摘要
针对一类带有外部干扰、状态不可测的非仿射非线性系统,提出了基于观测器的自适应神经网络H∞跟踪控制结构.利用隐函数定理和泰勒公式及中值定理,将非仿射非线性系统转变为仿射型非线性系统.控制器由等效控制器和H∞控制器组成,H∞控制器用于减弱外部干扰及神经网络逼近误差对跟踪的影响.总体控制方案及基于李亚普诺夫稳定性理论的权值更新律保证了系统的稳定性及跟踪误差渐近收敛于零,并使干扰对系统的影响衰减到指定的性能指标.理论分析及仿真结果均证明了本文方法的有效性.
An observer-based adaptive neural-network H∞ tracking control scheme is presented for a class of non-affine nonlinear systems with external disturbance and unavailable states. By using implicit function theorem, Taylor＇s formula and mean theorem, the form of the non-affine nonlinear systems is transformed into the form of affine nonlinear systems. The controller consists of an equivalent controller and H∞ controller designed to attenuate the effect of external disturbance and approximation errors of the neural networks on tracking. The overall control scheme and the weight update laws based on Lyapunov stability theory can guarantee the system stability and asymptotic convergence of the tracking error to zero, and attenuate the effect of the disturbance on system to a prescribed level. Theoretical analysis and simulation results demonstrate the effectiveness of the approach.
出处
《信息与控制》
CSCD
北大核心
2009年第4期468-472,483,共6页
Information and Control
基金
湖南省科技计划资助项目(2008FJ3029)
湖南省自然科学基金资助项目(05JJ40093)
