双层结构模型预测控制算法性能分析

双层结构模型预测控制是在常规模型预测控制的基础上集成了稳态目标计算层,所增加稳态目标计算层通过对给定外部目标进行调节或执行独立经济优化为底层动态控制提供设定值.本文着重于分析增加稳态目标计算层对常规模型预测控制策略在控制性能、经济性能、及鲁棒性方面的影响.阐明稳态目标计算是在动态不确定性下的最优决策过程,可实时考虑当前工况环境给出最佳设定值,使动态层控制量的计算更加合理,并可保证在动态控制层实现无静差控制;稳态目标计算层可利用包含目标跟踪和经济优化的性能指标,在保证跟踪控制要求的同时利用操作自由度进行经济性优化,有助于提高系统经济性能,此外由于操作自由度增加使得系统对于特定方向的扰动和通道失配具有更强的鲁棒性.最后通过实验仿真验证了所做分析的正确性.

Performance analysis of double-layered model predictive control algorithm

Double-layered structure model predictive control strategy adopted by the current mainstream industrial process predictive control software (eg: DMCplus, RMPCT. et al), but lack of deep research in theoretical level. This paper focuses on the analysis of the effects on the control performance, economic performance and robustness of adding a steady-state target calculation layer on conventional single model predictive control strategies. It is clarified that the steady-state target calculation is the optimal decision under dynamic uncertainty, which can give the real-time optimal setting value under the current working condition and prove that the offset-free control can be realized under constant disturbance. In addition, the steady-state target calculation layer can make use of the degree of freedom to optimize the economy while ensuring the tracking control of important variables, which not only helps to improve the economic performance of the system, but also helps to make the system more robust to perturbations and channel mismatches in specific directions. Finally, the correctness of the analysis is verified by simulation.