Adaptive output feedback control of uncertain nonlinear systems using single-hidden-layer neural networks
Adaptive output feedback control of uncertain nonlinear systems using single-hidden-layer neural networks
复制标题
DOI：
10.1109/tnn.2002.804289
复制
发表时间：
2002-11
影响因子：
--
通讯作者：
N. Hovakimyan;F. Nardi;A. Calise;Nakwan Kim
中科院分区：
文献类型：
--
作者：
N. Hovakimyan;F. Nardi;A. Calise;Nakwan Kim
我们考虑不确定非线性系统的自适应输出反馈控制，其中被控系统的动力学特性和维数可能都是未知的。然而，假定被控输出的相对阶数是已知的。给定一个平滑的参考轨迹，问题是设计一个控制器，迫使系统的测量值以有界误差跟踪该参考轨迹。经典方法需要一个状态观测器。为不确定非线性系统找到一个好的观测器并非易事。我们认为，为输出跟踪误差构建一个观测器就足够了。通过李雅普诺夫直接法证明了误差信号的最终有界性。理论结果在一个相对阶数为2的四阶非线性系统的控制器设计以及一个R - 50直升机模型的高带宽姿态指令系统中得到了说明。
We consider adaptive output feedback control of uncertain nonlinear systems, in which both the dynamics and the dimension of the regulated system may be unknown. However, the relative degree of the regulated output is assumed to be known. Given a smooth reference trajectory, the problem is to design a controller that forces the system measurement to track it with bounded errors. The classical approach requires a state observer. Finding a good observer for an uncertain nonlinear system is not an obvious task. We argue that it is sufficient to build an observer for the output tracking error. Ultimate boundedness of the error signals is shown through Lyapunov's direct method. The theoretical results are illustrated in the design of a controller for a fourth-order nonlinear system of relative degree two and a high-bandwidth attitude command system for a model R-50 helicopter.