Optimal control using Particle Swarm Optimization: Case study: Bilocal constrained problem for a DC motor
Viorel Mînzu · 2017
This paper has as a start point the metaheuristic Particle Swarm Optimization (PSO), which has very good abilities to solve many types of optimization problems. As a main contribution, this work proposes an intelligent algorithm derived from PSO. This algorithm has two main characteristics. The first one consists in the use of an improved version of PSO, namely Hybrid Topology Particle Swarm Optimization (HTPSO). The second characteristic is related to the kind of solved problems. The algorithm is devoted to the optimal control problems, even those who handle bilocal constraints concerning the state variables. In order to prove its efficiency, the HTPSO algorithm was tested on many optimal control problems. A case study is presented in the second part of this paper: the optimal control problem for a DC motor with bilocal constraints. In addition to the initial conditions, there are also final conditions related to the state variables. Emphasis is placed on the use of an extended objective function.