Chen Bing, Zhang Huaguang, Liu Xiaoping, Lin Chong
IEEE Trans Neural Netw Learn Syst. 2018 Sep;29(9):4261-4271. doi: 10.1109/TNNLS.2017.2760903. Epub 2017 Oct 31.
This paper addresses the problem of adaptive neural tracking control for nonlinear nonstrict-feedback systems. The state variables are immeasurable and only the system output is available. A neural observer is constructed to estimate these unknown system state variables. An observer-based adaptive neural tracking control scheme is developed via backstepping approach. It is shown that the designed controller guarantees that the system output well follows the desired reference signal, and meanwhile, other closed-loop signals remain bounded. Finally, two simulation examples are used to test our results.
本文研究了非线性非严格反馈系统的自适应神经跟踪控制问题。状态变量不可测量，仅有系统输出可用。构造了一个神经观测器来估计这些未知的系统状态变量。通过反步法设计了一种基于观测器的自适应神经跟踪控制方案。结果表明，所设计的控制器能保证系统输出很好地跟踪期望参考信号，同时，其他闭环信号保持有界。最后，用两个仿真例子验证了我们的结果。
