20,659 research outputs found

    Real-time fault diagnosis and fault-tolerant control

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    Fault diagnosis and fault-tolerant control for system with fast time-varying delay

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    This paper proposes a fault diagnosis and fault-tolerant control method for a system with a fast time-varying delay and time-varying parameters. A fault observer is designed to estimate faults, and an improved fast adaptive fault estimation (FAFE) algorithm is developed to reduce the relevant constraints in the general form of this algorithm. With newly introduced relaxation matrices, this study estimates faults in a system exhibiting a fast time-varying delay. Based on the estimated faults, an output feedback controller is designed to accommodate the faults. The fault-tolerant control is realized using the introduced relaxation matrices. An algorithm is derived to solve for the observer and controller. Finally, the theory and method are validated using a real example of a helicopter system

    Fault diagnosis and sustainable control of wind turbines: Robust data-driven and model-based strategies

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    Fault Diagnosis and Sustainable Control of Wind Turbines: Robust Data-Driven and Model-Based Strategies discusses the development of reliable and robust fault diagnosis and fault-tolerant (‘sustainable’) control schemes by means of data-driven and model-based approaches. These strategies are able to cope with unknown nonlinear systems and noisy measurements. The book also discusses simpler solutions relying on data-driven and model-based methodologies, which are key when on-line implementations are considered for the proposed schemes. The book targets both professional engineers working in industry and researchers in academic and scientific institutions. In order to improve the safety, reliability and efficiency of wind turbine systems, thus avoiding expensive unplanned maintenance, the accommodation of faults in their early occurrence is fundamental. To highlight the potential of the proposed methods in real applications, hardware-in-the-loop test facilities (representing realistic wind turbine systems) are considered to analyze the digital implementation of the designed solutions. The achieved results show that the developed schemes are able to maintain the desired performances, thus validating their reliability and viability in real-time implementations. Different groups of readers-ranging from industrial engineers wishing to gain insight into the applications’ potential of new fault diagnosis and sustainable control methods, to the academic control community looking for new problems to tackle-will find much to learn from this work

    An unknown input observer-EFIR combined estimator for electro-hydraulic actuator in sensor fault tolerant control application

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    This paper presents a novel unknown input observer (UIO) integrated extended finite impulse response (EFIR) estimator (UIOEFIR) and its application for an effective sensor fault tolerant control of an electro-hydraulic-actuator (EHA). The proposed estimator exploits the UIO structure in the EFIR filter. Thus, it requires only a small number of historical data (N) whilst ensuring threefold: i) Sensor fault and system-state estimation accuracy under time-correlated noise ii) The number of estimator-design-parameters is significantly minimized. iii) Robust residual generation. A Lyapunov-stability-based theory is carried out to study its convergence condition. Next, an EHAbased test rig has been setup and sensor FTC is performed by carrying this estimator as a part of fault diagnosis algorithm to evaluate its performance by both simulation and realtime experiments. Results highlight that under optimal setting (N = Nopt), the estimator performance is near-accurate to the very-well-developed Extended Kalman Filter-based unknown input observer in an undisturbed condition but significantly outperformed while dealing with time-correlated noise under the same control environment. The estimator also shows its robustness under below-optimal setting (downgrading Nopt by 50%.) while performing in real-time sensor fault-tolerant control

