一种基于T-S模糊模型的自适应预测函数控制

Adaptive Predictive Functional Control Based on T-S Fuzzy Model

针对离散时间非线性系统,提出了一种基于T-S模糊模型的自适应预测函数控制算法。该算法利用加权递推最小二乘法在线辨识T-S模糊模型后件参数,以克服模型失配对系统性能的影响。根据辨识得到的模型参数直接递推计算模型的预测输出,而不需要求解Dio-phantine方程,进而直接递推求解预测控制律,而不需要求解矩阵逆。仿真结果表明,该算法具有良好的跟踪性能和较强的鲁棒性。

An adaptive predictive functional control algorithm based on T-S fuzzy model is proposed for discrete-time nonlinear systems. In this algorithm the consequent parameters of T-S fuzzy model are identified by the weighting recursive least square method in order to overcome the influence of model mismatch on the system performance. Parameters of fuzzy model are used to directively recursively compute the model prediction output without solving Diophantine functions. Direct solution of predictive control input is received. Simulation result shows that the proposed algorithm is an effective control strategy with excellent tracing ability and strong robustness.