Projeto de Filtro de Kalman em um manipulador robótico usando um algoritmo genético

Abstract

This research aims to use design Kalman Filter to estimate the state variables of a robotic manipulator, since the same are not available in practice. The problem of the Kalman filter is solved using the methodology of robust control LQG, this means that both the uncertainty with respect to the state variables, as the disturbances are considered during the controller design. Furthermore, it means that the designed controller can tolerate the error modeling without significantly degrading the performance of the control system. Regarding the evaluation of this methodology, it has been analyzed the response in the time domain for a unit impulse input, evaluating peak time, settling time, and steady-state error, and in the frequency domain, evaluating parameters such as: Gain Margin, Margin Phase, bandwidth, resonance frequency and resonance peak. It has been observed that the Kalman Filter has fulfilled its role of estimating states, satisfactorily, and performance and stability of the compensated system had desired behavior, even in the presence of noise in the plant and noise in the measurement, and additional poles not modeled