Hybrid Fault-tolerant Control Research Articles

Design of hybrid fault-tolerant control system for air-fuel ratio control of internal combustion engines using artificial neural network and sliding mode control against sensor faults

This paper proposes a novel hybrid fault-tolerant control system (HFTCS) with dedicated non-linear controllers: artificial neural network (ANN) and sliding mode control (SMC) for active and passive parts, respectively. The proposed system can provide both desirable properties of stability to unexpected fast disturbances and post-fault optimal performance. In the active fault tolerant control system (AFTCS) part, the fault detection and isolation (FDI) unit is designed through the use of ANN for the estimation of faulty sensor values in the observer model. In the passive fault-tolerant system (PFTCS) part, the air-fuel ratio (AFR) controller is designed using a robust SMC that allows systems to manage faults in predefined limits without estimation. In the proposed system, SMC will form the passive part to react instantly to faults while ANN will optimize post-fault performance with active compensation. Moreover, Lyapunov stability analysis was also performed to make sure that the system remains stable in both normal and faulty conditions. The simulation results in the Matlab/Simulink environment show that the designed controller is robust to faults in normal and noisy measurements of the sensors. A comparison with the existing works also demonstrates the superior performance of the proposed hybrid algorithm.

Hybrid Fault-Tolerant Control for Air-Fuel Ratio Control System of Internal Combustion Engine Using Fuzzy Logic and Super-Twisting Sliding Mode Control Techniques

Safety and critical applications employ fault-tolerant control systems (FTCS) to increase reliability and availability in the event of a failure of critical components. Process facilities may employ these technologies to cut down on production losses caused by equipment failures that occur on an irregular or unscheduled basis. Air–fuel ratio (AFR) adjustment in the fuel system of internal combustion engines (ICE) is crucial for enhancing engine efficiency, saving fuel energy, and safeguarding the environment. This paper proposes a novel hybrid fault-tolerant control system (HFTCS) for controlling the AFR in ICEs that combines the features of both an active fault-tolerant control system (AFTCS) and a passive fault-tolerant control system (PFTCS). The fault detection and isolation (FDI) unit is designed using fuzzy logic (FL) as part of an AFTCS to give estimated sensor values to the engine controller when the sensor becomes faulty. Super-twisting sliding mode control (ST-SMC) is implemented as part of a PFTCS to maintain AFR by adjusting the throttle actuator in the fuel supply line under faulty conditions. Lyapunov stability analysis is also performed to make sure that the system remains stable in both normal and faulty conditions. According to the results in the Matlab/Simulink environment, the suggested system stays robust and stable during sensor faults. In faulty situations, it also maintains the AFR at 14.6 without any degradation, and a comparison with previous studies is carried out. The study shows that the suggested approach is an innovative and highly dependable solution for AFR control in ICEs, preventing engine shutdown and output loss for higher profitability.

Design of a Hybrid Fault-Tolerant Control System for Air–Fuel Ratio Control of Internal Combustion Engines Using Genetic Algorithm and Higher-Order Sliding Mode Control

Fault-tolerant control systems (FTCS) are used in safety and critical applications to improve reliability and availability for sustained operation in fault situations. These systems may be used in process facilities to reduce significant production losses caused by irregular and unplanned equipment tripping. Internal combustion (IC) engines are widely used in the process sector, and efficient air–fuel ratio (AFR) regulation in the fuel system of these engines is critical for increasing engine efficiency, conserving fuel energy, and protecting the environment. In this paper, a hybrid fault-tolerant control system has been proposed, being a combination of two parts which are known as an active fault-tolerant control system and a passive fault-tolerant control system. The active part has been designed by using the genetic algorithm-based fault detection and isolation unit. This genetic algorithm provides estimated values to an engine control unit in case of a fault in any sensor. The passive system is designed by using the higher-order sliding mode control with an extra fuel actuator in the fuel supply line. The performance of the system was tested experimentally in MATLAB/Simulink environment. Based on the simulation results, the designed system can sustain the AFR despite sensor failures. A new method of managing the AFR of an IC engine has been demonstrated in this study, and it is highly capable, robust, reliable, and highly effective. A comparison with the existing works found in the literature also proves its superior performance. By inserting the fault in each sensor, it was clearly observed that proposed HFTCS was much better than the existing model as it was more fault-tolerant due to its ability to work in both online and offline modes. It also provided an exact value of 14.6 of AFR without any degradation.

A comprehensive review of fault diagnosis and fault-tolerant control techniques for modular multi-level converters.

