Offline Parameter Identification of Second-order Discrete Systems using Metaheuristic Algorithms

The analysis of dynamic systems is essential in the design of both classical and modern controllers, especially in situations where obtaining accurate model parameters is complex. This difficulty stems from the uncertain and variable nature of many real systems, which can compromise the effectiveness of the designed controllers. In order to address this problem, this article proposes developing an innovative methodology based on the Rooted Tree Optimization (RTO) algorithm. This algorithm, inspired by the natural behavior of plant roots moving toward the nearest water sources, is used as a metaphor for the search for optimal parameters. In particular, the methodology suggests the optimization of the parameters of the discrete transfer function of second-order systems, thus seeking to improve the accuracy and robustness of the dynamic models used in control. In addition, tests were carried out where the signal measurement was contaminated by random noise to obtain the model parameters, showing robustness in searching for parameters, even when the signal was unclear.