Adaptive Security Control Using Output Only for Quantized Nonlinear Systems Under Irregularly Intermittent DoS...

Area of Science:

• Control Theory
• Nonlinear Systems
• Cybersecurity

Background:

• Quantized signal-driven control is crucial for nonlinear systems.
• Mismatched uncertainties and denial-of-service (DoS) attacks complicate control design.
• Attacks on input/output signals make states and inputs inaccessible, hindering traditional control methods.

Purpose of the Study:

• To develop a novel adaptive output feedback control method for nonlinear systems under quantized signals, uncertainties, and DoS attacks.
• To address challenges posed by inaccessible states and quantized, nondifferentiable output signals.
• To ensure stability and bounded errors in closed-loop systems.

Main Methods:

• Design of a gain-switched quantized observer for state estimation.
• Application of first-order dynamic filtering to handle signal quantization nondifferentiability.
• Development of adaptive estimators for unknown quantization parameters using a sector quantizer.
• Establishment of controller parameter design conditions.

Main Results:

• All closed-loop signals are demonstrated to be semiglobally uniformly ultimately bounded (SUUB).
• Regulation error can be minimized by adjusting design parameters.
• The proposed method effectively handles quantized outputs and intermittent DoS attacks.

Conclusions:

• The novel adaptive output feedback control method successfully addresses complex challenges in quantized nonlinear systems.
• The approach provides robust control against uncertainties and DoS attacks.
• Numerical simulations validate the proposed method's effectiveness and stability guarantees.