Many faults occur in the modular multi-level converters (MMCs), including unbalancing capacitor voltage, lower and upper arm unbalancing, the line to line voltage unbalancing, sensors and actuators fault, system fault, and sub-modules fault in high as well as medium voltage applications. Several fault-tolerant approaches are presented to overcome these problems, such as active fault-tolerant control system (AFTCS), passive fault-tolerant control system (PFTCS), hybrid fault-tolerant control system (HFTCS), redundant system technique, special power circuit with the controller, and zero sequence voltage methods, which we will explain extensively in this article. This review emphasizes the types of faults in the MMCs and discusses the protection methods under failure conditions. The MMC is more popular in high voltage applications because it not only improves the quality of the grid but also has good harmonic performance in high power transmission. There is no need for any isolated dc sources to operate it. When faults are removed, the efficiency and reliability of the system will be increased. This extensive explanation of the current literature on MMC fault diagnosis and control techniques will conclude which methods provide a more valuable solution. Finally, this paper discusses the best approach to reduce MMC faults and provides a future research direction to the readers.

Adaptive data-driven fault-tolerant control strategy for optimal power extraction in presence of broken rotor bars in wind turbine

Broken rotor bars of a Squirrel Cage Induction Generator (SCIG) impact significantly the quality and quantity of produced electrical energy from Wind Energy Conversion Systems (WECS) because: (1) they change the characteristics of SCIG entailing the invalidity of the designed Maximum Power Point Trucking (MPPT) control and pitch angle control, (2) they increase mechanical and thermal stresses, as well as the harmonic content in stator currents. Therefore, this paper proposes an efficient fault tolerant control strategy in order to mitigate the aforementioned consequences. This strategy is based on a hybrid (mechanic-electric) fault tolerant control (FTC) allowing obtaining optimal power extraction in presence of broken rotor bars. A failure (one or two broken bars) is detected in early stage based on the use of a data-driven (machine learning) approach. The latter uses a discriminative feature space (frequency and magnitude of stator harmonic currents) in order to represent and separate the normal operation mode from faulty modes (broken bars). Simulations using MATLAB demonstrated a nominal current in healthy rotor bars in wind turbine operation zone-3 and new optimal power extraction despite one or two broken bars.

Design of an Improved Hybrid FTC for Faults in Aero-Engine Closed-Loop Control System

Due to the aero-engines in a high temperature, pressure, and spool speed environment, the concurrent faults in actuator/sensor combined with degradation of the aero-engine could arise the problem of closed-loop instability during the flight. For this purpose, an improved hybrid fault-tolerant control (FTC) technique has been studied in this paper to deal with simultaneous failure of actuators and sensors associated with health parameters of the typical components’ degradation in aero-engines. The improved hybrid FTC structure combined with the nonlinear thermodynamic component-level (NCL) model-based estimation method merges fault estimation of actuators/sensors and typical components’ degradation estimation process into the FTC process. A robust H ∞ state feedback controller under the disturbance of simultaneous actuator and sensor faults is designed in the proposed method, together with the switching algorithm serving for the fault estimation and improved hybrid FTC channels. In order to show the feasibility of the proposed method, several semiphysical experiments are engaged to illustrate that the improved hybrid FTC structure can save the tolerant-control time and improve performance of the control system.

A hybrid fault-tolerant control strategy for four-wheel independent drive vehicles

In this paper, a hybrid fault-tolerant control strategy is putted forward to improve the stability of the four-wheel independent drive (4WID) electric vehicle with motor failures. To improve the handling performance of the vehicle with in-wheel motor failures, the faults of in-wheel motors are analyzed and modeled. Then, a model reference adaptive fault observer was designed to observe the faults in real-time. Based on the observation results, there are designed a model predictive control (MPC) based high-performance active fault-tolerant control (AFTC) strategy and a sliding mode control based high-robust passive fault-tolerant control (PFTC) strategy. However, the fault observation results may not always be accurately. For this circumstance, a hybrid fault-tolerant control strategy was designed to make the control method find a balance between optimality and robustness. Finally, a series of simulations are conducted on a hardware-in-loop (HIL) real-time simulator, the simulation results show that the control strategy designed in this paper is effectiveness.

