Fault-tolerant Control Scheme Research Articles

Model Free Adaptive Iterative Learning Control Based Fault-Tolerant Control for Subway Train With Speed Sensor Fault and Over-Speed Protection

A model free adaptive iterative learning control based fault-tolerant control (MFAILC-FTC) scheme for subway train speed tracking with speed sensor fault and over-speed protection is proposed. Firstly, the train dynamics is transformed into a compact form dynamic linearization (CFDL) data model by applying the concept of pseudo-partial derivative (PPD). If speed sensor fault occurs, the fault function is approximated by the trained RBFNNs under normal condition and the output data of the train system with fault, which serves as a compensation for the proposed MFAILC-FTC scheme. Then, over-speed protection mechanism is developed to ensure that the train operates within safe speed range. Furthermore, the constraint on traction/braking force is also taken into account. Through rigorous mathematical analysis, it is proved that the proposed MFAILC-FTC method with over-speed protection mechanism can ensure the train speed tracking error converges along the iteration axis, which implies the train operates safely and reliably. Finally, the simulation results further demonstrate the effectiveness of the proposed algorithm. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Subway train as a practical engineering system with short distance between two stations, starts and stops frequently, has the outstanding repetitive operation pattern, and it is unavoidable subject to speed sensor fault, aerodynamic issues, constraint on output speed and traction/braking force. Nevertheless, few works have considered these factors simultaneously, and a lot of data contain valuable operation information are generated during the train operation, this motives the work of this note. On account of the repetitive operation features of subway trains, the control schemes of speed trajectory tracking are handled under MFAILC framework, which is a pure data-driven model free control methodology. By constructing the RBFNNs-based fault function estimation mechanism, a robust compensation term is designed in the fault-tolerant controller. Taking the safe operation of subway trains into account, an over-speed protection term with trigger mechanism is added to the fault-tolerant controller. To further enhance the application, the constraint on traction/braking force is addressed as well. Without requirement of the train dynamics model, the theoretical analyses and simulation results have confirmed the effectiveness and the feasibility of the proposed data-driven control approach. In the future work, we will focus on verifying the proposed control strategy and addressing some other practical problems, for instance, the energy-efficiency and exogenous disturbances during the train operation.

Grid-Forming Inverter Primary Control Using Robust-Residual-Observer-Based Digital-Twin Model

Grid-forming (GFM) inverters with inductor-capacitor (LC) filters are used to interface distributed generation with the grid. However, the GFM inverter systems are prone to incipient multiplicative faults due to the inherent parameter drift phenomenon of the LC filter. Motivated by this scenario, this paper presents a primary active fault-tolerant control (PAFTC) strategy based on the robust-residual-observer-based-digital-twin model (RRODTM) to achieve the fault-tolerant control for the incipient multiplicative faults. The RRODTM is composed of a robust residual observer and a residual-driven compensation controller. Specially, the residual-driven compensation controller is designed by the data-driven method based on the multiplicative uncertainty caused by the incipient multiplicative faults. At the same time, this paper constructs a data-driven-event-trigger mechanism based on stability margin to achieve the plug-and-play (PnP) function of the residual-driven compensation controller. Based on these, the PAFTC strategy improves the control performance online according to the degree of the incipient multiplicative fault. Comprehensive experiments show that compared to well-known control schemes in the literature, the PAFTC strategy improves the power distribution accuracy and transient response speed as well as enhances the robustness of the system.

A GOA-Based Fault-Tolerant Trajectory Tracking Control for an Underwater Vehicle of Multi-Thruster System Without Actuator Saturation

