FOGI-based fault prognosis and tolerant control of open-circuit faults in a DAB converter for battery charging applications in EV

T-S fuzzy fault-tolerant load frequency control for power systems with energy storage system under DoS attacks and actuator failures: A two-step adaptive event-triggered mechanism

Distributed bearing-based fault-tolerant formation control of fixed-wing UAV swarm with prescribed performance

Prescribed-time fault-tolerant tracking control for aquatic-aerial unmanned amphibious vehicles

Fault-tolerant group consensus control for hybrid multi-agent systems by observers and event-triggered strategy

Fault-tolerant security control for switched systems via learning observer and DoS attacks

Fuzzy observer-based adaptive fault tolerant control for uncertain underactuated nonlinear systems under TS fuzzy model with unmeasured premise variables

KPCA digital twin-enhanced real-time fault-tolerant control for autonomous vehicles

A finite-time adaptive fault-tolerant control method for a fractional-order ship power system

Adaptive fault-tolerant control of nonlinear systems: A self-regulating spatiotemporal performance approach

Distributed fault-tolerant control for a class of uncertain cascaded ODE-PDE multi-agent systems

Adaptive fuzzy fault estimation and fault-tolerant control method considering sensor and actuator faults for aeroengines

Every summer, wildfires ravage thousands of acres. To respond effectively and reduce the impact, firefighters need real-time monitoring of the fire's progression. This article proposes a novel fixed-time control scheme for a multiple quadcopter uncrewed aerial vehicle (multi-QUAV) system designed to cooperatively monitor the dynamic spread of wildfires, even in the presence of unforeseen actuator faults and dynamic changes in the number of QUAVs due to damage, refuelling, or wildfire expansion. The control scheme integrates a fixed-time sliding mode control method with a fixed-time extended state observer (FxESO) to estimate multi-source perturbations arising from external disturbances, parameter uncertainties and actuator faults. The fixed-time convergence of the collaborative formation tracking error to zero is rigorously proven using Lyapunov theorem. Comparative simulations, benchmarked against three existing control schemes, demonstrate superior convergence speed, reduced overshoot, and improved resilience in wildfire scenarios, highlighting the potential for enhancing emergency response systems. Highlights Fault-tolerant control Wildfire monitoring Time-varying formation tracking

This paper investigates a fixed-time fault-tolerant control problem for the virtually coupled train set subject to the actuator faults, input saturation, external disturbances and parameter uncertainties. A novel fixed-time adaptive sliding mode fault-tolerant control scheme is proposed. By introducing the hyperbolic tangent function, a failure compensation strategy is designed to address the unknown actuator fault without the prior knowledge of fault. Moreover, we estimate the combinations of unknown parameters instead of directly estimating the unknown parameter itself, which significantly saves the computing resources of trains and improves the efficiency. Furthermore, an auxiliary system is introduced to compensate for the influence of input saturation. It guarantees the position and speed tracking errors of each train can converge to the small regions in fixed time in despite of the influence of internal faults and external disturbances, as well as actuator saturation. The proposed control scheme is of great significance to improve the efficiency, safety and reliability of high-speed trains' operation. Finally, simulations are provided to verify the feasibility and effectiveness of the proposed control scheme.

This paper proposes a comprehensive framework for control of an extended Morphing Aerial System (MAS) designed to achieve both mission flexibility and fault tolerance. The proposed quadrotor features a morphing configuration that integrates a two-dimensional planar folding structure with a tilt mechanism. This morphing capability offers structural simplicity and operational versatility, which enables stable flight in various established modes. The control strategy utilizes feedback linearization and a Linear Quadratic Regulator (LQR), adapted to the system’s nonlinear dynamics and capable of controlling the MAS across various configurations (X, H, and O modes). An Extended Kalman Filter (EKF) is also incorporated for state estimation. To ensure fault resilience, we introduce the Y-mode configuration and a corresponding Fault-Tolerant Control (FTC) architecture. Numerical simulations demonstrate that while a nominal controller fails immediately upon motor failure, the proposed FTC method successfully recovers flight stability, converging to the reference trajectory within 6.9 s. Furthermore, robustness analysis confirms that the system maintains operational integrity for fault detection latencies up to 0.40 s, demonstrating its feasibility under realistic sensing constraints.

