神经网络逆系统及其在电力系统控制中的应用

摘要

This paper presents and proves a sufficient condition of the invertibility of a general class of dynamic systems, which are represented by input-output differential equations. The realization of the corresponding analytic inverse system is also discussed. A novel dynamic neural network (NN), constructed based on a number of integrators and the static neural network, is investigated. Based on neural networks and the inverse system theory, an α-th order NN inverse system is proposed and its application to power system TCSC control has been attempted. Simulation results show the effectiveness of the proposed methods.%阐述和证明了基于输入输出微分方程描述的系统可逆性的充分条件，并给出了相应的解析逆系统的实现方法。文中同时研究了采用积分器和静态神经网络组成动态神经网络结构的方法，并将这种神经网络结构与逆系统理论相结合，提出了神经网络α阶逆系统的结构及其实现步骤，运用该神经网络α阶逆系统对TCSC控制器进行了设计。实际系统的仿真结果证实了所设计控制策略的有效性。