    Hata tanıma ve hata toleranslı kontrol: Destek vektörü makineleri yaklaşımı

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    Because of increasing need for reliability, safety, maintainability and survivability in technological systems, fault tolerant control system has become extremely important. Fault tolerant control systems have been developed to overcome some weaknesses of the conventional feedback control design, such as instability and unsatisfactory performance in the faulty cases. In complex systems such as aircrafts, nuclear power plants, chemical plants etc., the results of a minor fault in the system can be destructive. Therefore, it is necessary to design control systems that are able to tolerate potential faults in these systems. A control system with this kind of fault tolerance capability is defined as fault tolerant control system. A fault tolerant control system is a closed-loop control system which can tolerate malfunctions while maintaining desirable performance and stability properties. A typical active fault tolerant control system includes three sub-systems: reconfigurable controller, fault detection and diagnosis unit and decision supervisor unit. The reconfigurable controller is placed in control loop, instead of regular controller in traditional closed-loop control system. Since the real time toleration of faults can only be achieved if the control system has an automatic reconfiguration mechanism. This reconfiguration is generally activated after a fault has been detected and isolated. A fault detection and diagnosis system is a unit that obtains the occurrence of faults and determines their features in terms of type, location, size and/or time. The decision supervisor activates reconfiguration action in response, which can be pre-determined for each fault or obtained from real time analysis and optimisation. In active fault tolerant control systems, reconfiguration mechanism can be classified as on-line controller selection and on-line controller calculation techniques. In the on-line controller selection approach, the controllers associated with presumed faulty conditions are computed in an off-line manner in the design stage and they are selected in an on-line manner based on the real time information from fault detection and diagnosis algorithm. In the on-line controller calculation approach, the controller parameters are calculated in an on-line manner after the occurrence of fault. In this study, an active fault tolerant control technique, support vector machines based direct fault tolerant control system, is presented. In general, reconfiguration mechanism of a fault tolerant control system utilizes the information from fault detection and diagnosis unit at the decision stage. In the presented method, reconfiguration mechanism and diagnosis unit work independently. Both of them use only real time system outputs. A powerful and fast learning algorithm is needed for this purpose. Support vector machines is one of the most popular intelligent machine learning tools. They have become a very good alternative of neural networks with their superior generalization capacity, classification, regression and modeling performance. In this paper, support vector regression machines have been used in fault detection and diagnosis process and also in reconfigurable controller unit. PID type controllers have been used in reconfiguration sub-system. The PID coefficients of faulty and un-faulty cases to be used in training stage are obtained by genetic algorithm approach in an off-line manner. In reconfiguration mechanism, for each PID coefficient one support vector regression machine is set up. Faulty and un-faulty system outputs are collected for different input signals. In training stage, faulty system outputs and corresponding PID parameters are used as support vector regression machines' inputs and outputs, respectively. Thus the training phase of support vector machines is completed in an off-line manner. After completing the training phase, system is run for the reference input signal. The outputs of system are sent to decision unit periodically. Three of support vector regression machines are simultaneously evaluated the data sent by the system, and produce coefficients of the PID controller. The controller of which its coefficients are reconfigured, starts to work to maintain system performance in an on-line manner. In order to determine the type of fault, a similar process is exploited using one support vector regression machine. In training phase, inputs of this support vector regression machine are faulty and un-faulty system outputs but outputs are the features of the faults. This fault diagnosis unit runs parallel with intelligent fault tolerant controller. The performance of this knowledge based fault diagnosis and active fault tolerant control methods is illustrated on simulation example involving a two-tank water level control system under faulty conditions. Keywords: Fault tolerant control, fault detection and diagnosis, support vector machines, PID controllers, two tank water level system.Geleneksel bir geri-beslemeli kontrol sistemi, bazı arıza durumlarında istenilen başarımı veya kararlılığı sağlamayabilir. Bu tür zayıflıkların üstesinden gelebilmek için, bir yandan istenen kararlılık ve performans özelliklerini sağlayacak bir yandan da elemanların kayıplarını telafi edecek hata toleranslı kontrol tasarım yöntemleri geliştirilmiştir. Geleneksel hata toleranslı kontrol sistemlerinde önce olası hatalar tespit edilir, sonra kararlılığı ve kabul edilebilen bir başarımı sağlayacak yeniden düzenlemeyi gerçekleştirmesi için akıllı bir karar mekanizması devreye girer. Bununla, tespit edilmiş duruma en uygun olan önceden tasarlanmış kontrolör devreye sokulur. Bu çalışmada önerilen destek vektörü makineleri ile doğrudan hata toleranslı kontrol yöntemi, hatanın etkisini giderecek düzenleme yapması için, hata bulma ve tanıma aşamalarına gereksinim duymaz. Bu çalışmada amaç, sistemde oluşabilecek hatanın etkisini sadece sistem çıkışından alınan verilerle çevrim-içi çalışan bir düzenleme ile ortadan kaldırmaktır Bu yöntemde bir akıllı kontrolör sistemi kurulur. Çevrim-dışı gerçekleştirilen eğitimde kullanılacak hatalı durumlara ilişkin kontrolör katsayıları genetik algoritma arama yöntemi ile tespit edilir. PID tipi kontrolör katsayılarının her biri için kurulan destek vektörü bağlanım makinesi, toplanan hatalı ve hatasız sistem çıkışları giriş ve ilgili katsayılar çıkış olacak şekilde eğitilir. Sistem çalışırken belli aralıklarla alınan sistem cevabı karar mekanizması tarafından değerlendirilir. Kontrolör katsayıları, sistem cevabına göre çevrim-içi ayarlanır ve sistemin istenen davranışa götürülmesi sağlanır. Hata tanıma birimi, çıkışı hatanın türü olan bir destek vektörü makinesi ile benzer şekilde oluşturulur ve paralel çalıştırılır. Yöntemin, çift tanklı sıvı seviye sisteminde uygulaması yapılmıştır. Anahtar Kelimeler: Hata toleranslı kontrol, hata bulma ve tanıma, destek vektörü makineleri, PID kontrolör, çift tanklı sıvı seviye sistemi

