多变量非线性系统的有约束模糊预测解耦控制

Constrained fuzzy predictive control for multivariable nonlinear systems

针对多变量非线性系统提出了一种带约束输入的广义预测解耦控制算法:首先对多变量非线性系统建立T-S模糊模型,然后在每个采样点对系统进行局部动态线性化,将得到的系统线性化模型进行对角解耦,然后对其设计带输入约束的GPC算法.该算法充分考虑了控制输入及其增量受约束的情况,而且不必求Dio-phantine方程,减小了计算量,且削弱了变量之间的耦合程度.最后的仿真结果说明了该算法对多变量非线性系统的有效性.

A fuzzy generalized predictive decoupling control （GPC） with the input constraints is presented for the multivariable nonlinear systems. First, a T-S fuzzy model is built to approach the nonlinear system. And then the local dynamic linearization is applied to the system at each sampling point. Based on deeoupling diagonally this linearizing model into some single input singl output（ SISO） models, the GPC algorithm with input constraints is presented. This algorithm takes account of all the constraints of the control signals and their increments. It does not require solving the Diophantine equation, and needs only small computer memory. Furthermore it weakens the coupling of the variables. The simulation results show that this algorithm has superior performance for multivariable nonlinear systems.