论文标题
控制未知（线性）系统的控制范围学习
Control of Unknown (Linear) Systems with Receding Horizon Learning
论文作者
论文摘要
提出了一种退化的视野学习方案，以将离散时间动态控制系统的状态转移到无需系统模型的情况下将其转移到零。假设只有输入和输出数据可用，并且已知状态维度的上限，则证明了全局状态收敛到零的可稳定性和可检测的线性时间流动系统。所提出的方案包括一个退化的地平线控制方案和基于接近度的估计方案，以估计和控制闭环轨迹。为线性和非线性系统提供了模拟。
A receding horizon learning scheme is proposed to transfer the state of a discrete-time dynamical control system to zero without the need of a system model. Global state convergence to zero is proved for the class of stabilizable and detectable linear time-invariant systems, assuming that only input and output data is available and an upper bound of the state dimension is known. The proposed scheme consists of a receding horizon control scheme and a proximity-based estimation scheme to estimate and control the closed-loop trajectory. Simulations are presented for linear and nonlinear systems.
