On-line Adaptive Interval Type-2 Fuzzy Controller Design via Stable SPSA Learning Mechanism

Ching-Hung Lee ； Feng-Yu Chang ； Chih-Min Lin

《International Journal of Fuzzy Systems》 14卷4期 (2012/12) Pp. 489-500

https://doi.org/10.30000/IJFS.201212.0003

並列摘要

This paper proposes an interval type-2 Takagi-Sugeno-Kang fuzzy neural system (IT2TFNS) to develop an on-line adaptive controller using stable simultaneous perturbation stochastic approximation (SPSA) algorithm. The proposed IT2TFNS realizes an interval type-2 TSK fuzzy logic system formed by the neural network structure. Differ from the most of interval type-2 fuzzy systems, the type-reduction of the proposed IT2TFNS is embedded in the network by using uncertainty bounds method such that the time-consuming Karnik-Mendel (KM) algorithm is replaced. The proposed stable SPSA algorithm provides the gradient free property and faster convergence. However, the stable SPSA algorithm inherently has the problem for on-line adaptive control. Hence, in order to achieve the on-line result, we utilize the sliding surface to develop a new on-line adaptive control scheme. In addition, the corresponding stable learning is derived by Lyapunov theorem which guarantees the convergence and stability of the closed-loop systems. Simulation and comparison results are shown to demonstrate the performance and effectiveness of our approach.

並列關鍵字

interval type-2 fuzzy neural system ； uncertainty bounds ； simultaneous perturbation stochastic approximation algorithm ； Lyapunov theorem ； on-line control