A Computationally Efficient LQR based Model Predictive Control Scheme for Discrete-Time Switched Linear Systems

Midhun T. Augustine, Deepak U. Patil
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Abstract

This paper studies the optimal control problem for discrete-time switched linear systems with quadratic cost. A model predictive control (MPC) scheme is proposed which results in closed-loop strategies for both switching and control inputs. To reduce the online computation and ensure stability of the MPC scheme, a two-stage pruning algorithm is constructed which is performed offline. The resulting MPC scheme ensures exponential stability, and the cost function is suboptimal. Stability, feasibility, and suboptimality of the MPC scheme are studied. Simulation results are given for the MPC scheme which shows the proposed approach results in reduced computation and acceptable performance.
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一种计算效率高的离散时间切换线性系统LQR模型预测控制方法
研究具有二次代价的离散时间切换线性系统的最优控制问题。提出了一种模型预测控制(MPC)方案,实现了开关输入和控制输入的闭环控制策略。为了减少在线计算量,保证MPC方案的稳定性,构造了一种离线执行的两阶段剪枝算法。所得到的MPC方案保证了指数稳定性,而代价函数是次优的。研究了MPC方案的稳定性、可行性和次优性。最后给出了MPC方案的仿真结果,结果表明该方案在减少计算量的同时具有良好的性能。
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