Mixed-integer optimal control problems (MIOCPs) frequently arise in the domain of optimal control problems (OCPs) when decisions including integer variables are involved. However, existing state-of-the-art approaches for solving MIOCPs are often plagued by drawbacks such as high computational costs, low precision, and compromised optimality. In this study, we propose a novel multiphase scheme coupled with an iterative second-order cone programming (SOCP) algorithm to efficiently and effectively address these challenges in MIOCPs. In the first phase, we relax the discrete decision constraints and account for the terminal state constraints and certain path constraints by introducing them as penalty terms in the objective function. After formulating the problem as a quadratically constrained quadratic programming (QCQP) problem, we propose the iterative SOCP algorithm to solve general QCQPs. In the second phase, we reintroduce the discrete decision constraints to generate the final solution. We substantiate the efficacy of our proposed multiphase scheme and iterative SOCP algorithm through successful application to two practical MIOCPs in planetary exploration missions.
Multiphase Iterative Algorithm for Mixed-Integer Optimal Control
Journal of Guidance, Control, and Dynamics ; 48 , 4 ; 757-770
2025-04-01
Article (Journal)
Electronic Resource
English
Multiphase Mixed-Integer Optimal Control Approach to Aircraft Trajectory Optimization
Online Contents | 2013
|Multiphase Mixed-Integer Optimal Control Approach to Comercial Aircraft Trajectory Optimization
BASE | 2013
|Comercial aircraft trajectory planning based on multiphase mixed-integer optimal control.
BASE | 2013
|