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arXiv 2603.28016eess.SYcs.SYmath.OC
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线性系统在数据率约束下的输入到状态稳定化

Input-to-state stabilization of linear systems under data-rate constraints

Rutgers University–New Brunswick(罗格斯大学新不伦瑞克校区)

Mahmoud Zamani, Guosong Yang

AI总结:

本文研究了在未知干扰存在下,受有限数据率约束的连续时间线性系统反馈稳定化问题,提出了一种基于采样和量化状态测量的通信与控制策略,通过动态调整量化范围和利用量化参数估计的干扰,实现输入到状态稳定化,改进了现有结果。

摘要:

我们研究了在未知干扰存在下,受有限数据率约束的连续时间线性系统反馈稳定化问题。提出了一种基于采样和量化状态测量的通信与控制策略,其中量化范围通过可达集传播和从量化参数导出的干扰估计动态调整。该策略在稳定和搜索阶段之间交替,以处理逃离量化范围的情况,并使用额外的量化符号确保接近平衡点的鲁棒性。该策略保证了输入到状态稳定性(ISS),优于现有结果,这些结果只能提供实际ISS或缺乏显式的数据率条件。仿真结果展示了该策略的有效性。

英文摘要:

We study feedback stabilization of linear systems under data-rate constraints in the presence of completely unknown disturbances. A communication and control strategy is proposed based on sampled and quantized state measurements, where the quantization range is dynamically adjusted using reachable-set approximations and a disturbance estimate derived from quantization parameters. The strategy alternates between stabilizing and searching stages to recapture the state after escapes from the quantization range. Under a data-rate condition, it guarantees input-to-state stability (ISS) with respect to the disturbance. An additional quantization symbol is introduced to establish ISS near the equilibrium. A simulation example illustrates the effectiveness of the proposed approach.

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