An extended sensor fault tolerant control method applied to three-phase induction motor drives

This paper proposes a fault diagnosis and tolerant control methods for an open-switch fault caused in a three-phase three-level neutral-point-clamped (NPC) pulse-width modulation (PWM) active rectifier. The open-switch fault in the three-level NPC active rectifier causes a distortion in the input phase current and a ripple in the DC-link capacitor voltage. Therefore, proper fault diagnosis and tolerant control methods are required to prevent additional failures and performance degradation in the rectifier system. This paper conducted a detailed analysis of the effect of the single open-switch fault on the NPC PWM active rectifier and proposed a fault diagnosis method utilizing the DC link voltage and the phase angle of the input grid voltage. Furthermore, this paper proposes a fault-tolerant control method to reduce the effect of the open-switch fault by compensating a distorted reference voltage. The effectiveness of the proposed fault diagnosis and tolerant control methods are verified through experimental results.

A performance comparison between a rareearth and a rare-earth-free five-phase PMa-SynRMs operating at maximum torque per ampere (MTPA) control is present in this paper under different open phase faults. The five-phase machines show inherent higher fault tolerance advantageous over the conventional three-phase machine under different number of open-phase conditions. Ferrite (Fe) magnets are cost effective replacement of the rare-earth material e.g. neodymium (Nd) magnets. Both magnets in PMa-SynRMs show degraded electromagnetic torque characteristics under different open phase faults. Traditional MTPA control method is not able to improve performance under faulty conditions. Advanced fault-tolerant MTPA control method is required to achieve satisfactory performance both under healthy and faulty conditions. In this paper, the fault tolerant control method is modified with MTPA technique to achieve higher performance. The proposed technique is applied on both machines under open phase faults to compare their performances. Detail theoretical analysis is carried out through MATLAB and finite element analysis (FEA). Experimental test results are provided for the Nd-based PMa-SynRM.

Actuator faults of the driving/steering/suspension subsystems may lead to instability in over-actuated electric vehicles. Though many fault tolerant control methods that rely on partial subsystems exist, a novel coordinated fault tolerant control (CFTC) method based on optimal longitudinal/lateral/vertical tyre force distribution is proposed. First, the coordination principle of all the actuator subsystems is explained using vehicle dynamics control equations. Then, an optimal longitudinal/lateral/vertical tyre force distribution method is established. Results of simulations and hardware-in-the-loop (HIL) experiments show that the CFTC method successfully coordinates all the subsystems to compensate actuator faults and effectively improve vehicle stability and safety.

This paper focuses on insufficient perception in blind scenes and the failures of the actuator and sensor of vehicle suspension. The safe speed is designed and the fault-tolerant strategy based on the observer is designed when the actuator and sensor fail simultaneously. A speed planning strategy to ensure that vehicles operate at a safe speed is proposed. The Markov suspension fault jump model considering the suspension sensor and actuator faults is established. Based on the fault estimation obtained by the fault observer, a fault tolerance control strategy of sensor signal reconstruction and actuator fault compensation is adopted. The measurement index for evaluating fault tolerance effectiveness has been established, and an exploration of fault tolerance control is conducted across various fault levels, to identify the preferred fault tolerance strategies corresponding to different levels of fault tolerance. The simulation results show that the designed speed control strategy can improve vehicle safety by decelerating in advance, the fault observer is capable of accurately estimating the true values of actuator and sensor faults. The simulation and vehicle test results demonstrate that similar suspension performance has been obtained by fault-tolerant control strategy and preferred fault tolerance under different fault tolerance levels compared with normal fault tolerance.

