of the 3 membership functions and 9 rules and after the optimization it is enough for the 4 DOF SCARA Robot control to compensate for structured and unstructured uncertainty. Fuzzy controller with the generalized bell membership functions can provide better dynamic performance of the robot then with the triangular membership functions. The proposed joint-space controller is computationally simple and had adaptability to a sudden change in the dynamics of the robot. Results of the computer simulation applied to the 4 DOF SCARA Robot show the validity of the proposed method.