摘要
基于神经网络提出一种自适应Ｈ∞控制方法。控制器由等效控制器和Ｈ∞控制器两部分组成。用神经网络逼近未知非线性函数，Ｈ∞控制器用于减弱外部及神经网络逼近误差对跟踪误差的影响。所设计的控制器不仅保证了闭环控制系统的稳定性，而且使外部干扰及神经网络逼近误差对跟踪误差的影响减小到预定的性能指标。
A neural network based adaptive H control scheme is developed. In the procedure, the controller composed of equivalent controller and H controller, the neural networks are used to model the nonlinear functions for the design of the equivalent controller, and the H controller is designed for attenuating the external disturbance and approximation errors of the neural networks. The controller can not only guarantee the stability of the overall control system, but aslo attenuate the effect of both the external disturbance and neural approximation error to a prescribed leval. Furthermore, only smooth control signal is needed via the proposed control design, thus avoiding the chatting phenomena in traditional sliding model control. Finally, simulations are carried on the inverted pendulum systems, simulation results demonstrate the effectiveness of the proposed method.
出处
《控制与决策》
EI
CSCD
北大核心
1999年第4期297-302,共6页
Control and Decision
基金
国家自然科学基金
辽宁省教委科研基金
