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Periodic Event-Triggered Quantization Policy Design for a Scalar LTI System With i.i.d. Feedback Dropouts

机译:具有i.i.d的标量LTI系统的定期事件触发量化策略设计反馈辍学

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This technical note proposes an event-triggered quantization policy design method to stabilize a scalar continuous-time linear time-invariant (LTI) system, whose feedback loop is closed over an unreliable digital communication network. The feedback packets suffer from network delay and may be dropped in an independent and identically distributed (i.i.d.) way. In order to save quantization bit rate, we implement a periodic event-triggering strategy which periodically samples the state and only quantizes and transmits the sampled state when a predefined event is triggered. By making good use of both the information bits and the sampling time instants of the feedback packets, our policy can obtain the desired mean-square stability at a lower bit rate than the conventional time-triggered quantization policies which utilize only the information bits inside the feedback packets. Under our quantization policy, the stabilizing bit rate condition is up to the dropout rate, the processing and network delays and the unstable eigenvalue of the system, and is independent of the bounded process noise.
机译:本技术说明提出了一种事件触发的量化策略设计方法,以稳定标量连续时间线性时不变(LTI)系统,该系统的反馈回路在不可靠的数字通信网络上闭合。反馈分组遭受网络延迟,并且可以以独立且相同分布(i.i.d.)的方式丢弃。为了节省量化比特率,我们实现了一种周期性的事件触发策略,该策略会定期对状态进行采样,并且仅在触发预定义事件时才对采样的状态进行量化和传输。通过充分利用信息包和反馈数据包的采样时刻,我们的策略可以以比传统的时间触发量化策略低的比特率获得所需的均方稳定度,而传统的时间触发量化策略仅利用内部的信息位。反馈数据包。在我们的量化策略下,稳定比特率条件取决于丢包率,处理和网络延迟以及系统的不稳定特征值,并且不受制程噪声的影响。

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