Swarm optimization tuned fuzzy sliding mode control design for a class of nonlinear systems in presence of uncertainties

Authors:
Mohammad Hassan Khooban;Mohammad Reza Soltanpour
Affiliations:
Department of Electrical and Robotic Engineering, Garmsar Branch Islamic Azad University of Iran, Garmsar, Iran;Department of Electrical Engineering, Aeronautical University of Science and Technology, Tehran, Iran
Venue:
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Computational intelligence models for image processing and information reasoning
Year:
2013

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Abstract

This paper provides an optimal controlling approach for a class of nonlinear systems with structured and unstructured uncertainties using fuzzy sliding mode control. First known dynamics of the system are eliminated through feedback linearization and then optimal fuzzy sliding mode controller is designed using an intelligent fuzzy controller based on Sugeno-Type structure. The proposed controller is optimized by a novel heuristic algorithm namely Particle Swarm Optimization with random inertia Weight RNW-PSO. In order to handle, the uncertainties Lyapunov method is used. There are no signs of the undesired chattering phenomenon in the proposed method. The globally asymptotic stability of the closed-loop system is mathematically proved. Finally, this control method is applied to the inverted pendulum system as a case study. Simulation results show desirability of the system performance.