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针对传统的区间模型预测控制算法的性能指标函数设计复杂,以及被控变量进入区间后稳态轨迹变化幅度大的缺点,提出一种区间特性和变量软约束的模型预测控制算法.该算法仅利用期望输出区间的上下限,通过预测输出与区间的等式关系构造区间跟踪偏差项,同时利用预测输出和操作变量的增量二次型构造变量软约束项,减小区间内的稳态轨迹的变化幅度,上述两项合称为软约束区间跟踪性能指标项.以回转窑模型为被控对象进行仿真,表明了算法的有效性.
In view of the complex design of the performance index function of the traditional interval model predictive control algorithm and the large variation range of the steady-state trajectory after the controlled variable enters the interval, a model predictive control algorithm with interval characteristics and soft-constraint variables is proposed. Expect the upper and lower limits of the output interval, construct the interval tracking deviation term by the predictive output and the equation of the interval, and use the incremental quadratic type construction variable soft constraint term of the forecast output and manipulated variable to reduce the steady-state trajectory in the interval The amplitude of the change, the above two items are called soft constraint interval tracking performance index item.With rotary kiln model as the controlled object simulation, shows the effectiveness of the algorithm.