基于T-S模型的稳定自适应FNN控制器的设计

DESIGN OF STABLE ADAPTIVE FNN CONTROLLER USING T-S MODEL

对一类不确定非线性系统 ,提出一种基于 T- S模型的自适应 FNN控制器 .首先用权值固定的 FNN作为非线性系统的近似模型 ,然后再应用自适应 FNN逼近建模误差 ,并引入滑模项增加控制器的鲁棒性 .通过稳定性理论设计自适应律 ,保证了系统的全局稳定 。

An adaptive FNN control scheme for a class of unknown nonlinear systems is presented, which is based on multi-dimensional fuzzy inference model proposed by Takagi and Sugeno. The control architecture first employs two fixed structural FNNs to approximate plant uncertainties, then uses additional parallel adaptive FFNs to compensate for the modeling errors. A sliding mode term is introduced to improve robustness. Based on the Lyapunov theory, the adaptation laws to tune on-line both the membership functions and weighting factors are derived. Therefore, the closed-loop system is stable with the tracking error converging to zero.