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Y. J. Park, H. S. Cho and D. H. Cha, “Genetic AlgorithmBased Optimization of Fuzzy Logic Controller Using Characteristic Parameters,” IEEE International Conference on Evolutionary Computation, Taejon, Vol. 2, 1995, pp. 831-836.

has been cited by the following article:

• TITLE: Design of Fuzzy Controller for Robot Manipulators Using Bacterial Foraging Optimization Algorithm

  AUTHORS: Mickael Aghajarian, Kourosh Kiani, Mohammad Mehdi Fateh

  KEYWORDS: BFO Algorithm; PSO Algorithm; Fuzzy Control; Robot Manipulator; Tracking Control

  JOURNAL NAME: Journal of Intelligent Learning Systems and Applications, Vol.4 No.1, February 28, 2012

  ABSTRACT: Trial and error method can be used to find a suitable design of a fuzzy controller. However, there are many options including fuzzy rules, Membership Functions (MFs) and scaling factors to achieve a desired performance. An optimiza-tion algorithm facilitates this process and finds an optimal design to provide a desired performance. This paper presents a novel application of the Bacterial Foraging Optimization algorithm (BFO) to design a fuzzy controller for tracking control of a robot manipulator driven by permanent magnet DC motors. We use efficiently the BFO algorithm to form the rule base and MFs. The BFO algorithm is compared with a Particle Swarm Optimization algorithm (PSO). Performance of the controller in the joint space and in the Cartesian space is evaluated. Simulation results show superiority of the BFO algorithm to the PSO algorithm.