Extended state observer-based backstepping control for nonlinear systems under FDI attacks.

Area of Science:

• Control Systems Engineering
• Nonlinear System Analysis
• Cybersecurity in Control

Background:

• Strict-feedback nonlinear systems are susceptible to unmeasured state dynamics.
• False Data Injection (FDI) attacks pose a significant threat to system security and performance.
• Existing control strategies may not adequately address simultaneous state estimation and attack mitigation.

Purpose of the Study:

• To develop a robust control scheme for nonlinear systems under FDI attacks.
• To simultaneously estimate unmeasured states and detect/compensate for FDI attacks.
• To ensure the stability and performance of the closed-loop system despite security threats.

Main Methods:

• Design of a novel extended state observer (ESO) for online state and attack estimation.
• Development of a backstepping control strategy integrated with the ESO.
• Implementation of an output feedback tracking controller with an attack compensation mechanism.

Main Results:

• The proposed scheme guarantees semi-global uniformly ultimately boundedness of the closed-loop system.
• Observation errors are shown to be adjustable to arbitrarily small values.
• Tracking errors converge to a small neighborhood of the origin, demonstrating effective control.

Conclusions:

• The novel extended state observer-based backstepping control effectively addresses FDI attacks in nonlinear systems.
• The proposed method ensures system stability and accurate state tracking even with unmeasured states.
• Simulation examples confirm the practical efficacy and robustness of the developed control strategy.