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  3. Cooperative-critic Learning-based Secure Tracking Control For Unknown Nonlinear Systems With Multisensor Faults.
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  3. Cooperative-critic Learning-based Secure Tracking Control For Unknown Nonlinear Systems With Multisensor Faults.

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Cooperative-Critic Learning-Based Secure Tracking Control for Unknown Nonlinear Systems With Multisensor Faults.

Hongbing Xia, Xiao Wang, Darong Huang

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    View abstract on PubMed

    Summary
    This summary is machine-generated.

    This study introduces a cooperative-critic learning-based secure tracking control (CLSTC) for nonlinear systems with sensor faults. The method effectively handles faults, ensuring system stability and optimal performance.

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    Area of Science:

    • Control Systems Engineering
    • Nonlinear System Analysis
    • Fault-Tolerant Control

    Background:

    • Unknown nonlinear systems are susceptible to multisensor faults, compromising tracking control performance.
    • Existing methods may struggle with online identification of system dynamics and simultaneous fault detection.

    Purpose of the Study:

    • To develop a cooperative-critic learning-based secure tracking control (CLSTC) method for unknown nonlinear systems facing multisensor faults.
    • To achieve robust and optimal secure tracking control with enhanced fault tolerance.

    Main Methods:

    • A low-pass filter transforms sensor faults into pseudo actuator faults.
    • A joint neural network Luenberger observer (NNLO) estimates system dynamics and faults online.
    • An augmented tracking system and a novel cost function are designed for optimal control.
  • The Hamilton-Jacobi-Bellman equation is solved using an adaptive critic structure for the CLSTC strategy.

    • Main Results:

    • The proposed CLSTC method demonstrates effective fault tolerance against various sensor faults.
    • Lyapunov stability theorem confirms the convergence of all closed-loop system signals.
    • Simulation results validate the practical applicability and performance of the control strategy.

    Conclusions:

    • The developed CLSTC method provides a robust solution for secure tracking control in nonlinear systems with multisensor faults.
    • The approach effectively integrates online fault identification and adaptive control for improved system reliability.