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