Fault tolerant control for strict-feedback nonlinear system via event-triggered adaptive algorithms.

Area of Science:

• Control Systems Engineering
• Nonlinear Dynamics
• Robotics

Background:

• Strict-feedback nonlinear systems are susceptible to actuator faults and parameter uncertainties, complicating control design.
• External disturbances further degrade system performance and stability.
• Existing fault-tolerant control methods often require continuous communication, which is inefficient.

Purpose of the Study:

• To develop an event-triggered adaptive fault-tolerant tracking control strategy for strict-feedback nonlinear systems.
• To address challenges posed by mismatched unknown parameters, external disturbances, and actuator faults.
• To ensure system signal boundedness and achieve arbitrary small output tracking errors.

Main Methods:

• A novel adaptive fault-tolerant mechanism using discrete-state parameter estimators governed by a state-dependent event-triggered mechanism.
• Introduction of auxiliary dynamics to guarantee signal boundedness.
• Development of robust event-triggered mechanisms and adaptive algorithms, proven to be Zeno-free.

Main Results:

• All system signals are ultimately bounded.
• Asymptotic output tracking error is within an arbitrarily small residual set.
• The proposed event-triggered mechanisms are demonstrated to be Zeno-free, reducing communication load.
• Control effectiveness verified through numerical simulations and a single-link manipulator example.

Conclusions:

• The proposed event-triggered adaptive fault-tolerant control strategy effectively manages actuator faults and parameter uncertainties in nonlinear systems.
• The method enhances system robustness and tracking performance while minimizing communication requirements.
• The approach offers a practical solution for fault-tolerant control in complex dynamic systems.