This paper proposes an intelligent fault-tolerant control (FTC) strategy to tackle the trajectory tracking problem of an underwater vehicle (UV) under thruster damage (power loss) cases and meanwhile resolve the actuator saturation brought by the vehicle’s physical constraints. In the proposed control strategy, the trajectory tracking component is formed by a refined backstepping algorithm that controls the velocity variation and a sliding mode control deducts the torque/force outputs; the fault-tolerant component is established based on a Grasshopper Optimization Algorithm (GOA), which provides fast convergence speed as well as satisfactory accuracy of deducting optimized reallocation of the thruster forces to compensate for the power loss in different fault cases. Simulations with or without environmental perturbations under different fault cases and comparisons to other traditional FTCs are presented, thus verifying the effectiveness and robustness of the proposed GOA-based fault-tolerant trajectory tracking design. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This paper is motivated by the actuator saturation problem that exists in the trajectory tracking of an underwater vehicle (UV) when encountering power loss of the thruster system. The fault-tolerance trajectory tracking performance is affected by physical constraints of the vehicle when using the traditional methods as they may deduct excessive kinematic/dynamic requirements during the control process, thus inducing the deviation of the tracking trajectory. Therefore, the refined backstepping as well as the grasshopper optimization (GOA) are combined to eliminate the excess, where the refined backstepping is used to alleviate the speed jumps (kinematic outputs) and the GOA is to control the propulsion forces (dynamic outputs) when facing thruster fault cases. This innovates the industrial practitioners that the control design of the vehicle can be improved to avoid the tracking deviation brought by unsatisfied driving commands under fault cases through embedding optimization algorithms. Moreover, for the specific type of UV studied in this paper used for dam detection, simulations regarding practical dam detection such as the 3D polygonal line trajectory tracking and the frequently occurring UV single-fault cases are chosen, which can serve as references for practitioners working in the related field. In the future, underwater experiments of the UV will be investigated, with more effects of the practical environment involved.

Short-Circuit Fault-Tolerant Topology and Control Strategy for Active Magnetic Bearing Drive Based on Shared Bridge Arm

Short-Circuit Fault-Tolerant Topology and Control Strategy for Active Magnetic Bearing Drive Based on Shared Bridge Arm

Robust adaptive fault tolerant control for nonlinear systems with actuator failure and mismatched disturbance

In this paper, a class of nonlinear systems with mismatched disturbance and actuator failure is investigated. A disturbance observer is proposed to estimate the disturbance first and the error of the estimation converges to zero exponentially. By introducing an integral sliding mode surface, the disturbance observer-based integral sliding mode fault tolerant control scheme is proposed to attenuate the disturbance and guarantee the stability of the system. In particular, the control law is designed for decoupling the partial disturbance and attenuating the disturbance that cannot be decoupled. Finally, two examples are given to illustrate the effectiveness of the proposed method.

An Adaptive Fault-Tolerant Control Scheme for 6-DOF Spacecraft Based on A Control Gain Re-Construction

An Adaptive Fault-Tolerant Control Scheme for 6-DOF Spacecraft Based on A Control Gain Re-Construction

Neural-Network-Based Adaptive Fixed-Time Control for Nonlinear Multiagent Non-Affine Systems.

In this research, the adaptive neural network consensus control problem is addressed for a class of non-affine multiagent systems (MASs) with actuator faults and stochastic disturbances. To overcome difficulties associated with actuator faults and uncertain functions of the designed MAS, a neural network fault-tolerant control scheme is developed. Moreover, an adaptive backstepping controller is developed to solve the non-affine appearance in multiagent stochastic non-affine systems using the mean value theorem. Being different from the existing control methods, the developed adaptive fixed-time control approach can ensure that the outputs of all followers track the reference signal synchronously in the fixed time, and all signals of the controlled system are semi-globally uniformly fixed-time stable. The simulation results confirm that the presented control strategy is effective in achieving control goals.

Sliding Mode Fault-Tolerant Control for Nonlinear High-Order Fully Actuated Systems.

The high-order fully actuated systems (HOFASs) approach can only completely eliminate known nonlinearities. However, the practical systems often encounter unknown nonlinearities, including disturbances and faults. Therefore, this article studies a class of nonlinear HOFAS with component faults and disturbances. By applying the HOFAS theory, a novel integrated sliding mode fault-tolerant control strategy is proposed to ensure the stability of the closed-loop system. The state feedback and output feedback controllers are designed, respectively. For output feedback control, an extended state observer is designed to estimate system states. Once the HOFAS model is established, the designed controller and extended state observer can be directly implemented, facilitating the analysis and design of the control system. And the stability analysis does not depend on the complexity of the nonlinear functions. Finally, a numerical simulation example shows the effectiveness of the proposed method.

