基于T-S模型的自适应模糊广义预测控制

对一类非线性系统，利用一种基于模糊规则的快速模糊辨识方法建立起系统的T—S模型，并基于该模型应用局部递推最小二乘方法根据采样值对模型参数进行在线修正，根据系统动态线性化模型采取广义预测控制策略，从而实现了基于T—S模糊模型的非线性系统自适应模糊预潮控制。与以往的模糊广义预测控制算法相比，此方法简单，而且较大地减少计算量，适合于在线控制。通过仿真研究验证所提方法的有效性。

Adaptive Fuzzy Generalized Predictive Control Based on T-S Model

A T-S fuzzy model was established for nonlinear system by a fast fuzzy identification method based on fuzzy logic rules. The model parameters were modified by local recursive least square method at sampling point. According to the dynamic linearization model of the T-S fuzzy model, an adaptive fuzzy generalized predictive controller was designed. Compared with previous fuzzy generalized predictive controllers, the proposed controller is simple, and can be applied on-line. The simulation results show that this method is effective.