    Fault-Tolerant Control with Applications to Aircraft Using Linear Quadratic Design Framework

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    Safety is one of the major concerns in the aviation community for both manned aircraft and unmanned aerial vehicles (UAVs). The safety issue of manned aircraft, such as commercial aircraft, has drawn great attentions especially after a series of disasters in recent decades. Safety and reliability issues of UAVs have also attracted significant attention due to their highly autonomous feature towards their future civilian applications. Focusing on the improvement of safety and reliability of aircraft, a fault-tolerant control (FTC) system is demanded to utilize the configured redundancy in an effective and efficient manner to increase the survivability of aircraft in the presence of faults/failures. This thesis aims to develop an effective FTC system to improve the security, reliability, and survivability of the faulty aircraft: manned aircraft and UAVs. In particular, the emphases are focused on improving the on-line fault-tolerant capability and the transient performance between faults occurrence and control re-configuration. In the existing fault-tolerant literature, several control approaches are developed to possess fault-tolerant capability in recent decades, such as sliding mode control (SMC), model reference adaptive control (MRAC), and model predictive control (MPC), just as examples. Different strategies have their specific benefits and drawbacks in addressing different aspects of fault-tolerant problems. However, there are still open problems in the fault-tolerant performance improvement, the transient behavior management, consideration of the interaction between FTC and fault detection and diagnosis (FDD), etc. For instance, MPC is recognized as a suitable inherent structure in synthesizing a FTC system due to its capability of addressing faults via solving constraints, reforming cost function, and updating model on-line. However, this on-line FTC capability introduces further challenges in terms of fault problem formulation, on-line computation, transient behavior before reconfiguration is triggered, etc. Designing an efficient FDD is also a challenge topic with respect to time response speed, accuracy, and reliability due to its interaction with a fault-tolerant controller. In the control design framework based on linear quadratic (LQ) cost function formulation, faults can be accommodated in both passive and active way. A passive FTC system is synthesized with a prescribed degree of stability LQ design technique. The state of the post-fault system is obtained through state-augmented extended Kalman filter (SAEKF), which is a combined technique with state and parameter estimation. In terms of reconfiguration capability, MPC is considered as a favorable active FTC strategy. In addition to MPC framework, the improvement of on-line computational efficiency motivates MPC to be used to perform fault-tolerant flight control. Furthermore, a Laguerre-function based MPC (LF-MPC) is presented to enhance the on-line fault-tolerant capability. The modification is based on a series of Laguerre functions to model the control trajectory with fewer parameters. In consequence, the computation load is reduced, which improves the real-time fault-tolerant capability in the framework of MPC. The FTC capability is further improved for accommodating the performance degradation during the transient period before the control reconfiguration. This approach is inspired by exponentially increasing weighting matrix used in linear quadratic regulator (LQR). Two platforms are used to perform the evaluation of the designed FTC system. A quadrotor UAV, named the Qball-X4, is utilized to test FTC designed with exponentially increasing weighing matrix LQ technique and FDD designed with SAEKF. The evaluation is conducted under the task of trajectory tracking in the presence of loss of control effectiveness (LOE) faults of actuators. The modified MPC is utilized to synthesize an active FTC system to accommodate the elevator stuck fault of a Boeing 747-100/200 benchmark model. The exponentially increasing weighing matrix LQ technique is further implemented in LF-MPC framework to improve the fault-tolerant capability before the control reconfiguration. A time delayed FDD is integrated into the evaluation process to present the effectiveness of the proposed FTC strategies. The designed FTC system is evaluated under the emergency landing task in the event of failure of elevators

    Fault-Tolerant Control with Applications to Aircraft Using Linear Quadratic Design Framework

