Optimization of Membership Functions for an Indirect Adaptive Interval Type-2 Fuzzy Sliding Mode Control using Particle Swarm
نویسنده
چکیده
Here, an Indirect Adaptive Interval Type-2 Fuzzy Sliding Mode Control (AIT2FSMC) is introduced for a class of nonlinear systems. In order to approximate unknown nonlinear functions, interval type-2 fuzzy logic system (IT2FLS) can be useful in presence of noisy data and external disturbances. Since, adjusting the interval type-2 fuzzy Membership Functions (MFs) to improve performance is a difficult task, we need a method to optimize the MFs. In this study, the MFs are optimized using Particle Swarm Optimization (PSO) that is a population based continues optimization method. The interval type-2 adaptation laws are derived using Lyapunov approach, and mathematical analysis proves the closed loop system to be asymptotically stable. Two examples of nonlinear system simulations investigate the effectiveness of the proposed optimization method and the merits of proposed optimized AIT2FSMC are presented.
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