An iterative framework to solve nonlinear optimal control with proportional delay using successive convexification and symplectic multi-interval pseudospectral scheme
作者：
Highlights：
• Optimal control problem of proportional delay systems is solved by an indirect method.
• Initial guess on costate variables is avoided due to the benefit of successive convexification (SCvx) technique.
• Each sub-problem is transformed into a system of linear algebraic equations with a sparse coefficient matrix.
• Converged solutions can be obtained within a few iterations with an exponential convergent rate.
• Both linear or exponential convergence property is exhibited by tuning the number of mesh and the LGL degree.
摘要
•Optimal control problem of proportional delay systems is solved by an indirect method.•Initial guess on costate variables is avoided due to the benefit of successive convexification (SCvx) technique.•Each sub-problem is transformed into a system of linear algebraic equations with a sparse coefficient matrix.•Converged solutions can be obtained within a few iterations with an exponential convergent rate.•Both linear or exponential convergence property is exhibited by tuning the number of mesh and the LGL degree.
论文关键词：Nonlinear optimal control,Proportional delay,Successive convexification,Symplectic pseudospectral method,Proportional mesh
论文评审过程：Received 5 June 2020, Revised 25 May 2022, Accepted 25 July 2022, Available online 14 August 2022, Version of Record 14 August 2022.
论文官网地址：https://doi.org/10.1016/j.amc.2022.127448
