基于可达集的鲁棒模型预测控制

A Robust Model Predictive Control Based on Reachable Sets

  • 摘要: 设计了一种基于可达集的鲁棒模型预测控制算法.首先确定了一个鲁棒不变集,并将此不变集用作模型预测控制的终端约束集:接着采用终端约束集对可达集的包含度作为优化指标;最后,采用预测时域逐渐减小的控制策略以保证在线优化存在可行解.从理论上证明了吸引域内的任意点在有限时域内都会被引导至终端约束集并始终停留在此集之内,并由仿真算例验证了本文所设计鲁棒模型预测控制算法的可行性.

     

    Abstract: A robust model predictive control(MPC) algorithm based on reachable sets is designed.Firstly,a robust invariant set is established and serves as the terminal constraint set for MPC;next,the inclusion degrees of reachable sets in terminal constraint set are used as optimization index;finally,the control strategy with gradually shortened predictive horizon is adopted to guarantee the existence of the feasible solution of online optimization.It is proved in theory that any point in the region of attraction will be led to the terminal constraint set in finite horizon and then stays in this set all the time.The simulation example verifies the feasibility of the robust MPC algorithm designed.

     

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