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研究了工业生产过程存在着输入、输出软硬混合约束的优化控制技术。给出了基于约束的预测控制算法,提出了用动态优先级对有硬约束的操作变量进行在线协调,当协调过程找不到满足所有约束条件的可行解时,对被控变量进行约束软化,本文采取的线性和二次型相结合的惩罚函数对预测时域上每个时刻的激活值进行惩罚,不仅可以保证可行解的存在,而且能使系统处于动态和稳态的优化性能。
In this paper, the optimal control technology for the input and output mixed constraints of hardware and software exists in industrial production process. This paper presents a constraint-based predictive control algorithm. The paper proposes dynamic coordination of online hard-constrained operation variables with dynamic priority. When the coordination process can not find a feasible solution that satisfies all the constraints, the controlled variable is softened and constrained. The penalty function combined with linear and quadratic methods in this paper can not only ensure the existence of feasible solutions but also make the system be in dynamic and steady state optimization performance.