Fuzzy Adaptive Hybrid Compensation for Compound Faults of Hypersonic Flight Vehicle

Based on the adaptive control technique, this study investigates the active-passive hybrid fault-tolerant control (FTC) for hypersonic flight vehicles (HFVs) with compound faults, including system and actuator faults. System and actuator compound faults are defined in multi-augmented Takagi-Sugeno fuzzy HFV systems. Indirect passive compensation factors shield the system faults. An observer with adaptive learning rates that combine fault magnitude and fuzzy premise variable is then designed to estimate actuator faults, where a novel bionic variable parameter algorithm improves the sensitivity and accuracy of fault estimation to the incipient fault deviations. Hence the fault-tolerant controller actively compensates for the actuator faults by using estimated information while shielding the system faults. Finally, the improved adaptive active-passive hybrid FTC for compound faults are completed, and the system’s robust stability is proven. Simulation results are provided to illustrate the effectiveness of the proposed FTC scheme.

Active fault-tolerant control of a Schon̈flies parallel manipulator based on time delay estimation

Abstract In this paper, a new hybrid fault-tolerant control (FTC) strategy based on nonsingular fast integral-type terminal sliding mode (NFITSM) and time delay estimation (TDE) is proposed for a Schönflies parallel manipulator. In order to detect, isolate, and accommodate actuator faults, TDE is used as an online fault estimation algorithm. Stability analysis of the closed-loop system is performed using Lyapunov theory. The proposed controller performance is compared with conventional sliding mode and feedback linearization control methods. The obtained results reveal the superiority of the proposed FTC based on TDE and NFITSM.

Hybrid Adaptive Fault-Tolerant Control for Compound Faults of Hypersonic Vehicle

This study investigates the hybrid fault-tolerant control (FTC) for hypersonic flight vehicles (HFVs) under the rudder structure fault (RSF) and rudder angle deviation fault (RADF). The nonlinear equations of the model are linearised by fuzzy logic, the external nonlinear disturbance is approximated by radial basis functions, which transforms the classical HFV into a linear system. In the case of only a RSF, the state feedback system can passively shield the fault using a compensation function and design a threshold to create conditions for RADF detection. During the RSF and RADF compound faults, the system with an adaptive observer implements angle deviation fault isolation/estimation and shields the structural fault. By using the estimation results, active-passive hybrid compensation completes passive FTC of the structural fault and active FTC of the angle deviation fault. The adaptive learning rates that mimic animal predatory behaviour increase the sensitivity to incipient deviation of RADF and improve compensation. Lyapunov method proves the stability and semi-physical simulation shows the control efficiency.

Research on static fault-tolerant control method of thruster based on MPC

To ensure that the unmanned underwater vehicles (UUVs) can still successfully complete the corresponding tasks in the case of thrusters having faults, a novel fault-tolerant control strategy which combines the model predictive control (MPC) algorithm and the fault-tolerant reconstruction algorithm is presented in this paper. Firstly, a cascade control method based on model predictive control algorithm is introduced, and then the problem when the thrusters in the faulty condition are discussed. For different degrees of thruster fault, the method of weighted pseudo inverse and quantum particle swarm optimization (QPSO) is used for hybrid fault-tolerant control (FTC). At the same time, to overcome the limitations brought by the pseudo inverse reconstruction algorithm, an optimization criterion with the infinite norm as the cost function is introduced into the QPSO algorithm to accelerate the search for the optimal solution in the feasibility space so as to ensure the feasibility of the solution. The simulation results show that the fault-tolerant control method proposed based on MPC (FTC-MPC) in this paper can provide ideal control effects for the unmanned underwater vehicles.

Robust fault tolerant optimal predictive control of hybrid actuators with time‐varying delay for industrial robot arm

AbstractThis paper presents a robust hybrid fault‐tolerant optimal predictive control (HFTPC), for an industrial robot arm under hybrid (electric and pneumatic) actuator faults and/or varying time‐delays. Based on the error dynamics, estimated states, and a predictive controller, a new state feedback control law is proposed and implemented for the reformulation of the optimal control problem of a nonlinear faulty hybrid actuator system based on predictive control via linear matrix inequalities (LMIs). First, a robust MPC scheme is performed in which the future control sequence is used to compensate the varying time‐delays. Then, a robust stable hybrid fault tolerant predivtive control is implemented to handle actuators faults to effect robust trajectory tracking. In fact, the stability of hybrid systems based on the proposed control scheme is a very sensitive criterion. Therefore, stability conditions are required for controlling the industrial arm under faulty hybrid (electric and pneumatic) actuator, based on the Lyapunov‐Krasovskii (L‐K) theory, less conservative stable conditions in terms of LMIs are given and used to ensure the asymptotically robust stability of closed‐loop constrained system that dependent delay‐range. To highlight the robustness and effectiveness of the proposed approach, a simulation study of an industrial robot arm example is proved, where the results showed the prompt and the accuracy of the proposed scheme.

