基于Anytime算法的模型预测控制器的优化反馈调度

模型预测控制器可以实现为具有Anytime算法特征的模型预测控制（MPC）任务，它允许在执行时间和控制性能之间进行折衷．文中针对一组MPC任务，提出一种优化反馈调度算法（FS-CBS），在有限处理器时间约束范围内使全局控制性能最大化．该算法为每个MPC任务分配了一个恒定带宽服务器（CBS），并对CBS所预定的处理器时间进行动态调节，同时通过约束条件保证整个任务集的可调度性和各组分的稳定性．仿真结果表明，该算法对MPC运行时的执行时间变化不敏感，明显优于基本的CBS算法．

Optimal Feedback Scheduling Based on Anytime Algorithm for Model Predictive Controllers

A model predictive controller can be implemented as a MPC(Model Predictive Control) task with the characteristics of the Anytime algorithm,which allows the computation time to be traded for control performance. This paper presents an optimal feedback scheduling(FS-CBS) algorithm for a set of MPC tasks to maximize the global control performance subjected to limited processor time.Each MPC task is assigned with a CBS(Constant Bandwidth Server), whose reserved processor time is dynamically adjusted.The constraints in the FS-CBS algorithm guarantee the schedulability of the total task set and the stability of each component.Simulated results indicate that the optimal scheduling algorithm is robust against the variation of execution time of MPC tasks at runtime,and that it performs much better than the basic CBS algorithm.