Asymptotic Stabilization of Nonlinear DAE Subsystems Using Artificial Neural Networks with Application to Power Systems

摘要

The problem of robust stabilization for such class of uncertain nonlinear Differential-Algebraic Eqyatuion subsystems is considered in this paper. The robust stabilization controller is proposed based on backstepping approach using two-layer Artificial Neural Networks (ANN) whose weights are updated on-line. A new adaptive algorithm is proposed to update the weights of ANN such that all signals in the closed-loop systems are bounded and the states are convergent asymptotically to the equilibrium through the proposed controller. Finally, using the design scheme proposed in this paper, a governor controller is designed for one synchronous generator in a multi-machine power systems. The simulation results demonstrate its effectiveness.