Rule-based Fault Diagnosis of Hall Sensors and Fault-tolerant Control of PMSM

Hall sensor is widely used for estimating rotor phase of permanent magnet synchronous motor(PMSM). And rotor position is an essential parameter of PMSM control algorithm, hence it is very dangerous if Hall senor faults occur. But there is scarcely any research focusing on fault diagnosis and fault-tolerant control of Hall sensor used in PMSM. From this standpoint, the Hall sensor faults which may occur during the PMSM operating are theoretically analyzed. According to the analysis results, the fault diagnosis algorithm of Hall sensor, which is based on three rules, is proposed to classify the fault phenomena accurately. The rotor phase estimation algorithms, based on one or two Hall sensor(s), are initialized to engender the fault-tolerant control algorithm. The fault diagnosis algorithm can detect 60 Hall fault phenomena in total as well as all detections can be fulfilled in 1/138 rotor rotation period. The fault-tolerant control algorithm can achieve a smooth torque production which means the same control effect as normal control mode (with three Hall sensors). Finally, the PMSM bench test verifies the accuracy and rapidity of fault diagnosis and fault-tolerant control strategies. The fault diagnosis algorithm can detect all Hall sensor faults promptly and fault-tolerant control algorithm allows the PMSM to face failure conditions of one or two Hall sensor(s). In addition, the transitions between health-control and fault-tolerant control conditions are smooth without any additional noise and harshness. Proposed algorithms can deal with the Hall sensor faults of PMSM in real applications, and can be provided to realize the fault diagnosis and fault-tolerant control of PMSM.

Temperature fault-tolerant control system of CSTR with coil and jacket heat exchanger based on dual control and fault diagnosis

For the characteristics of the continuous stirred-tank reactor(CSTR) with coil and jacket cooling system,a CSTR temperature dual control solution based on the analysis of the CSTR exothermic reaction control characteristic was proposed for an organic material polymerization production.The control solution has passive fault-tolerant ability for the jacket cooling water cutting off fault and active fault-tolerant potential for the coil cooling water cutting off fault,and it has good control ability,high saving energy and reducing consumption performance.Fault detection and diagnosis and fault-tolerant control strategy are designed for the coil cooling fault to achieve the active fault-tolerant control function.The CSTR temperature dual control,process fault detection and diagnosis and active fault-tolerant control were full integrated into the CSTR temperature fault-tolerant control system,which achieve fault tolerance control of CSTR temperature for any severe malfunction of jacket cooling or coil cooling cutting off,and the security for CSTR exothermic reaction is improved.Finally,the effectiveness of this system was validated by semi-physical simulation experiment.

Design and Analysis of Fault Diagnosis and Fault-tolerant Control for a Class of MIMO Nonlinear State Systems

This paper presents a fault diagnosis and fault-tolerant control algorithm,which can be used for a class of multi-input multi-output(MIMO)nonlinear state systems.First,a state estimator is proposed,which is able to detect fault occurrence,by using a residual signal.Second,when the state is at an abnormal condition,the fault-tolerant control will be triggered to minimize the impact of the fault occurrence.This fault-tolerant control is designed by using a robust controller(original controller),and an on-line approximator to capture a nonlinear function that indicates the fault occurrence.The detailed analysis is given for the proposed fault accommodation control.

Fault diagnosis and fault-tolerant control of photovoltaic micro-inverter

An observer-based fault diagnosis method and a fault tolerant control for open-switch fault and current sensor fault are proposed for interleaved flyback converters of a micro-inverter system. First, based on the topology of a grid-connected micro-inverter, a mathematical model of the flyback converters is established. Second, a state observer is applied to estimate the currents online and generate corresponding residuals. The fault is diagnosed by comparing the residuals with the thresholds. Finally, a fault-tolerant control that consists of a fault-tolerant topology for the faulty switch and a simple software redundancy control for the faulty current sensor, is proposed to achieve a fault-tolerant operation. The feasibility and effectiveness of the proposed method has been verified by simulation and experimental results.