This paper investigates an asymptotically stable fault tolerant control (FTC) method for nonlinear continuous-time systems (NCTS) with actuator failures via differential game theory (DGT). Based on DGT, the FTC problem can be regarded as a two-player differential game problem with control player and fault player, which is solved by utilizing adaptive dynamic programming technique. Using a critic-only neural network, the cost function is approximated to obtain the solution of the Hamilton-Jacobi-Isaacs equation (HJIE). Then, the FTC strategy can be obtained based on the saddle point of HJIE, and ensures the satisfactory control performance for NCTS. Furthermore, the closed-loop NCTS can be guaranteed to be asymptotically stable, rather than ultimately uniformly bounded in corresponding existing methods. Finally, a simulation example is provided to verify the safe and reliable fault tolerance performance of the designed control method.

In this article, fault diagnosis and tolerant control methods are proposed for an open-switch fault in a Vienna rectifier. The proposed diagnosis method uses only the input currents to detect an open-switch fault without any additional hardware. In the proposed tolerant control, the offset voltage is used to restore the input currents when an open-switch fault occurs in a Vienna rectifier. In addition, the proposed tolerant control considers the balance of the neutral-point voltage. This method can improve the total harmonic distortion (THD) of the current and mitigate the dc-link voltage ripple. The effectiveness of the proposed open-switch fault diagnosis and tolerant control method is verified by simulated and experimental results.

Loss of control accounts for over 25% of aircraft accidents worldwide. This study presents a fault tolerant flight control strategy for increasing aircraft safety. The work has been undertaken within the Action Group on fault tolerant control (FTC) of the European GARTEUR programme, which develops collaborative efforts in Europe to create new FTC technologies that could significantly advance the goals of the aviation safety. After the fault detection and confirmation by the in-flight dedicated systems, a compensation loop is activated to ensure safe recovery. The design of the FTC loop is achieved without any changes in the nominal (and certificated) flight control system (FCS). The FTC scheme design is formulated as an H∞ strong stabilisation problem. Fault compensability is subsequently discussed and formulated as a trim-deficiency analysis problem. The proposed technique is implemented on the SIMONA flight simulator and evaluated through a pilot experiment. The tested scenario corresponds to the landing approach of a large transport aircraft (B747-100/200). The faulty situation is related to trimmable horizontal stabiliser (THS) failures. Piloted flight simulator experiments show that fault tolerance can be achieved under the condition that there exists sufficient remaining control authority.

Sensor fault-tolerant control for wind turbines: an iterative learning method

Fault probability rises with an increase in the number of current sensors in multi-phase permanent synchronous motor (PMSM) drives. This paper proposes an improved axis rotation method for fault diagnosis and tolerant control to make the multi-phase PMSM drives against current sensor loss signal and gain faults. This method can effectively diagnose and distinguish faults without selecting a threshold value, and the degree of fault can be further estimated. The proposed method makes current sensor fault diagnosis and tolerant control become an integrated module. The validity and accuracy of the proposed method is verified by different fault diagnoses and tolerant control experiments of a 9 kw nine-phase PMSM drive.

This paper investigates the consensus control problem for unknown nonlinear multi-agent systems (MASs) with both sensor and actuator faults. Different from the existing data-driven control methods for unknown nonlinear MASs without faults, a new data-driven adaptive fault-tolerant control (DDC-FTC) method is proposed. Firstly, the data mapping of agents with sensor and actuator faults is established by the locally dynamic linearisation technique. Then, by employing an adaptive fault compensation method, a fault-tolerant controller is designed for unknown nonlinear MASs. Especially, through the stability analysis, it is proven that the consensus tracking error under the designed controller is bounded, where the error bound is related with the parameters in the proposed compensation mechanism, which can be effectively decreased by tuning the parameters. Finally, simulations are given to verify the correctness of the proposed DDA-FTC approach.

Actuator faults have been thought to be one of the most main challenges to be addressed because the system stability can be seriously deteriorated by incorrect actuator actions. Therefore, in this paper, an adaptive neural fault tolerant control (FTC) method is developed for a class of multiple-input-multiple-output (MIMO) uncertain nonlinear systems which are subject to actuator faults and external disturbances. The proposed method utilizes extreme learning machine (ELM) neural networks which are of random hidden nodes to approximate the uncertain modules of systems due to their universal approximation property. Meanwhile, our method does not require prior knowledge of the considered systems outlined, and can effectively compensate for the effects of the actuator faults and external disturbances. Moreover, it is proved that all signals in the closed-loop system remain uniformly ultimately bounded. Finally, simulation results demonstrate the effectiveness of the proposed FTC method.

