Influence of State Space Topology on the Parameter Identification Based on the PSO Method

Anotace: Motion control of electromechanical systems still plays a very important role in a wide area of weapon systems. Modern control systems use not only data from various sensors, but also state parameters of controlled system. The article explores the influence of state space topology on parameter identification of real simple electromechanical system based on the Particle Swarm Optimization (PSO) method. Four different but equivalent mathematical models of the second order were used to create different state spaces of the system parameters. A general recommendation for the PSO method setup and two independent program tools were applied to evaluate the state space searching by the PSO method. The PSO simulations were focused on both narrow and wide state spaces around the fitness function global minimum. A novel approach to set the PSO method initial agents’ positions has been introduced since the traditional random uniform distribution failed when wide state spaces were used.