TLBO-Based Optimal Speed Controller Design for Induction Motors Using Fuzzy Sliding Mode Controller

Abstract

Teaching-Learning-Based Optimization (TLBO) algorithm is a new optimization technique which has been shown to be competitive to other population-based algorithms. In this paper, TLBO algorithm is employed for speed control of induction motor based on Fuzzy Sliding Mode Controller (FSMC). The proposed control method, namely Optimal Fuzzy SMC (OFSMC), formulates the design of FSMC as an optimization problem. First, a sliding mode speed controller with an integral switching surface is designed, in which the acceleration information for speed control is not required. In this case, the upper bound of the lumped uncertainties including parameter uncertainties and load disturbance must be available. The importance of this parameter regarding the system performance is illustrated. Then, the fuzzy sliding mode speed controller is utilized to estimate the upper bound of the lumped uncertainties. Finally, TLBO algorithm is employed to determine the optimal upper bound of these uncertainties. Simulation results are included to demonstrate that the proposed OFSMC can obtain better quality solution than many existing techniques like Proportional-Integrator (PI), SMC, FSMC and an Adaptive FSMC (AFSMC).