In this paper, a finite-time command filter-based sliding mode fault-tolerant control (FTCFSMFTC) strategy is developed for uncertain robotic manipulator systems (RMS) with actuator faults (AFs) under interval excitation (IE) conditions. A novel adaptive control algorithm is introduced via integrating the command filter backstepping with sliding mode control in a completely new way, in which the error compensation mechanism of traditional command filter backstepping is eliminated and a fresh integral terminal sliding surface is provided based on system information and the filter output; also, a composite optimal weight estimation method is designed for the unknown dynamics and AFs in RMS. Then, by the FTCFSMFTC law, all signals of RMS are finite-time (FT) bounded, and the trajectory tracking error converges to zero in FT under IE conditions. Finally, the effectiveness of the proposed algorithm is validated through simulation experiments.

This paper investigates the prescribed-time fault tolerant tracking control problem for output-constrained systems. First, a prescribed-time output-constrained function is defined, and a kind of time-varying barrier Lyapunov functions are developed. Then, based on backstepping design scheme and the time-varying barrier Lyapunov functions, a fault tolerant control scheme is designed. It is proved that when the actuator suffers partial failure or fault-free, the proposed control approach can make the trajectory error of output-constrained system tend to zero in a prescribed time with the control signal being bounded. Finally, the prescribed-time fault tolerant tracking control approach is applied to the Mars entry vehicle tracking control under disturbances and a set of numerical simulations demonstrate the validity of the proposed approach.

When disturbances or nonlinearities couple the observer and the controller, implementing active fault-tolerant control (AFTC) via the separation principle (SP) becomes challenging. This article proposes a novel AFTC framework with the goal of decoupling design for a class of uncertain nonlinear systems, thereby recovering the use of SP in AFTC design. An observer is developed for fault diagnosis and state estimation based on the system outputs, and the boundedness of the estimation errors is guaranteed. Next, an active fault-tolerant controller integrated with an adaptive mechanism is constructed for fault accommodation using the obtained fault information. To mitigate bidirectional influences between the observer and controller designs, all estimation errors and disturbances are treated as new disturbances in the AFTC system (AFTCS), and adaptive updating terms are designed to compensate for these disturbances. The stability of the AFTCS is analyzed, ensuring that all signals in the closed-loop system remain bounded and that the output tracking error converges to a neighborhood around zero. The effectiveness of the proposed approach is illustrated through a numerical simulation example.

This paper addresses the coordinated driving control problem of a six-wheeled lunar rover subject to system uncertainties, external disturbances, and actuator faults. A novel fault-tolerant adaptive control framework is developed using fuzzy logic systems to approximate unknown nonlinear dynamics and fault functions. To mitigate tracking errors, a compensatory control term is integrated into the controller design. A rigorous Lyapunov-based stability analysis demonstrates that the proposed scheme ensures the convergence of tracking errors to a small neighborhood around the origin. Furthermore, the tracking performance can be enhanced by appropriately tuning design parameters. The controller design procedure, including parameter selection guidelines, is explicitly presented through a detailed example. Numerical simulations conducted validate the effectiveness and robustness of the proposed control strategy.

Three-phase grid-connected inverters (GCIs) are essential components in distributed generation systems, where the accuracy of current measurement circuits is fundamental for reliable closed-loop operation. Nevertheless, the presence of a DC offset in the measured current can disrupt the regulation of grid currents and significantly degrade system performance. In this work, a fault-tolerant control approach is introduced to counteract the impact of such offset faults through a dedicated current compensation mechanism. The proposed solution is built around two main stages: (i) detecting and isolating DC offset faults that may appear in one or multiple phases of the measured grid currents, and (ii) estimating the fault magnitude and reconstructing the corrected current signal. The offset magnitude is obtained analytically by examining the grid current projected onto the synchronous d-axis at the grid angular frequency, eliminating the need for any additional sensing hardware. Simulation and experimental investigations conducted under several fault scenarios confirm the robustness of the proposed strategy and highlight significant improvements in detection speed and diagnostic accuracy. Conflict of Interest Statement The authors declare no conflicts of interest.