A Novel Penalty Approach for Nonlinear Dynamic Optimization Problems With Inequality Path Constraints

摘要

The control vector parameterization (CVP) approach is popular to solve nonlinear dynamic optimization problems, but handling inequality path constraints within its framework is a challenge. This study deals with inequality path constraints by using the $l_{1}$ penalty function and a novel smoothing technique. After clarifying some theories of the proposed approach, a concomitant algorithm is also put forward and verified.