Prescribed Fixed-Time Control for Constrained Uncertain Nonlinear Cyber-Physical Systems Against Deception Attacks.

Area of Science:

• Control Engineering
• Cyber-Physical Systems
• Nonlinear Systems

Background:

• Cyber-physical systems (CPSs) face challenges from exogenous perturbations and deception attacks.
• Existing dynamic surface control (DSC) schemes can suffer from computational complexity.
• Ensuring constrained performance and fixed-time convergence in nonlinear systems is crucial.

Purpose of the Study:

• To develop a novel prescribed fixed-time adaptive tracking control scheme for MIMO nonlinear CPSs.
• To address challenges posed by exogenous perturbations and controller-actuator (C-A) channel deception attacks.
• To enhance system performance and ensure predefined tracking accuracy and regulation time.

Main Methods:

• Design of a novel nonlinear filter to mitigate computational complexity.
• Integration of a new barrier Lyapunov function (BLF) with the prescribed performance function (PPF) approach.
• Development of an adaptive tracking control strategy for constrained MIMO nonlinear CPSs.

Main Results:

• The proposed control strategy effectively handles both exogenous interferences and deception attacks simultaneously.
• All tracking errors (output and virtual) converge to a prespecified region within a fixed time.
• Tracking errors consistently adhere to predefined constraints throughout the control operation.

Conclusions:

• The novel control scheme guarantees fixed-time convergence and constraint satisfaction for MIMO nonlinear CPSs.
• The approach offers arbitrary prespecification of regulation time and tracking accuracy.
• The effectiveness is validated through a representative application instance.