A finite-time fuzzy adaptive output-feedback fault-tolerant control for underactuated wheeled mobile robots systems

This paper investigates the adaptive fuzzy finite-time output-feedback fault-tolerant control (FTC) problemfor a class of nonlinear underactuated wheeled mobile robots (UWMRs) system with intermittent actuatorfaults. The UWMR system includes unknown nonlinear dynamics and immeasurable states. Fuzzy logic systems(FLSs) are utilized to work out immeasurable functions. Furthermore, with the support of the backsteppingcontrol technique and adaptive fuzzy state observer, a fuzzy adaptive finite-time output-feedback FTC scheme isdeveloped under the intermittent actuator faults. It is testifying the scheme can ensure the controlled nonlinearUWMRs is stable and the estimation errors are convergent. Finally, the comparison results and simulationvalidate the effectiveness of the proposed fuzzy adaptive finite-time FTC approach.

Backstepping-based active fault-tolerant control for a class of uncertain SISO nonlinear systems

Active fault-tolerant control is investigated for a class of uncertain SISO nonlinear flight control systems based on the adaptive observer, feedback linearization and backstepping theory.Firstly an adaptive observer is constructed to estimate the fault in the faulty system.A new fault updating law is presented to simplify the assumption conditions of the adaptive observer.The asymptotical stability of the observer and the uniform ultimate boundedness of the fault estimation error are guaranteed by Lyapunov theorem.Then a backstepping-based active fault-tolerant controller is designed for the faulty system.The asymptotical stability of the closed-loop system and uniform ultimate boundedness of the tracking error are proved based on Lyapunov theorem.The effectiveness of the proposed scheme is demonstrated through the numerical simulation of a flight control system.

Adaptive fault-tolerant control based on boundary estimation for space robot under joint actuator faults and uncertain parameters

Since the joint actuator of the space robot executes the control instructions frequently in the harsh space environment,it is prone to the partial loss of control effectiveness(PLCE)fault.An adaptive fault-tolerant control algorithm is designed for a space robot system with the uncertain parameters and the PLCE actuator faults.The mathematical model of the system is established based on the Lagrange method,and the PLCE actuator fault is described as an effectiveness factor.The lower bound of the effectiveness factors and the upper bound of the uncertain parameters are estimated by an adaptive strategy,and the estimated value is fed back to the control algorithm.Compared with the traditional fault-tolerant algorithms,the proposed algorithm does not need to predetermine the lower bound of the effectiveness factor,hence it is more in line with the actual engineering application.It is proved that the algorithm can guarantee the stability of the closed-loop system based on the Lyapunov function method.The numerical simulation results show that the proposed algorithm can not only compensate for the uncertain parameters,but also can tolerate the PLCE actuator faults effectively,which verifies the effectiveness and superiority of the control scheme.

Robust and Active Fault-tolerant Control for a Class of Nonlinear Uncertain Systems

A novel integrated design strategy for robust fault diagnosis and fault-tolerant control （FTC） of a class of nonlinear uncertain systems is proposed. The uncertainties considered in this paper are more general than those in other existing works, and faults are described in a new formulation. It is proven that the states of a closed-loop system converge asymptotically to zero even if there are uncertainties and faults in a system. Simulation results on a simple pendulum are presented for illustration.

An Equipment Fault-tolerant Control Expert System and its Application

This paper presents an expert system that can automatically monitor, diagnose and fault-tolerant control by combining fault diagnosis with fault-tolerant technology. The features of the structure of this expert system, knowledge acquisition and organization, and the strategies and realized methods of fault-tolerant control are introduced. An applied example is given.

Novel robust fault diagnosis method for flight control systems

A novel robust fault diagnosis scheme, which possesses fault estimate capability as well as fault diagnosis property, is proposed. The scheme is developed based on a suitable combination of the adaptive multiple model （AMM） and unknown input observer （UIO）. The main idea of the proposed scheme stems from the fact that the actuator Lock-in-Place fault is unknown （when and where the actuator gets locked are unknown）, and multiple models are used to describe different fault scenarios, then a bank of unknown input observers are designed to implement the disturbance de-coupling. According to Lyapunov theory, proof of the robustness of the newly developed scheme in the presence of faults and disturbances is derived. Numerical simulation results on an aircraft example show satisfactory performance of the proposed algorithm.

