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Model-Based Event-Triggered Control for Systems With Quantization and Time-Varying Network Delays

机译:带有量化和时变网络延迟的系统的基于模型的事件触发控制

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摘要

This paper combines two important control techniques for reducing communication traffic in control networks, namely, model-based networked control systems (MB-NCS) and event-triggered control. The resulting framework is used for stabilization of uncertain dynamical systems and is extended to systems subject to quantization and time-varying network delays. The use of a model of the plant in the controller node not only generalizes the zero-order-hold (ZOH) implementation in traditional event-triggered control schemes but it also provides stability thresholds that are robust to model uncertainties. The effects of quantized measurements are especially important in the selection of stabilizing thresholds. We are able to design error events based on the quantized variables that yield asymptotic stability compared to similar results in event-triggered control that consider nonquantized measurements which, in general, are not possible to use in digital computations. With respect to MB-NCS, the stability conditions presented here do not need explicit knowledge of the plant parameters as in previous work but are given only in terms of the parameters of the nominal model and some bounds in the model uncertainties. We consider the joint adverse effects of quantization and time delays and emphasize the expected tradeoff between the selection of quantization parameters and the admissible network induced delays.
机译:本文结合了两种重要的控制技术来减少控制网络中的通信流量,即基于模型的网络控制系统(MB-NCS)和事件触发控制。所得的框架用于稳定不确定的动态系统,并扩展到受量化和时变网络延迟影响的系统。在控制器节点中使用工厂模型不仅可以概括传统事件触发控制方案中的零阶保持(ZOH)实现,而且还提供了对不确定性建模具有鲁棒性的稳定性阈值。在选择稳定阈值时,量化测量的影响尤为重要。与事件触发控制中考虑非量化测量的类似结果相比,我们能够基于产生变量渐近稳定性的量化变量设计错误事件,而通常情况下这些量化无法在数字计算中使用。对于MB-NCS,此处介绍的稳定性条件不需要像以前的工作那样对工厂参数有明确的了解,而仅根据名义模型的参数和模型不确定性的某些范围给出。我们考虑了量化和时间延迟的共同不利影响,并强调了量化参数的选择与可容许的网络引起的延迟之间的预期折衷。

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