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    Safety is one of the major concerns in the aviation community for both manned aircraft and unmanned aerial vehicles (UAVs). The safety issue of manned aircraft, such as commercial aircraft, has drawn great attentions especially after a series of disasters in recent decades. Safety and reliability issues of UAVs have also attracted significant attention due to their highly autonomous feature towards their future civilian applications. Focusing on the improvement of safety and reliability of aircraft, a fault-tolerant control (FTC) system is demanded to utilize the configured redundancy in an effective and efficient manner to increase the survivability of aircraft in the presence of faults/failures. This thesis aims to develop an effective FTC system to improve the security, reliability, and survivability of the faulty aircraft: manned aircraft and UAVs. In particular, the emphases are focused on improving the on-line fault-tolerant capability and the transient performance between faults occurrence and control re-configuration. In the existing fault-tolerant literature, several control approaches are developed to possess fault-tolerant capability in recent decades, such as sliding mode control (SMC), model reference adaptive control (MRAC), and model predictive control (MPC), just as examples. Different strategies have their specific benefits and drawbacks in addressing different aspects of fault-tolerant problems. However, there are still open problems in the fault-tolerant performance improvement, the transient behavior management, consideration of the interaction between FTC and fault detection and diagnosis (FDD), etc. For instance, MPC is recognized as a suitable inherent structure in synthesizing a FTC system due to its capability of addressing faults via solving constraints, reforming cost function, and updating model on-line. However, this on-line FTC capability introduces further challenges in terms of fault problem formulation, on-line computation, transient behavior before reconfiguration is triggered, etc. Designing an efficient FDD is also a challenge topic with respect to time response speed, accuracy, and reliability due to its interaction with a fault-tolerant controller. In the control design framework based on linear quadratic (LQ) cost function formulation, faults can be accommodated in both passive and active way. A passive FTC system is synthesized with a prescribed degree of stability LQ design technique. The state of the post-fault system is obtained through state-augmented extended Kalman filter (SAEKF), which is a combined technique with state and parameter estimation. In terms of reconfiguration capability, MPC is considered as a favorable active FTC strategy. In addition to MPC framework, the improvement of on-line computational efficiency motivates MPC to be used to perform fault-tolerant flight control. Furthermore, a Laguerre-function based MPC (LF-MPC) is presented to enhance the on-line fault-tolerant capability. The modification is based on a series of Laguerre functions to model the control trajectory with fewer parameters. In consequence, the computation load is reduced, which improves the real-time fault-tolerant capability in the framework of MPC. The FTC capability is further improved for accommodating the performance degradation during the transient period before the control reconfiguration. This approach is inspired by exponentially increasing weighting matrix used in linear quadratic regulator (LQR). Two platforms are used to perform the evaluation of the designed FTC system. A quadrotor UAV, named the Qball-X4, is utilized to test FTC designed with exponentially increasing weighing matrix LQ technique and FDD designed with SAEKF. The evaluation is conducted under the task of trajectory tracking in the presence of loss of control effectiveness (LOE) faults of actuators. The modified MPC is utilized to synthesize an active FTC system to accommodate the elevator stuck fault of a Boeing 747-100/200 benchmark model. The exponentially increasing weighing matrix LQ technique is further implemented in LF-MPC framework to improve the fault-tolerant capability before the control reconfiguration. A time delayed FDD is integrated into the evaluation process to present the effectiveness of the proposed FTC strategies. The designed FTC system is evaluated under the emergency landing task in the event of failure of elevators

