IEEE Trans Neural Netw Learn Syst. 2017 Jul;28(7):1520-1530. doi: 10.1109/TNNLS.2016.2529843. Epub 2016 Mar 8.
This paper is concerned with the problem of adaptive tracking control for a class of uncertain nonlinear systems with nonsymmetric input saturation and immeasurable states. The radial basis function of neural network (NN) is employed to approximate unknown functions, and an NN state observer is designed to estimate the immeasurable states. To analyze the effect of input saturation, an auxiliary system is employed. By the aid of adaptive backstepping technique, an adaptive tracking control approach is developed. Under the proposed adaptive tracking controller, the boundedness of all the signals in the closed-loop system is achieved. Moreover, distinct from most of the existing references, the tracking error can be bounded by an explicit function of design parameters and saturation input error. Finally, an example is given to show the effectiveness of the proposed method.
本文针对一类具有非对称输入饱和和不可测状态的不确定非线性系统的自适应跟踪控制问题进行了研究。利用神经网络(NN)的径向基函数来逼近未知函数,并设计了一个 NN 状态观测器来估计不可测状态。为了分析输入饱和的影响,引入了一个辅助系统。通过自适应反推技术,提出了一种自适应跟踪控制方法。在所提出的自适应跟踪控制器下,闭环系统中所有信号的有界性得以实现。此外,与大多数现有参考文献不同的是,跟踪误差可以通过设计参数和饱和输入误差的显式函数来进行约束。最后,通过一个实例验证了所提出方法的有效性。