IET, Modelling and Parameter Estimation of Dynamic Systems

Parameter estimation involves using system observations to build mathematical models that accurately capture system dynamics. The model is defined by a finite set of parameters, whose values are determined through estimation methods. Traditionally, most techniques rely on minimizing the error between the model’s output and the actual system response using least-squares methods. However, with the advent of high-speed digital computing, more advanced approaches—such as the filter error method, genetic algorithms, and artificial neural networks—are increasingly being applied to parameter estimation challenges. Modelling and Parameter Estimation of Dynamic Systems offers an in-depth exploration of various estimation techniques and modeling issues.