Self-triggered Resilient Stabilization of Linear Systems with Quantized Output

TL;DR

This paper develops a resilient self-triggered control method for linear systems with quantized output, capable of handling DoS attacks and reducing communication, demonstrated through a numerical example.

Contribution

It introduces a novel self-triggered stabilization approach with output encoding, resilient to DoS, and simplifies control architecture with adaptive transmission protocols.

Findings

Exponential stabilization under certain DoS conditions.

Trade-off identified between sampling time and DoS resilience.

Numerical example confirms practical effectiveness.

Abstract

This paper studies the problem of stabilizing a self-triggered control system with quantized output. Employing a standard observer-based state feedback control law, a self-triggering mechanism that dictates the next sampling time based on quantized output is co-developed with an output encoding scheme. If, in addition, the transmission protocols at the controller-to-actuator (C-A) and sensor-to-controller (S-C) channels can be adapted, the self-triggered control architecture can be considerably simplified, leveraging a delicate observer-based deadbeat controller to eliminate the need for running the controller in parallel at the encoder side. To account for denial-of-service (DoS) in the S-C channel, the proposed output encoding and self-triggered control schemes are further made resilient. It is shown that a linear time-invariant system can be exponentially stabilized if some conditions on the average DoS duration time are met. There is a trade-off between the maximum inter-sampling time and the resilience against DoS attacks. Finally, a numerical example is presented to demonstrate the practical merits of the proposed self-triggered control schemes and associated theory.