An Indirect Method for Regular State-Constrained Optimal Control Problems in Flow Fields

• 成果类型: Article
• 署名作者: Chertovskih, Roman; Karamzin, Dmitry; Khalil, Nathalie T.; Pereira, Fernando Lobo
• 署名单位: Universidade do Porto; Russian Academy of Sciences; Federal Research Center Computer Science & Control of RAS
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2020.2986179
• 发表日期: 2021
• 页码: 787-793
• 关键词: Indirect numerical methods; MAXIMUM PRINCIPLE; optimal control; REGULARITY; state constraints

摘要

This article concerns an indirect method to solve state-constrained optimal control problems. The dynamics of the controlled system is given by ordinary differential equations encompassing the effect of a steady flow field in which the moving object is immersed. The proposed method is based on the maximum principle in Gamkrelidze's form. At the core of the approach is a regularity hypothesis which entails the continuity of the measure Lagrange multiplier associated with the state constraint. This property plays key role in shaping a properly modified shooting method to solve the two-point boundary value problem resulting from the maximum principle. Illustrative applications to time optimal control problems are considered and results of numerical experiments are provided.