论文标题
基于模型和数据驱动的事件和自触发离散时间LTI系统的控制
Model-Based and Data-Driven Control of Event- and Self-Triggered Discrete-Time LTI Systems
论文作者
论文摘要
本文考虑了在事件触发和自我触发传输方案下对未知线性时间不变的离散时间系统的基于模型和数据驱动的控制。为此，我们首先基于周期性采样介绍动态事件触发方案（ETS），以及一个离散的时间循环功能方法，通过该方法得出了基于模型的稳定性条件。建立了基于模型的条件与最新的基于数据的系统表示，建立了以线性矩阵不平等（LMI）形式的数据驱动稳定性标准，这也提供了一种共同设计ETS矩阵和控制器的方法。为了进一步减轻ETS的采样负担，由于其连续/周期性检测，开发了自触发方案（STS）。利用预收缩的输入状态数据，给出了一种预测下一个传输瞬间的算法，同时实现了系统稳定性。最后，数值模拟展示了ET和ST在减少数据传输以及所提出的共同设计方法的功效。
The present paper considers the model-based and data-driven control of unknown linear time-invariant discrete-time systems under event-triggering and self-triggering transmission schemes. To this end, we begin by presenting a dynamic event-triggering scheme (ETS) based on periodic sampling, and a discrete-time looped-functional approach, through which a model-based stability condition is derived. Combining the model-based condition with a recent data-based system representation, a data-driven stability criterion in the form of linear matrix inequalities (LMIs) is established, which also offers a way of co-designing the ETS matrix and the controller. To further alleviate the sampling burden of ETS due to its continuous/periodic detection, a self-triggering scheme (STS) is developed. Leveraging pre-collected input-state data, an algorithm for predicting the next transmission instant is given, while achieving system stability. Finally, numerical simulations showcase the efficacy of ETS and STS in reducing data transmissions as well as of the proposed co-design methods.
