非线性系统神经网络输出稳定控制器的设计

针对一类非线性系统,以线性化后的布鲁诺标准型为新被控对象,提出一种基于李雅普诺夫定理的神经网络稳定控制器。该非线性控制器采用神经网络补偿的方式来抵消外界干扰的不利影响,减少系统达到平衡状态的时间。分析了系统的稳定性,并将该方法应用到单机无穷大电力系统中,仿真结果验证了该控制器在非线性系统稳定性控制中的有效性。

Design of neural network output stability controller for nonlinear system

With a linearlization standard Brunovsky model as the controlled object in a class of non-linear,we propose a new neural network stable controller based on Lyapunov principle.The non-linear controller can check the disturbances to reduce the responding time to the balance state.Both the robustness and stability are analyzed,and the controller is applied to the single-machine infinite power system.The simulation results verify the effectiveness of the controller for the stability of the non-linear system.