Improved Control for Industrial Systems Over Model Uncertainty: A Receding Horizon Expanded State Space Control Approach
提出一种基于滚动时域扩展状态空间模型的线性二次跟踪控制策略，通过结合系统状态变量与跟踪误差，增加控制参数调节自由度，在典型逆过程仿真中相比传统方法提升了伺服与调节性能。
In this paper, an improved linear quadratic tracking control strategy using a new receding horizon expanded state space (ESS) model is proposed. Unlike traditional state space model, the new ESS model first facilitates the combination of the system state variables and tracking errors, then a subsequent new receding horizon improved linear quadratic tracking control (RHLQTC) is designed with more degrees of freedoms for the adjustment of control parameters, which yields improved control performance compared with traditional RHLQTC. Finally, simulations on a typical reverse process are done in comparison with traditional RHLQTC in terms of both servo and regulatory performance, where results show that the proposed controller provides improved performance under both situations.