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The sector bound approach to quantized feedback control

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TLDR
The coarsest quantization densities for stabilization for multiple-input-multiple-output systems in both state feedback and output feedback cases are derived and conditions for quantized feedback control for quadratic cost and H/sub /spl infin// performances are derived.
Abstract
This paper studies a number of quantized feedback design problems for linear systems. We consider the case where quantizers are static (memoryless). The common aim of these design problems is to stabilize the given system or to achieve certain performance with the coarsest quantization density. Our main discovery is that the classical sector bound approach is nonconservative for studying these design problems. Consequently, we are able to convert many quantized feedback design problems to well-known robust control problems with sector bound uncertainties. In particular, we derive the coarsest quantization densities for stabilization for multiple-input-multiple-output systems in both state feedback and output feedback cases; and we also derive conditions for quantized feedback control for quadratic cost and H/sub /spl infin// performances.

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${\cal H}_{\infty}$ Estimation for Uncertain Systems With Limited Communication Capacity

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References
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Book

Feedback Systems: Input-output Properties

TL;DR: In this paper, the Bellman-Gronwall Lemma has been applied to the small gain theorem in the context of linear systems and convolutional neural networks, and it has been shown that it can be applied to linear systems.
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Control under communication constraints

TL;DR: This paper forms a control problem with a communication channel connecting the sensor to the controller, and provides upper and lower bounds on the channel rate required to achieve different control objectives.
Journal ArticleDOI

Stabilization of linear systems with limited information

TL;DR: By relaxing the definition of quadratic stability, it is shown how to construct logarithmic quantizers with only finite number of quantization levels and still achieve practical stability of the closed-loop system.
Journal ArticleDOI

Quantized feedback stabilization of linear systems

TL;DR: A new control design methodology is proposed, which relies on the possibility of changing the sensitivity of the quantizer while the system evolves, which yields global asymptotic stability.
Journal ArticleDOI

The complex structured singular value

TL;DR: A tutorial introduction to the complex structured singular value (μ) is presented, with an emphasis on the mathematical aspects of μ.
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