具记忆状态反馈的输入受限时滞系统模型预测控制器

针对一类具有输入约束的离散线性不确定时滞系统,提出了一种具有记忆状态反馈的模型预测控制器.首先,定义时滞系统的鲁棒性能指标,在考虑时滞状态影响的条件下设计了包含时滞状态的记忆状态反馈控制律,在线优化时将当前控制量作为独立优化变量,与其它作为反馈控制的时域控制序列分开处理,以降低算法保守性,提高可行性.然后,给出了基于线性矩阵不等式凸优化的控制策略以及系统稳定的充分条件.最后,通过仿真实验验证了该控制算法的有效性.

Memory State Feedback-Based Model Predictive Controller of Time-Delay Systems with Input Constraints

Proposed in this paper is a model predictive controller(MPC) based on the memory state feedback,which is developed for discrete-time uncertain linear time-delay systems with input constraints.In this MPC,a robust performance index is defined,and the feedback control law with time-delay state is presented by taking into consideration the influence of time-delay state.During the online optimization,the current control variable is taken as an independent decision variable and is separated from the rest of the control variables governed by the feedback law.Thus,the conservatism of the algorithm is deduced and the feasibility of the algorithm is improved.Moreover,the control strategy of the convex optimization based on the linear matrix inequality and the sufficient condition of system stability are presented,and a simulation is finally performed to verify the effectiveness of the proposed algorithm.