Observer-Based Adaptive Fixed-Time Sensor Fault Compensation Control for Uncertain Nonlinear Systems

Area of Science:

• Control Systems Engineering
• Nonlinear System Analysis
• Fault Diagnosis and Tolerance

Background:

• Uncertain nonlinear systems are susceptible to sensor faults, degrading performance and safety.
• Existing control methods struggle with simultaneous state estimation and fault compensation under fixed-time constraints.
• Accurate tracking and stability are critical in dynamic systems despite sensor malfunctions.

Purpose of the Study:

• To develop an observer-based adaptive sensor fault compensation strategy for uncertain nonlinear systems.
• To achieve fixed-time tracking control despite unknown system dynamics and sensor failures.
• To ensure all system states and tracking errors converge within a predetermined finite time.

Main Methods:

• Design of a novel sixth-power Lyapunov function for adaptive fixed-time fault compensation.
• Development of an improved state observer to estimate unmeasured states using only actual output.
• Integration of observer-based state estimation with adaptive fault compensation for controller design.

Main Results:

• All closed-loop signals are demonstrated to be bounded within a fixed-time interval.
• Observation errors and tracking errors converge to a small neighborhood around zero in fixed time.
• Simulation results validate the effectiveness and robustness of the proposed control approach.

Conclusions:

• The proposed observer-based adaptive control scheme effectively compensates for sensor faults in uncertain nonlinear systems.
• The method guarantees fixed-time convergence of tracking and observation errors, enhancing system reliability.
• This approach offers a significant advancement in fault-tolerant control for complex dynamic systems.