Fault-Tolerant Control Techniques for Nonlinear Dynamic Systems
Summary
Fault-tolerant control for nonlinear dynamic systems has matured into a multidisciplinary field combining robust control theory, advanced estimation and diagnostic techniques. Its aim is to maintain stability and performance despite sensor or actuator faults, structural degradations or external disturbances. Active strategies employ on-line fault detection and controller reconfiguration to compensate faults dynamically, while passive methods leverage inherent system robustness to withstand specified fault conditions without reconfiguration. Hybrid approaches integrate both paradigms to achieve resilience across a wider range of fault scenarios. Recent trends emphasise model-based observers, fuzzy logic and machine learning to tackle nonlinearity and uncertainty, underpinned by Lyapunov and sliding-mode analyses to guarantee stability. Applications span aerospace flight control, renewable energy systems, automotive powertrain management and industrial process plants, where uninterrupted operation and safety are paramount. The coupling of fault diagnosis with adaptive control and analytical-redundancy schemes is enabling controllers to detect, isolate and accommodate faults in real time, thereby reducing downtime and extending system life.
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Fault-Tolerant Control Techniques for Nonlinear Dynamic Systems publication trend
The graph below shows the total number of articles in fault-tolerant control techniques for nonlinear dynamic systems across all publications each year (not limited to Nature Index journals).
Technical terms
Fault-tolerant control (FTC): A control framework designed to maintain system stability and performance in the presence of component faults or failures.
Active FTC: An approach that incorporates on-line fault detection and controller reconfiguration to compensate faults dynamically.
Passive FTC: A design that embeds robustness into the control law, enabling tolerance to specified faults without altering controller parameters.
Fault detection and isolation (FDI): Techniques for identifying the occurrence, type and location of faults in sensors or actuators.
Fuzzy logic system: A modelling and inference structure that deals with uncertainty and nonlinearity by using linguistic rules and membership functions.
Sliding mode observer: A robust estimation scheme employing discontinuous injection terms to reconstruct states and fault signals under matched uncertainties.
References
- A Survey on Active Fault-Tolerant Control Systems. Electronics (2020).
- TakagiSugeno Fuzzy Model Based Fault Estimation and Signal Compensation With Application to Wind Turbines. IEEE Transactions on Industrial Electronics (2017).
- Design of Active Fault Tolerant Control System for Air Fuel Ratio Control of Internal Combustion Engines Using Artificial Neural Networks. IEEE Access (2021).
- Adaptive Fuzzy Fault-Tolerant Control against Time-Varying Faults via a New Sliding Mode Observer Method. Symmetry (2021).
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