Parameter estimation for state controlled rolling-mill motors using evolutionary algorithms

The subject of this research is the automated start-up procedure of a PI state controlled high-powered electrical drive by using evolutionary algorithms. Compared to the conventional PI speed control, applying the method of deliberate pole placement to the state controller design succeeds in improving the transient response of setpoint and disturbance changes. To put the PI state controlled drive with observer into operation to obtain a controller with a high robustness and dynamic, the precise knowledge of this physical parameter is necessary. An evolution-based system is used to solve the estimation problem. A high degree of reliability respecting multimodal characteristics and robustness against random noise is expected from the identification method. Evolutionary algorithms fulfil this requirement. With genetic operators like mutation, crossover and selection, evolutionary algorithms mimic the principles of organic evolution in order to solve the optimization problem.