Análise da Metodologia SOESGOPE em malha fechada para a Estimação Ótima de Parâmetros de um quadrotor

Abstract

There are several methods of optimal parameter estimation. In system identification, a rich excitation signal is required, which excites the system sufficiently. If the input/output ratio is not able to generate enough information, any OPE technique will necessarily fail. The process of identifying closed-loop systems is fundamental for situations in which the plant has non-linearities and behaviors that are difficult to predict and with stability not guaranteed for open-loop systems. This work presents an analysis of the SOESGOPE methodology for estimation of the parameters of a closed-loop system and excitation signal generation for the experiment. For the identification of closed loop non-linear systems, a simple controller is needed to preserve the system stable and to allow the passage of frequencies that adequately sensitize the system. For cases in which the uncertainties about the parameters complicate the design of the controller, a new approach to the methodology was proposed, aiming to find a simple and efficient controller for the estimation of parameters. The proposed new approach find, from the optimization process in two layers, a set of controllers to keep the system stable and compatible with with the excitation signal for the parameter estimation process. The new approach of the SOESGOPE methodology presents positive results for application in UAVs, with satisfactory performance in the estimation of parameters in all considered cases. The error obtained in the estimates of the parameters decreased to 1.5% in one of the parameters, in the new approach, the convergence time of the new algorithm was reduced in the range of 100 seconds and the entropy of the signals used for the parametric estimation increased by 3.3646 when compared to the original methodology, ensuring that the information for the parametric estimation is not lost when the excitation signal is filtered by the system controller