论文标题
具有Lyapunov稳定性的神经观察者的不确定非线性系统
Neural Observer with Lyapunov Stability Guarantee for Uncertain Nonlinear Systems
论文作者
论文摘要
在本文中，我们提出了一个基于神经网络的新型非线性观察者，称为神经观察者，以观察线性时间不变（LTI）系统和不确定的非线性系统的观察任务。特别是，专为不确定系统设计的神经观察者受到主动干扰拒绝控制的启发，该控制可以实时测量不确定性。提出并保证了LTI和不确定的非线性系统（涉及神经观察者）的稳定性分析（例如，指数收敛速率）（涉及神经观察者），并保证仅使用线性基质不等式（LMI）才能解决观察问题。同样，据表明，需要系统矩阵的可观察性和可控性来证明LMI的溶液的存在。最后，在三个模拟案例中验证了神经观察者的有效性，包括X-29A飞机模型，非线性摆和四轮转向车辆。
In this paper, we propose a novel nonlinear observer based on neural networks, called neural observer, for observation tasks of linear time-invariant (LTI) systems and uncertain nonlinear systems. In particular, the neural observer designed for uncertain systems is inspired by the active disturbance rejection control, which can measure the uncertainty in real-time. The stability analysis (e.g., exponential convergence rate) of LTI and uncertain nonlinear systems (involving neural observers) are presented and guaranteed, where it is shown that the observation problems can be solved only using the linear matrix inequalities (LMIs). Also, it is revealed that the observability and controllability of the system matrices are required to demonstrate the existence of solutions of LMIs. Finally, the effectiveness of neural observers is verified on three simulation cases, including the X-29A aircraft model, the nonlinear pendulum, and the four-wheel steering vehicle.
