针对TS模糊系统,提出一种基于模糊李亚普诺夫函数的稳定预测控制方法,通过构造模糊李普诺夫函数并最小化预测控制中无穷时域或拟无穷时域性能指标的上界,来设计满足系统闭环稳定、输入约束以及控制性能最优的平行分配补偿控制律。该控制律最终归结为求解一组线性矩阵不等式约束下的凸优化问题。模糊李亚普诺夫函数的使用减少了公共李亚普诺夫函数及分段李亚普诺夫函数的保守性,增加了可行解的范围。数值仿真和火电厂非线性机炉协调系统中的仿真试验,证明了这种方法的优越性和有效性。
A stable model predictive control based on fuzzy Lyapunov function and TS fuzzy model was proposed. The main idea of the proposed approach is to design a parallel distributed compensate control law in such a way that a fuzzy Lyapunov function is constructed with minimizing the upper bound of the infinite or quasi-infinite objective function in the fuzzy model predictive control. Therefore, the predictive controller can guarantee both the stability of the closed-loop fuzzy model predictive control system and input constraints while obtaining the optimal transient performance. It is shown that the controller is obtained by solving a set of linear matrix inequalities. Fuzzy Lyapunov function reduces the conservatism of common Lyapunov function and piecewise Lyapunov function, it enlarges the feasible area of the predictive controller. The simulations on numerical example and nonlinear boiler-turbine coordinated system of unit power plant demonstrate the advantage and effectiveness of the proposed methodology.