基于T-S模糊模型的直接自适应预测控制

摘要

提出一种基于T-S模糊模型的直接自适应预测控制算法.该算法利用加权递推最小二乘法在线辨识T-S模糊模型的后件参数.用已经辨识好的参数,进行直接迭代计算,直接得到模型的预测输出.此算法很好地解决了非线性预测控制中,建模与优化两大难题,为非线性系统的高精度控制提供了保证.计算机仿真表明,该算法具有较好的跟踪性能.%A direct adaptive predictive control based on T - S fuzzy model was proposed. The structure parameters of T - S fuzzy model were identified online using the weighted recursive least squares method. The identified parameters of fuzzy model were used to directly receive the model predicted output with direct iterative for the T-S model. The algorithm is a good way to resolve the two major problems, modeling and optimization, and provide a guarantee for high-precision control of nonlinear systems. Simulation result shows that the proposed algorithm is an effective control strategy with excellent tracing ability.