Output feedback based adaptive robust fault-tolerant control for a class of uncertain nonlinear systems

An adaptive robust approach for actuator fault-tolerant control of a class of uncertain nonlinear systems is proposed.The two chief ways in which the system performance can degrade following an actuator-fault are undesirable transients and unacceptably large steady-state tracking errors.Adaptive control based schemes can achieve good final tracking accuracy in spite of change in system parameters following an actuator fault,and robust control based designs can achieve guaranteed transient response.However,neither adaptive control nor robust control based fault-tolerant designs can address both the issues associated with actuator faults.In the present work,an adaptive robust fault-tolerant control scheme is claimed to solve both the problems,as it seamlessly integrates adaptive and robust control design techniques.Comparative simulation studies are performed using a nonlinear hypersonic aircraft model to show the effectiveness of the proposed scheme over a robust adaptive control based faulttolerant scheme.

Kalman filter based fault diagnosis of networked control system with white noise

The networked control system NCS is regarded as a sampled control system withoutput time-variant delay. White noise is considered in the model construction of NCS. By using theKalman filter theory to compute the filter parameters, a Kalman filter is constructed for this NCS.By comparing the output of the filter and the practical system, a residual is generated to diagnoseme sensor faults and the actuator faults. Finally, an example is given to show the feasibility ofthe approach.

Design and simulation of fault diagnosis based on NUIO/LMI for satellite attitude control systems

This paper presents a scheme of fault diagnosis for flexible satellites during orbit maneuver. The main contribution of the paper is related to the design of the nonlinear input observer which can avoid false alarm arising from the disturbance from orbit control force. The effects of orbit control force on the fault diagnosis system for satellite attitude control systems, including the disturbing torque caused by the misalignments and the model uncertainty caused by the fuel consumed, are discussed, where standard Lu- enberger observer cannot work well. Then the nonlinear unknown input observer is proposed to decouple faults from disturbance, Besides, a linear matrix inequality approach is adopted to reduce the effect of nonlinear part and model uncertainties on the observer. The numerical and semi-physical simulation demonstrates the effectiveness of the proposed observer for the fault diagnosis system of the satellite during orbit maneuver.

Research on Remote Monitoring and Fault Diagnosis Technology of Numerical Control Machine

Based on the internet technology,it has become possible to complete remote monitoring and fault diagnosis for the numerical control machine.In order to capture the micro-shock signal induced by the incipient fault on the rotating parts,the reso- nance demodulation technology is utilized in the system.As a subsystem of the remote monitoring system,the embedded data acquisi- tion instrument not only integrates the demodulation board but also complete the collection and preprocess of monitoring data from different machines.Furthermore,through connecting to the internet,the data can be transferred to the remote diagnosis center and data reading and writing function can be finished in the database.At the same time,the problem of the IP address floating in the dial-up of web server is solved by the dynamic DNS technology.Finally,the remote diagnosis software developed on the Lab VIEW platform can analyze the monitoring data from manufacturing field.The research results have indicated that the equipment status can be monitored by the system effectively.

A fault-tolerant control method for distributed flight control system facing wing damage

With the strong battlefield application environment of the next generation fighter,based on the design of distributed vehicle management system,a fault diagnosis and fault-tolerant control(FTC)method for wing surface damage is proposed in this paper.Aiming at three kinds of wing damage modes,this paper proposes a diagnosis method based on the fault decision tree and forms a fault decision tree for wing damage from the aspects of sample database construction,feature parameter extraction,and fault decision tree construction.Based on the fault diagnosis results,the longitudinal control law based on dynamic inverse and the lateral-directional robust control laws based on linear quadratic regulator(LQR)are proposed.From the simulation examples,the fault diagnosis algorithm based on the decision tree can complete the judgment of three wing surface damage modes within 2 ms,and the FTC law can make the fighter quickly return to a stable flight state after a short transient of 1 s,which achieves the fault-tolerant goal.

