基于状态观测器的非仿射非线性系统鲁棒自适应H_∞跟踪控制

Robust Adaptive H_∞ Tracking Control Based on State Observer for a Class of Non-affine Nonlinear Systems

针对一类非仿射非线性系统,提出了基于状态观测器的鲁棒自适应H∞跟踪控制结构.文中利用高斯径向基神经网络(RBF神经网络)在线抵消非线性模型误差,利用高增益观测器估计不能直接测量的输出导数.利用李亚普若夫稳定理论导出了系统的控制律,包括固定结构的控制律和自适应控制律两个部分,并给出了详细的理论分析和证明:在系统没有扰动时,确保跟踪误差渐近趋于零且系统的所有信号有界;存在扰动时,取得了预期的H∞跟踪性能.*

A robust adaptive H∞ tracking control architecture with state observer is proposed for a class of nonaffine nonlinear systems. A Gauss radial basis function neural network （ RBF neural network） is used to eliminate nonlinear modeling errors, and a high-gain observer is used to estimate the system output derivatives whick are unavailable for measurement. Lyapunov stability theory is used to derive the control laws including fixed control law and adaptive law, and the detailed analysis is given. It is shown that the tracking error is guaranteed to be asymptotically convergent to zero when there exists no externel disturbance, and a desired H∞ tracking performance is achieved when externel disturbances exist.