In this paper, a simple and fast open-phase fault (OPF) detection and fault tolerant control method is proposed for three-phase induction machine. Instead of using integrators or low pass filter, this method utilizes the phase current magnitude and trajectory to detect open phase fault in three-phase motor drive. This significantly increases the speed of fault detection, allowing an OPF to be detected and compensated within several sampling cycles, which is advantageous for safety-critical applications. In addition, a double synchronous reference frame PI (DSRF-PI) controller method is adopted as the fault tolerant controller. Compared to previous methods that utilizes feedforward voltage compensation, the DSRF-PI does not require prior knowledge on the machine parameters and operating condition, and therefore is easier to implement. The proposed fault detection and fault tolerant control method are simulated using MATLAB Simulink simulation where the results confirms the high speed and robustness of the proposed methods.

The problem of fault tolerant shape control for particle size distribution (PSD) process subject to simultaneous time‐varying actuator and sensor faults is studied. In this work, sensor and actuator faults are taken into consideration in a unified framework, and estimated by using adaptive observer technique. For the PSD process, the output distribution, rather than the system output signal itself, is adopted for shape control. Square root rational B‐spline approximation is used to fit the distribution shape. An innovative on‐line fault estimation scheme is proposed for simultaneous actuator and sensor faults estimation. Then an augmented controller based on the virtual actuator and virtual sensor techniques is designed to compensate for the faults and realise PSD shape tracking. A simulation example of emulsion polymerisation is used to validate the proposed scheme and satisfactory performance is obtained.

Thermal protection strategies are employed to protect in-wheel-motors (IWM). Vehicle motions and stability can be affected by such motor thermal protections because they typically reduce the motor output torque to lower motor temperature and protect motor from thermal damage. This paper proposes a fault-tolerant control (FTC) method and a fault-prevention control (FPC) method for vehicle motion control considering motor thermal protection. The FTC method aims to stabilize vehicle motion when motor thermal protection is triggered. A control allocation (CA) algorithm using motor temperature measurement is developed for the FTC method. The output torque constraints can be actively adjusted with motor temperature to include thermal protection strategy in the controller design. When future vehicle trajectories are available, a model predictive control (MPC) FPC algorithm is created to regulate the control efforts in advance to avoid overheating the IWMs that triggers the thermal protection strategy. The proposed methods are validated in CarSim® simulations and the results show that both the FTC and FPC methods can reduce the vehicle yaw rate tracking errors when IWMs are subject to thermal protection strategy.

The unmanned aerial vehicle (UAV) has been developing rapidly recently, and the safety and the reliability of the UAV are significant to the mission execution and the life of UAV. Sensor and actuator failures of a UAV are one of the most common malfunctions, threating the safety and life of the UAV. Fault-tolerant control technology is an effective method to improve the reliability and safety of UAV, which also contributes to vehicle health management (VHM). This paper deals with the sliding mode fault-tolerant control of the UAV, considering the failures of sensor and actuator. Firstly, a terminal sliding surface is designed to ensure the state of the system on the sliding mode surface throughout the control process based on the simplified coupling dynamic model. Then, the sliding mode control (SMC) method combined with the RBF neural network algorithm is used to design the parameters of the sliding mode controller, and with this, the efficiency of the design process is improved and system chattering is minimized. Finally, the Simulink simulations are carried out using a fault tolerance controller under the conditions where accelerometer sensor, gyroscope sensor or actuator failures is assumed. The results show that the proposed control strategy is quite an effective method for the control of UAVs with accelerometer sensor, gyroscope sensor or actuator failures.