A Hybrid Fault-Tolerant Control for Nonlinear Active Suspension Systems Subjected to Actuator Faults and Road Disturbances

This paper proposes a hybrid fault-tolerant control strategy for nonlinear active suspension subjected to actuator faults and road disturbances. First, an augmented closed-loop system model is established for the nonlinear active suspension system with the actuator faults and road disturbances. Then, based on this model, a hybrid fault-tolerant controller that consists of a nominal state-feedback controller and a robust H∞ observer is proposed to stabilize the control plant under fault-free condition and further compensate for the suspension performance loss under the actuator fault condition. Finally, a half-vehicle active suspension example is exploited to demonstrate the effectiveness of the proposed hybrid fault-tolerant controller under various running conditions.

Hybrid Robust H2/H∞ Fault-Tolerant Control with Random Delay NCS

In this paper, a hybrid fault-tolerant control method with off-line design and online scheduling is proposed for NCS with actuator faults, random delay, and external finite energy disturbance. The problem of less conservatism of robust generalized H2/H∞ hybrid fault-tolerant control is studied. Firstly, a closed-loop fault model of the system with random delay parameters was established according to the Bernoulli 0-1 distribution; all possible prior faults are divided into a few intervals according to certain rules, and then an interval fault-tolerant controller is designed off-line according to the prior faults of each interval. Secondly, when the fault is estimated online, the corresponding interval fault-tolerant controller is called through the scheduling mechanism to achieve rapid fault tolerance of prior faults within the interval and mitigate the impact of other faults within the interval, which provides a guarantee for subsequent safe reconstruction control. Finally, the effectiveness of the proposed method is verified by Matlab simulation.

Nonlinear Adaptive Hybrid Compensation for Actuator-Sensor Compound Faults of Non-Gaussian Uncertain Systems

This paper presents a hybrid fault-tolerant control (FTC) method to handle actuator-sensor compound faults in non-Gaussian uncertain stochastic systems with approximation errors. Considering that multi-source nonlinearities of a class of stochastic systems cannot be approximated by a unified method, fuzzy logic is used to linearize nonlinear parameters, and the Lipschitz condition helps to proof the stability of FTC systems with nonlinear sensing functions. Moreover, to handle compound faults, an adaptive hybrid fault compensation scheme is devised. When only a sensor fault occurs, the feedback contains the fault information, and a feedback error composite function in the controller direct compensates the fault passively. When multiple actuator faults and a sensor fault occur, an adaptive fusion observer simultaneously implements sensor fault masking and actuator fault estimation, and then an active-passive hybrid FTC algorithm uses a compensation function and fault estimation to perform both passive compensation of the sensor fault and active FTC of actuator faults. Furthermore, an adaptive algorithm that resembles the animal predation behavior makes the controller more sensitive to incipient fault deviations. Lyapunov functions prove the robust stability of the proposed fault tolerant systems with approximation errors, and simulation experiment verifies the performance compared to a state-of-the-art method.

Optimized SVM and Remedial Control Strategy for Cascaded Current-Source-Converters-Based Dual Three-Phase PMSM Drives System

In this article, the switching strategy and the remedial control scheme are studied for the cascaded current-source converters (CSCs) fed dual three-phase permanent-magnet synchronous motor (PMSM) variable-speed drives. An optimized space vector modulation (SVM) strategy is proposed to reduce the DC-link current ripple for the proposed drives system. In particular, this switching strategy can work effectively for motor drives under low speed with low back EMF, where there exists a large voltage difference between peak voltage values on the grid side and the motor side. Apart from that, a hybrid fault-tolerant control scheme is also designed for the open-phase fault in dual three-phase PMSM drives system, aiming at achieving small DC-link current ripple and torque ripple, low copper loss, and machine-friendly waveform quality. With the proposed optimized SVM and the hybrid fault-tolerant control strategy, the DC-link current ripple of the cascaded CSCs system can be effectively reduced and good operational performance can be obtained under both normal operation condition and open-phase fault condition. Experimental results are provided to verify the effectiveness of the proposed methods.

