基于多优先级稳态优化的双层结构预测控制算法及软件实现

The Algorithm and Software Implementation for Double-layered Model Predictive Control Based on Multi-priority Rank Steady-state Optimization

研究包含稳态目标计算(Steady-state target calculation,SSTC)层和动态控制层的双层结构预测控制(Model predictive control,MPC)及其实现方法.我们将已有的辨识、优化和控制方案适当地组合并软件化.通过在多优先级稳态目标计算中引入新的变量,给出了稳态目标计算的统一表达方法,每个优先级的优化问题或是跟踪外部目标,或是放松软约束.通过仿真算例和应用实例相结合的方式验证了软件功能.

This paper studies the model predictive control （MPC） with multi-priority rank steady-state target calculation （SSTC） and dynamic control, and its implementation method. We properly combine the methods of identification, optimization and control in the existing literature, and implement these methods by software. By introducing new variables, the SSTC can be represented in a unified method, and the optimization problem in each priority rank is either the external target tracking or the soft constraints softening. We verify the software functions of the multi-priority rank SSTC via simulation and application examples.