Neuro‐Adaptive Finite Time Composite Fault Tolerant Control for Attitude Control Systems of Satellites

AbstractAn adaptive finite time composite fault tolerant control strategy based on an optimized neural network for Attitude control systems (ACSs) of satellites is proposed considering the state time‐varying delays, concurrent actuator and sensor faults, system uncertainties, modelable external disturbance and operating noise. An uncertain time‐varying state space model for ACSs of satellites is established, and sensor faults are equivalent to actuator‐like faults. A disturbance observer is designed for estimating the modelable external disturbance, and an improved dwarf mongoose optimization (DMO) algorithm based on the Levy flight distribution is utilized to optimize the basis function of hyperbasis function neural networks to better estimate the augmented actuator faults that include the actuator fault and the actuator‐like fault. Furthermore, an adaptive finite time composite fault‐tolerant controller is proposed, which includes the delay‐dependent feedback control law, disturbance estimation based‐disturbance compensation law and the adaptive fault compensation law based on the augmented fault estimation using the improved DMO‐hyper basis function neural network. The finite time boundness of the close‐loop dynamics to the uncertainties, operating noise, and augmented actuator faults and the robustness of the measurement to the uncertainties, operating noise and augmented actuator faults are analyzed, and the observer and controller design is formulated as the linear matrix inequalities. Simulation examples for ACSs in different working conditions are considered to exhibit the proposed method's effectiveness.

Fuzzy adaptive time‐varying formation control of USVs with actuator faults

SummaryThis paper investigates the fuzzy adaptive time‐varying formation control problem for fully‐actuated unmanned surface vehicles (USVs) systems. The studied USVs systems include uncertain dynamics and actuator faults. Fuzzy logic systems (FLSs) and disturbance observer are employed to estimate uncertain nonlinear dynamics in system model and external time‐varying disturbances, respectively. Meanwhile, the prescribed performance control (PPC) technique is applied to construct the constraint requirements of collision avoidance and connectivity preservation in time‐varying formation control. Additionally, a new robust adaptive fault‐tolerant control (FTC) algorithm is presented. Hence, by the aid of adaptive backstepping technique with performance functions, a robust fuzzy adaptive time‐varying formation FTC scheme of time‐varying formation is developed. The proposed formation control scheme not only has the advantages of avoiding collision and preserving connectivity, but also ensures all the signals are uniformly ultimately bounded (UUB). Finally, the simulation results are provided to demonstrate the effectiveness of the proposed approach.

Global adaptive neural network control of nonlinear time-varying systems with unknown control coefficients and model uncertainties

This paper investigates the adaptive control problem for the strict-feedback nonlinear time-varying system (NTVS) with unknown control coefficients and model uncertainties. To address the problem that the neural network (NN) can only achieve local approximation of unknown nonlinear functions, a novel NN control scheme is proposed. The scheme consists of a NN controller that operates inside the approximation domain and a robust controller that operates outside the approximation domain, and a novel switching function is designed to enable the two controllers to switch smoothly in the vicinity of the approximation domain to ensure that all signals of the closed-loop system are globally uniformly ultimately bounded. To address the problem that unknown time-varying control coefficients are difficult to handle, an adaptive fault-tolerant control scheme is proposed in combination with the congelation of variables method. The scheme employs classical adaptive control to adapt to the variation of unknown control coefficients and robust control to eliminate the time-varying disturbance terms, and introduces a positive integrable time-varying function to achieve asymptotic tracking of an arbitrary reference signal. The combination of these two schemes constitutes a global adaptive neural network control (GANNC) method for the NTVS with unknown control coefficients and model uncertainties. Finally, an adaptive attitude fault-tolerant controller for launch vehicles is designed by using the GANNC method, which can realize the accurate tracking of the attitude control system to the reference command under normal status, strong disturbances and actuator failures, and comparative experiments prove the effectiveness and superiority of the controller.

Self-triggered fixed-time bipartite fault-tolerant consensus for nonlinear multiagent systems with function constraints on states

This article presents a self-triggered bipartite fault-tolerant consensus control scheme in a fixed-time stability sense for multiagent systems (MASs) with function constraints on states. Neural networks are introduced to identify unknown nonlinearities, thereby relaxing constraints on unknown functions. Then, based on time-varying barrier Lyapunov functions including time and previous states, all states of the considered MASs are constrained to given ranges. In addition, to improve the utilization of system transmission resources, a self-triggered control method in which the next triggering time can be computed according to the current information of the controller is proposed. By applying the Lyapunov theory, the designed self-triggered controller can ensure that all signals containing consensus tracking errors are fixed-time bounded under a given communication topology, and the Zeno phenomenon is successfully avoided. Finally, a practical example is provided to testify the feasibility of the developed control scheme.

