Estimação de Estados de um Carro-Pêndulo Invertido Usando um Algoritmo Fuzzy Adaptativo Baseado em Inovação

Abstract

State estimation is a technique used in system control and identification, fault detection, monitoring, and prediction. In this work, state estimation of a cart-inverted pendulum system is developed using a fuzzy innovative-based adaptive algorithm, taking into account that the cart-inverted pendulum is a relevant system in real-world applications, such as space vehicle and missile launches, cranes for container handling, and self-balancing robots. Numerical simulation results show the effectiveness and robustness of the used method compared to the extended Kalman filter, considering four challenging scenarios.