Influence of State Space Topology on the Parameter Identification Based on the PSO Method
Keywords:Parameter estimation, particle swarm optimization, system identification
Motion control of electromechanical systems still plays very important role in 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 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 used 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. New approach to set the PSO method initial agents’ positions has been introduced because traditional random uniform distribution failed if wide state spaces were used.
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