Adaptación paramétrica de un sistema borroso mediante el filtro de Kalman extendido

Cuando se pretende analizar o controlar un sistema cuyo modelo se ha obtenido ´únicamente en base a datos de entrada/salida, es fundamental la precisión en el modelo. Por otro lado, para que el procedimiento sea practico, la etapa de modelado ha de ser eficiente computacionalmente hablando. En este sentido, se presenta en este trabajo la aplicación del filtro de Kalman extendido para la adaptación paramétrica de un modelo borros

Algoritmo para la adaptación paramétrica de un sistema borroso mediante el filtro de Kalman extendido

La fase de modelado es fundamental tanto en el proceso de análisis de un sistema dinámico como en el de diseño de un sistema de control. Esta fase es aún más crítica si se realiza en línea y la única información que se posee del sistema proviene de datos de entrada-salida del mismo. En este trabajo se presenta un algoritmo para la adaptación paramétrica de un sistema borroso basado en el filtro de Kalman extendido, el cual permite obtener modelos precisos sin renunciar a la eficiencia computacional que caracteriza al filtro de Kalman, y que permite su aplicación en línea con el proceso

Variable structure control with chattering elimination and guaranteed stability for a generalized T-S model

In this paper, a fuzzy based Variable Structure Control (VSC) with guaranteed stability is presented. The main objective is to obtain an improved performance of highly non-linear unstable systems. The main contribution of this work is that, firstly, new functions for chattering reduction and error convergence without sacrificing invariant properties are proposed, which is considered the main drawback of the VSC control. Secondly, the global stability of the controlled system is guaranteed.The well known weighting parameters approach, is used in this paper to optimize local and global approximation and modeling capability of T-S fuzzy model.A one link robot is chosen as a nonlinear unstable system to evaluate the robustness, effectiveness and remarkable performance of optimization approach and the high accuracy obtained in approximating nonlinear systems in comparison with the original T-S model. Simulation results indicate the potential and generality of the algorithm. The application of the proposed FLC-VSC shows that both alleviation of chattering and robust performance are achieved with the proposed FLC-VSC controller. The effectiveness of the proposed controller is proven in front of disturbances and noise effects

Fuzzy Optimal Control for Double Inverted Pendulum

In this paper a fuzzy optimal control for stabilizing an upright position a double inverted pendulum (DIP) is developed and compared. Modeling is based on Euler-Lagrange equations. This results in a complicated nonlinear fast reaction, unstable multivariable system. Firstly, the mathematical models of double pendulum system are presented. The weight variable fuzzy input is gained by combining the fuzzy control theory with the optimal control theory. Simulation results show that the controller, which the upper pendulum is considered as main control variable, has high accuracy, quick convergence speed and higher precision

Practice what you teach

When we try to analyze and to control a system whose model was obtained only based on input/output data, accuracy is essential in the model. On the other hand, to make the procedure practical, the modeling stage must be computationally efficient. In this regard, this paper presents the application of extended Kalman filter for the parametric adaptation of a fuzzy mode