    CAPACITOR VOLTAGE BALANCING, FAULT DETECTION, AND FAULT TOLERANT CONTROL TECHNIQUES OF MODULAR MULTILEVEL CONVERTERS

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    Modular Multilevel Converters (MMCs) are distinguished by their modular nature that makes them suitable for wide range of high power and high voltage applications. However, they are vulnerable to internal faults because of the large number of series connected Sub-Modules. Additionally, it is highly recommended not to block the converter even if it is subjected to internal faults to secure the supply, to increase the reliability of the system and prevent unscheduled maintenance. This thesis introduces a fault tolerant control system for controlling the MMC in normal as well as abnormal operating conditions. This is done through developing a new adaptive voltage balancing strategy based on capacitor voltage estimation utilizing ADAptive LInear NEuron (ADALINE) and Recursive Least Squares (RLS) algorithms. The capacitor voltage balancing techniques that have been proposed in literature are based on measuring the capacitor voltage of each sub-module. On contrary, the proposed strategy eliminates the need of these measurements and associated communication links with the central controller. Furthermore, the thesis presents a novel fault diagnosis algorithm using the estimated capacitor voltages which are utilized to detect and localize different types of sub-module faults. The proposed fault diagnosis algorithm surpasses the methods presented in literature by its fast fault detection capability without the need of any extra sensing elements or special power circuit. Finally, a new Fault Tolerant Control Unit (FTCU) is proposed to tolerate the faults located inside the MMC submodules. The proposed FTCU is based on a sorting algorithm which modifies the parameters of the voltage balancing technique in an adaptive manner to overcome the reduction of the active submodules and secure the MMC operation without the need of full shut-down. Most of fault tolerant strategies that have been proposed by other researchers are based on using redundant components, while the proposed FTCU does not need any extra components. The dynamic performance of the proposed strategy is investigated, using PSCAD/EMTDC simulations and hardware in the loop (HIL) real-time simulations, under different normal and faulty operating conditions. The accuracy and the time response of the proposed fault detection and tolerant control units result in stabilizing the operation of the MMC under different types of faults. Consequently, the proposed integrated control strategy improves the reliability of the MMC

    Pitch angle control with fault diagnosis and tolerance for wind turbine generation systems

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    To enhance the reliability of wind turbine generation systems that are generally located in the remote area and subjected to harsh environment, we design the pitch angle control for variable speed wind turbines with the function of fault diagnosis and fault tolerance. The main fault targeted in this research is the mechanical wear and possible break of the blade, pitch gear set or shaft, which cause shaft rotary friction change. The proposed method uses a disturbance observer to diagnose the fault. The estimated fault is used for component assessment and later maintenance. The fault-tolerant control is achieved using a full-order terminal sliding mode control combined with an adaptive neural network estimator. With the compensation of the adaptive estimator, the post-fault states can be driven onto the sliding surface and converge to a small area around the origin. The full-order terminal sliding mode control ensures the state convergence in finite time. The Lyapunov method is used to derive the control law, so that the closed-loop post-fault stability and the convergence of the adaptive estimator adaptation are both guaranteed. The computer simulations of the pitch angle control based on a 5-MW variable-speed variable-pitch angle wind turbine model are conducted with different types of fault simulated. A third-order nonlinear state space model with fault term is derived, and real physical parameters are applied in the simulations. The simulation results demonstrate the feasibility and effectiveness of the proposed scheme and the potential of real-world applications. © IMechE 2021

    Modelling, Diagnosis, and Fault-Tolerant Control of Open-Circuit Faults in Three-Phase Two-Level PMSM Drives

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    Attributing to the high efficiency, compact structure, and rapid dynamics, powertrains utilizing Permanent Magnet Synchronous Motors (PMSM) have emerged as a promising alternative and have seen extensive deployment in various industrial and transportation sectors, including electric vehicles (EVs), more-electric aircraft, and robotics. Despite ongoing interest in advanced redundant topologies for PMSM drives from both academia and industry, the three-phase two-level (3P2L) PMSM drive continues to dominate the majority of the electric drive market. However, when compared to its multi-phase counterparts, the most-commonly used 3P2L PMSM drive exhibits limited reliability and fault tolerance capabilities, particularly in safety-critical or cost-sensitive scenarios. Therefore, the development of embedded reliability-enhancing techniques holds great significance in enhancing the safety and maintenance of on-site powertrains based on the 3P2L PMSM drive. The purposes of this study are to investigate post-fault system models and develop hardwarefree fault diagnostic and fault-tolerant methods that can be conveniently integrated into existing 3P2L PMSM drives. Special attention is dedicated to the open-circuit fault, as it represents one of the ultimate consequences of fault propagation in PMSM drives. In the first place, the fault propagation from component failures to open-circuit faults is analyzed, and the existing literature on the modelling, diagnosis, and fault-tolerant control of PMSM drives is comprehensively reviewed. Subsequently, the study delves into the postfault system model under the open-phase (OP) fault, which includes the examination of postfault phase voltages and current prediction. Based on the phase voltages observed under the OP fault, a phenomenon of particular interest is modelled: the remaining current that flows through the free-wheeling diodes of the faulty phase under the open-switch (OS) fault. The conduction mechanism is elucidated, and a real-time estimation model is established. Furthermore, a sampling method is designed to enable the motor drive to detect the remaining current in the OS phase, along with a set of diagnostic rules to distinguish between OS and OP faults. Finally, an embedded fault-tolerant control method is introduced to enhance the post-fault speed and torque outputs of 3P2L PMSM drives
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