论文标题
采样控制框架和适用于稳健和自适应控制的应用
A Sampling Control Framework and Applications to Robust and Adaptive Control
论文作者
论文摘要
在本文中，我们提出了一个基于仿真技术的新型采样控制框架，其中采样误差被视为模拟系统的辅助输入。利用采样误差的最高规范，周期性采样和事件触发的控制法的设计使误差动力学有限输入结合状态（BIBS）以及与系统动力学结合时，实现了全球或半全球稳定。然后，将提出的框架扩展以解决事件触发的和周期性采样的稳定，该系统只有部分状态可用于反馈，并且该系统受参数不确定性的约束。进一步扩展了所提出的框架，以求解两类事件触发的自适应控制问题，在这些问题中，模拟的闭环系统不接受输入到国家稳定性（ISS）Lyapunov功能。对于具有线性参数化不确定性的第一类系统，在文献中经常需要的是，在没有全球Lipschitz对非线性条件的情况下，可以实现甚至触发的全球自适应稳定化。对于第二类的系统，其界限未知的系统，事件触发的自适应（动态）增益控制器首次设计。最后，理论结果通过两个数值示例验证。
In this paper, we propose a novel sampling control framework based on the emulation technique where the sampling error is regarded as an auxiliary input to the emulated system. Utilizing the supremum norm of sampling error, the design of periodic sampling and event-triggered control law renders the error dynamics bounded-input-bounded-state (BIBS), and when coupled with system dynamics, achieves global or semi-global stabilization. The proposed framework is then extended to tackle the event-triggered and periodic sampling stabilization for a system where only partial state is available for feedback and the system is subject to parameter uncertainties. The proposed framework is further extended to solve two classes of event-triggered adaptive control problems where the emulated closed-loop system does not admit an input-to-state stability (ISS) Lyapunov function. For the first class of systems with linear parameterized uncertainties, even-triggered global adaptive stabilization is achieved without the global Lipschitz condition on nonlinearities as often required in the literature. For the second class of systems with uncertainties whose bound is unknown, the event-triggered adaptive (dynamic) gain controller is designed for the first time. Finally, theoretical results are verified by two numerical examples.
