Autogeneration of Fuzzy Logic Rule-Base Controllers

Abstract:

A novel Fuzzy Logic controller design methodology is presented. The method utilizes a Particle Swarm Optimization (PSO) binary search algorithm to generate the rules for the Fuzzy Logic controller rule-base stage without human experience intervention. The proposed technique is compared with the well established Lyapunov based Fuzzy Logic controller design in generating the rules. Finally, the controller’s effectiveness and performance are tested, verified and validated using an elevator control application. The novel controller’s results are to be compared with traditional Proportional Integral Derivative (PID) controller and classical Fuzzy Logic (FL) controllers.

• Periodical: Applied Mechanics and Materials (Volumes 110-116)
• Pages: 5123-5130
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.110-116.5123
• Online since: October 2011
• Authors: M. O. Abdalla, T.A. Al–Jarrah
• Keywords: Binary Search, Fuzzy Logic Controller, Particle Swarm Optimization Algorithm (PSO), Rule-Base Generation

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