Control Parameter Optimization in the Hardware-in-the-loop System using Novel Search Algorithm

This article proposes an improved version of particle swarm optimization (PSO) algorithm where one or two particles are moving with a strategy: golden section search and steepest descent method. We clarify the excellence of the proposed algorithm using some benchmark problems and examine what kind of problems the proposed algorithm is adequate for. This algorithm is developed with the aim to be applied to auto-tuning of NC controllers. As this industrial application, a hardware-in-the-loop system which consists of a NC system with two motors and a computer that optimizes control parameters of the NC controller is constructed. Experimental results with this system verify the effectiveness of the proposed optimization method