Hybrid fault tolerant control for air–fuel ratio control of internal combustion gasoline engine using Kalman filters with advanced redundancy

In this paper, a hybrid fault tolerant control system is proposed for air–fuel ratio control of internal combustion gasoline engines based on Kalman filters and triple modular redundancy. Hybrid fault tolerant control system possesses properties of both active fault tolerant control system and passive fault tolerant control system. As part of active fault tolerant control system, fault detection and isolation unit is designed using Kalman filters to provide estimated values of the sensors to the engine controller in case of faults in the sensors. As part of passive fault tolerant control system, a dedicated proportional–integral feedback controller is incorporated to maintain air–fuel ratio by adjusting the throttle actuator in the fuel supply line in faulty and noisy conditions for robustness to faults and sensors’ noise. Redundancy is proposed in the sensors and actuators as a simultaneous failure of more than one sensor, and failure of the single actuator will cause the engine shutdown. Advanced redundancy protocol triple modular redundancy is proposed for the sensors and dual redundancy is proposed for actuators. Simulation results in the MATLAB Simulink environment show that the proposed system remains stable during faults in the sensors and actuators. It also maintains air–fuel ratio without any degradation in the faulty conditions and is robust to noise. Finally, the probabilistic reliability analysis of the proposed model is carried out. The study shows that the proposed hybrid fault tolerant control system with redundant components presents a novel and highly reliable solution for the air–fuel ratio control in internal combustion engines to prevent engine shutdown and production loss for greater profits.

Adaptive Minimum-Entropy Hybrid Compensation for Compound Faults of Non-Gaussian Stochastic Systems

This study investigated minimum-entropy hybrid fault-tolerant control (FTC) theory for non-Gaussian stochastic systems with compound faults. After fuzzy linearization for the singular systems, the output probability density function (PDF) is generated by rational square root B-splines. To deal with the compound faults consisting of single sensor fault and intermittent multiple actuator faults, an active-passive hybrid adaptive FTC scheme is proposed: A passive compensation function can directly reconstruct the algorithm to mask the sensor fault; then, actuator fault estimation accurately tracks the multiple actuator faults. Hence, the hybrid FTC combines estimated information and passive compensation simultaneously implements active actuator fault repair and passive sensor fault shielding. A novel variable parameter algorithm that mimics animal predation behavior is designed and incorporated into learning rates, making the controller more sensitive to the incipient deviations in actuator faults. Finally, with the optimal indicators containing entropy and mean of non-Gaussian PDF, the minimum-entropy FTC is achieved. Lyapunov and indicator functions prove the stability, simulation verifies the effectiveness of the methods.

A Hybrid Fault-Tolerant Strategy for Severe Sensor Failure Scenarios in Late-Stage Offshore DFIG-WT

As the phase current sensors and rotor speed/position sensor are prone to fail in the late stage of an offshore doubly-fed induction generator based wind turbine (DFIG-WT), this paper investigates a hybrid fault-tolerant strategy for a severe sensor failure scenario. The phase current sensors in the back-to-back (BTB) converter and the speed/position sensor are in the faulty states simultaneously. Based on the 7th-order doubly-fed induction generator (DFIG) dynamic state space model, the extended Kalman filter (EKF) algorithm is applied for rotor speed and position estimation. In addition, good robustness of this sensorless control algorithm to system uncertainties and measurement disturbances is presented. Besides, a single DC-link current sensor based phase current reconstruction scheme is utilized for deriving the phase current information according to the switching states. A duty ratio adjustment strategy is proposed to avoid missing the sampling points in a switching period, which is simple to implement. Furthermore, the additional active time of the targeted nonzero switching states is complemented so that the reference voltage vector remains in the same position as that before duty ratio adjustment. The validity of the proposed hybrid fault-tolerant sensorless control strategy is demonstrated by simulation results in Matlab/Simulink2017a by considering harsh operating environments.

An adaptive approach for the fault tolerant control of a nonlinear system

In this paper hybridisation between two optimisation methods such as modified bacterial foraging optimisation algorithm (MBFOA) and adaptive neuro fuzzy inference system (ANFIS) is presented for determining the optimal proportional-integral (PI) controller parameters, for fault tolerant control (FTC) in an wind energy conversion system (WECS). Initially, detection and diagnosis of fault is performed by the ANFIS. The wind turbine actual output performance and the estimated output values are given as an input to the ANFIS. The residuals, which are the outputs of ANFIS is used for deciding, whether the signal is a fault signal or a non-fault signal, which utilises the knowledge-based computation technique. By using the step size modified bacterial foraging optimisation algorithm-based FTC, the gain parameters are optimised based on the occurrence of fault. Then the proposed hybrid fault tolerant control model is implemented in the MATLAB/SIMULINK platform and the effectiveness is analysed by comparing with the other techniques. The comparison results demonstrate the superiority of the proposed approach and confirm its potential in controlling the fault in a WECS.