JILSA  Vol.4 No.1 , February 2012
Design of Fuzzy Controller for Robot Manipulators Using Bacterial Foraging Optimization Algorithm
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.

Cite this paper
M. Aghajarian, K. Kiani and M. Fateh, "Design of Fuzzy Controller for Robot Manipulators Using Bacterial Foraging Optimization Algorithm," Journal of Intelligent Learning Systems and Applications, Vol. 4 No. 1, 2012, pp. 53-58. doi: 10.4236/jilsa.2012.41005.
[1]   K. H. Ang, G. Chong and Y. Li, “PID Control System Analysis, Design, and Technology,” IEEE Transactions on Control Systems Technology, Singapore, Vol. 13, No. 4, 2005, pp. 559-576. doi:10.1109/TCST.2005.847331

[2]   T. H. Kim, I. Maruta and T. Sugie, “Robust PID Controller Tuning Based on the Constrained Particle Swarm Optimization,” Automatica, Vol. 44, No. 4, 2008, pp. 11041110. doi:10.1016/j.automatica.2007.08.017

[3]   L. X. Wang, “A Course in Fuzzy Systems and Control,” Prentice Hall, New York, 1996.

[4]   M. M. Fateh, “Robust Fuzzy Control of Electrical Manipulators,” Journal of Intelligent and Robotic Systems, Vol. 60, No. 3-4, 2010, pp. 415-434. doi:10.1007/s10846-010-9430-y

[5]   K. M. Passino, “Biomimicry of Bacterial Foraging for Distributed Optimization and Control,” IEEE Control Systems Magazine, Columbus, Vol. 22, No. 3, 2002, pp. 52-67. doi:10.1109/MCS.2002.1004010

[6]   J. Kennedy and R. Eberhart, “Particle Swarm Optimization,” IEEE International Conference on Neural Networks, Vol. 4, Perth, 27 November-1 December 1995, pp. 1942-1948. doi:10.1109/ICNN.1995.488968

[7]   M. Dorigo and T. Stutzle, “Ant Colony Optimization,” MIT Press, Cambridge, 2004. doi:10.1007/b99492

[8]   M. Tripathy and S. Mishra, “Bacteria Foraging-Based to Optimize Both Real Power Loss and Voltage Stability Limit,” IEEE Transactions on Power Systems, Vol. 22, No. 1, 2007, pp. 240-248. doi:10.1109/TPWRS.2006.887968

[9]   M. A. Munoz, J. A. Lopez and E. Caicedo, “Bacteria Swarm Foraging Optimization for Dynamical Resource Allocation in A Multizone Temperature Experimentation Platform,” Analysis and Design of Intelligent Systems using Soft Computing Techniques, Advances in Intelligent and Soft Computing, Vol. 41, 2007, pp. 427-435.

[10]   H. Shen, Y. Zhu, X. Zhou, H. Guo and C. Chang, “Bacterial Foraging Optimization Algorithm with Particle Swarm Optimization Strategy for Global Numerical Optimization,” Proceedings of the First ACM/SIGEVO Summit on Genetic and Evolutionary Computation, Shanghai, June 2009, pp. 497-504.

[11]   D. H. Kim, A. Abraham and J. H. Cho, “A Hybrid Genetic Algorithm and Bacterial Foraging Approach for Global Optimization,” Information Sciences, Vol. 177, No. 18, 2007, pp. 3918-3937. doi:10.1016/j.ins.2007.04.002

[12]   T. J. Su, G. Y. Chen, J. C. Cheng and C. J. Yu, “Fuzzy PID Controller Design Using Synchronous Bacterial Foraging Optimization,” 3rd International Conference on Information Sciences and Interaction Sciences, Kaohsiung, June 2010, pp. 639-642.

[13]   A. Biswas, S. Dasgupta, S. Das and A. Abraham, “Synergy of PSO and Bacterial Foraging Optimization: A Comparative Study on Numerical Benchmarks,” Innovations in Hybrid Intelligent Systems, Advances in Intelligent and Soft Computing, Vol. 44, 2007, pp. 255-263. doi:10.1007/978-3-540-74972-1_34

[14]   M. Clerc and J. Kennedy, “The Particle Swarm-Explosion, Stability and Convergence in A Multidimensional Complex Space,” IEEE Transactions on Evolutionary Computation, Vol. 6, No. 1, 2002, pp. 58-73. doi:10.1109/4235.985692

[15]   M. M. Fateh, “Proper Uncertainty Bound Parameter to Robust Control of Electrical Manipulators Using Nominal Model,” Nonlinear Dynamics, Vol. 61, No. 4, 2010, pp. 655-666. doi:10.1007/s11071-010-9677-7

[16]   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.