Tuning function-based fault-tolerant finite-time control for nonlinear systems with sensor/actuator faults

This paper discusses the adaptive fault-tolerant finite-time control tracking problem for a class of strict-feedback nonlinear systems with multiple faults and disturbances. Our essay focuses on the problem of over-parameterisation in traditional backstepping methods. A new fault-tolerant control scheme is proposed by combining tuning function with fuzzy control technology and finite-time control. This scheme greatly simplifies the process of derivation and computation and avoids high computational cost and high memory consumption. Thus the purpose of improving the reliability and robustness of the system is achieved. Finally, according to the Lyapunov finite-time stability theory, the proposed method can ensure that the closed-loop system remains semi-globally practically finite-time stable and the tracking errors converge to a small neighbourhood near the origin in finite time under the condition of unmatched disturbances and sensor/actuator faults simultaneously. The effectiveness of the proposed control strategy is verified by a simulation example.

Dynamic observer‐based fault estimation and fault‐tolerant control for switched stochastic systems with multiple faults

AbstractThe fault estimation (FE) and fault‐tolerant control (FTC) problems are studied for the switched system with sensor fault, actuator fault, and stochastic noise. The dynamic FE observers are used to reconstruct the system states and faults at the same time. Differently from the classical observer design method, in the process of observers design, both the output information and its derivative are introduced to improve the estimation performance, especially in the case of the systems subject time‐varying fault. Based on the coordinate transformation, the output derivative is not appeared in the observers, which means that the proposed dynamic observers can be used for the cased that the output derivative is unmeasured. Utilizing the estimate information, the observer‐based FTC scheme is given. For any switching signal, the linear matrix inequality (LMI) conditions are provided, which can ensure that the entire system is mean‐square exponentially stable (MSES). Finally, simulation examples show the effectiveness of the observer and controller.

A novel network-based adaptive fault-tolerant control of switched nonlinear systems subject to multiple faults under prescribed performance

It is the first report about fault-tolerant-based prescribed performance control of switched nonlinear systems under multiple faults. The concerned faults include not only external faults but also actuator faults. In the process of backstepping control design, prescribed performance control is fully considered, and the combination of unknown nonlinear functions is estimated by multi-dimensional Taylor network. Finally, the developed adaptive fault-tolerant control strategy guarantees the boundedness of all controlled signals while prescribed tracking performance is satisfied. In an effort to further manifest the validity of the fault-tolerant controller, a numerical simulation and a practical simulation are introduced.

Fault-Tolerant Fuzzy Observer-Based Fixed-Time Tracking Control for Nonlinear Switched Systems

This paper focuses on developing an adaptive output feedback fault-tolerant fixed-time tracking control strategy for a class of switched nonlinear systems with non-affine faults. To approximate the unmeasurable states, a mode-dependent state switched fuzzy observer is generated using fuzzy logic systems and a Butterworth low-pass filter. Next, an adaptive fixed-time tracking control strategy is developed by combining dynamic surface technology with the backstepping method. An improved mode-dependent average dwell time switching rule is also introduced to ensure the stability of switched nonlinear systems with unstable subsystems. A stability analysis proves the effectiveness of the proposed control scheme in stabilizing the switched nonlinear system under mode-dependent average dwell time switching, ensuring that the tracking error reaches the residual set within a derived settling time. Finally, a switched resistor-inductor-capacitor circuit example is provided to demon- strate the validity of the proposed strategy.

Distributed Adaptive Fault-Tolerant Formation-Containment Control With Prescribed Performance for Heterogeneous Multiagent Systems.

This article proposes a distributed adaptive fault-tolerant formation-containment control with prescribed performance for heterogeneous multiagent systems (MASs) consisting of multiple unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) in the presence of actuator faults. First, utilizing the neighborhood formation error information, the distributed fault-tolerant formation control strategy is developed for the trajectory dynamics of each UAV to achieve the formation tracking, that is, all UAVs track the virtual leader and perform the prespecified formation configuration. Then, the adaptive fault-tolerant containment algorithm, independent of the positions of the leaders, is proposed to guarantee the UGVs converge to the convex hull formed by the leader UAVs. The adaptive estimation scheme is constructed to compensate for the unknown system parameters and actuator loss-of-effectiveness and bias faults. The formation-containment tracking performance is analyzed based on Lyapunov theory with the synchronization errors satisfying the prescribed performance. A simulation example based on UAVs-UGVs systems is adopted to verify the effectiveness of the proposed control strategy.

