A Warm-Start Strategy in Interior Point Methods for Shrinking Horizon Model Predictive Control With Variable Discretization Step

• 成果类型: Article
• 署名作者: Zhang, Ziyou; Zhao, Qianchuan; Dai, Fa-An
• 署名单位: Tsinghua University
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2022.3201026
• 发表日期: 2023
• 页码: 3830-3837
• 关键词: Optimal control; trajectory; interpolation; COSTS; Complexity theory; Predictive control; Real-time systems; Interior point method (IPM); optimal control; second-order cone programming (SOCP); warm-start

摘要

In this article, we present a warm-start point algorithm in interior point methods for shrinking horizon model predictive control with a variable discretization step. In the algorithm, a convex combination of components of the earlier optimal solution is used to construct an interpolation point, and we use the convex combination of the modified interpolation point and the cold-start point to obtain a warm-start point. We prove that the worst-case iteration complexity of our strategy is better than that of the cold-start. In the numerical experiment of fuel-optimal planetary powered-descent guidance problems, our strategy reduces the number of iterations of second-order cone programming by about 80% with the number of samples available in practical applications.