Fault-tolerant Control of Nonlinear System Using Credit Assign Fuzzy CMAC

The adaptive fault-tolerant control scheme of dynamic nonlinear system based on the credit assigned fuzzy CMAC neural network is presented. The proposed learning approach uses the learned times of addressed hypercubes as the credibility, the amounts of correcting errors are proportional to the inversion of the learned times of addressed hypercubes. With this idea, the learning speed can indeed be improved. Based on the improved CMAC learning approach and using the sliding control technique, the effective control law reconfiguration strategy is presented. The system stability and performance are analyzed under failure scenarios. The numerical simulation demonstrates the effectiveness of the improved CMAC algorithm and the proposed fault-tolerant controller.

ROBUST FAULT DIAGNOSIS FOR HELICOPTER FCS BASED ON LINEAR PARAMETERVARYING ADAPTIVE OBSERVER

Based on the linear parameter-varying （LPV） adaptive observer, the robust fault diagnosis for a class of LPV systems with external disturbances is studied. Since the flight control system （FCS） is nonlinear and time-varying, the LPV technique is used for FCS. And then the adaptive fault estimation algorithm based on the LPV adaptive observer is proposed to estimate the fault. To minimize the effect of disturbances on the fault estimation, the H~ robust performance index is introduced to design the LPV adaptive fault diagnosis observer and the fault estimation algorithm. The result shows that the method has good estimation performance and is robust to external disturbances. The design method is presented in terms of linear matrix inequalities （LMIs）. Finally, a helicopter LPV FCS model with the actuator fault is used to illustrate the effectiveness of the proposed method.

APPLICATION OF ASSOCIATIVE MEMORY NEURAL NETWORK IN HIGH VOLTAGE TRANSMISSIONLINE FAULT DIAGNOSIS

Effective methods of enhancing the fault-tolerance property are proposed for two kinds of associative memory (AM) neural network (NN) used in high voltage transmission line fault diagnosis. For feedforward NN (FNN),the conception of 'fake attaction region' is presented to expand the attraction region artificially,and for the feedback Hopfield bidirectional AM NN (BAM-NN),the measure to add redundant neurons is taken to enhance NN's memory capacity and fault-tolerance property. Study results show that the NNs built not only can complete fault diagnosis correctly but also have fairly high fault-tolerance ability for disturbed input information sequence. Moreover FNN is a more convenient and effective method of solving the problem of power system fault diagnosis.

Digital Twin-Based Automated Fault Diagnosis in Industrial IoT Applications

In recent years, Digital Twin (DT) has gained significant interestfrom academia and industry due to the advanced in information technology,communication systems, Artificial Intelligence (AI), Cloud Computing (CC),and Industrial Internet of Things (IIoT). The main concept of the DT isto provide a comprehensive tangible, and operational explanation of anyelement, asset, or system. However, it is an extremely dynamic taxonomydeveloping in complexity during the life cycle that produces a massive amountof engendered data and information. Likewise, with the development of AI,digital twins can be redefined and could be a crucial approach to aid theInternet of Things (IoT)-based DT applications for transferring the data andvalue onto the Internet with better decision-making. Therefore, this paperintroduces an efficient DT-based fault diagnosis model based on machinelearning (ML) tools. In this framework, the DT model of the machine isconstructed by creating the simulation model. In the proposed framework,the Genetic algorithm (GA) is used for the optimization task to improvethe classification accuracy. Furthermore, we evaluate the proposed faultdiagnosis framework using performance metrics such as precision, accuracy,F-measure, and recall. The proposed framework is comprehensively examinedusing the triplex pump fault diagnosis. The experimental results demonstratedthat the hybrid GA-ML method gives outstanding results compared to MLmethods like LogisticRegression (LR), Na飗e Bayes (NB), and SupportVectorMachine (SVM). The suggested framework achieves the highest accuracyof 95% for the employed hybrid GA-SVM. The proposed framework willeffectively help industrial operators make an appropriate decision concerningthe fault analysis for IIoT applications in the context of Industry 4.0.