Slack variable-based control variable parameterization method for constrained engineering optimization - Ping Liu; Guodong Li (2017 Chinese Automation Congress (CAC), 2017)
In this paper, a slack variable-based control variable parameterization (CVP) method is proposed for solving engineering dynamic optimization problems with inequality path constraints. An improved slack variable transform technique is introduced so that the original problem is converted into an unconstrained dynamic optimization problem (uDOP). No approximation error generated and the inequality path constraints are satisfied during the whole time intervals. A nonlinear programming (NLP) problem, which approximates the original dynamic optimization problem, is obtained by applying the control variable parameterization. The variational method is derived to calculate the gradients so that the transformed NLP problem can be easily solved. Test results show that the proposed method performs better than the penalty method in terms of computation accuracy and computation time.