Input-Ouput Linearization and Control of Nunlinear System Using Recurrent Neural Networks

리커런트 신경 회로망을 이용한 비선형 시스템의 입출력 선형화 및 제어

In this paper, we execute identification, linearization, and control of a nonlinear system using recurrent neural networks. In general nonlinear control system become complex because of nonlinearity and uncertainty. And though we compose nonlinear control system based on the model, it is difficult to get good control ability. So we identify the nonlinear control system using the recurrent neural networks and execute feedback linearization of identified model, In this process we choose the optional linear system, and the system which will have to be feedback linearized if trained to follow the linearity between input and output of the system we choose. We the feedback linearized system by applying standard linear control strategy and simulation. And we evaluate the effectiveness by comparing the result which is linearized theoretically.