가변구조 시스템을 위한 신경회로망 학습 알고리즘

Neural Network Learning Algorithm for Variable Structure System

In this paper, a new control strategy is presented that combines sliding mode control theory with a neural network. Sliding mode control theory requires the complete knowledge of the dynamics of the controlled system. However, in practice, one often bas only a small number of state measurements. This could be a serious limitation on the practical usefulness of sliding mode control theory. A multilayer neural network is employed to solve this kind of problem. The neural network serves as a compensator without a prior knowledge about the system. The proposed control algorithm is applied to a class of uncertain nonlinear system. The robustness against parameter uncertainty, nonlinearity and external disturbances, and the effectiveness is verified by the simulation results.