Fixed time adaptive fault tolerant sliding mode control of PEMFC air supply system

Guaranteeing rapid management of oxygen excess ratio (OER) for proton exchange membrane fuel cells (PEMFC) under load variations is a challenge with practical significance. To improve the controller response of PEMFC air supply system, a fixed time fault-tolerant control strategy is proposed in this paper. A fixed convergence time of PEMFC air supply control system is quantified and guaranteed by the proposed method and the control response can be accelerated by reducing the setting time. The contributions of this paper is fourfold. Firstly, the manifold leakage fault is estimated by fixed time fault observer, which can improve the real-time fault tracking performance of the control system. Secondly, a hierarchical fixed time sliding mode controller is proposed to regulate the OER rapidly. Furthermore, a novel adaptive term is employed to reduce the effects of the chattering from fault observer in the outer loop. Finally, the effectiveness of the proposed method is verified on a real-time PEMFC simulation platform. Experimental results on a Hardware-in-the-loop (HIL) platform show that the proposed fixed time fault tolerant control strategy has the characteristics of fast response and high robustness.

Relaxed Stabilization of Event-Triggered Interval Type-2 T–S Fuzzy Positive Systems With Stochastic Actuator Failure

This paper studies the membership-function-dependent (MFD) stability and positivity analysis of positive Interval Type-2 (IT2) Takagi-Sugeno (T-S) fuzzy fault-tolerant control systems under the event-triggered control framework. Considering the fact that parameter uncertainties may exist in nonlinear plants, the IT2 T-S fuzzy model as an effective mathematical tool is employed to approximately express a complex positive system with nonlinearities and uncertainties. In order to save communication resources and improve the security of system operation, an event-triggered fault-tolerant control strategy is then designed based on the Imperfectly Premise Matching (IPM) concept. In addition, for capturing positivity characteristic and matching with the linear co-positive Lyapunov function, a novel event-triggered condition in the 1-norm rather than in the 2-norm is developed to control the positive IT2 T-S fuzzy systems. Thereinto, the non-convex problem as the first obstacle is required to be cleared since feasible solutions usually cannot be obtained based on the non-convex conditions. For dealing with this problem, a valid approach is presented to conduct convexification with the help of a user-chosen constant vector. Besides, because of event-triggered action, the inherent mismatched issue of the premise variables of the fuzzy model and the ones of the fuzzy controller is encountered. Fortunately, the advanced MFD analysis, which is capable of bringing the information contained in the membership functions (MFs) into the stability and positivity conditions, provides an effective strategy to remove this barrier. Consequently, relaxed results which can accomplish the stability and positivity for wider positive systems are developed and displayed in sum-of-squares (SOS) form. Detailed simulation results are given to clarify the effectiveness of the designed event-triggered fault-tolerant control method.

Preface

The International Conference on Mechatronics, Automation and Intelligent Control (MAIC) has confirmed once again this year the enthusiasm and determination of students and young researchers to play a major role in the scientific progress. Since 2021, we have regularly gathered to discuss the most recent developments and achievement on mechatronics, automation and intelligent control, and we firmly convince that sharing our expertise and experience is the foundation of research activity.The 2023 3rd International Conference on Mechatronics, Automation and Intelligent Control (MAIC 2023) took place from September 15th to 17th, 2023 in Guilin, China (virtual event), attracting about 80 leading delegates from around the world. The format we chose is a formal meeting primarily aimed at graduate students and leading researchers, who were encouraged to present their work through oral or poster presentations that provide genuine engagement of the audience and cross-pollination of ideas. One of the main purposes of the Conference was to create an international network of researchers, both experimentalists and theorists, and fruitful collaborations across different branches of mechatronics, automation and intelligent control.After previous two sessions that strengthened it, the International Conference on Mechatronics, Automation and Intelligent Control was held for the third time. It was a three-day Conference. The success of this year’s event was testified by an increased number of participants and institutions all around the world. This resulted in an extremely rich and interactive keynote speech, oral and poster session that covered several areas related to mechatronics, automation and intelligent control.With the intent of broadening the contents and stimuli adopting academic communication, the keynote speech part was held. This choice reflected the growing importance of the activity performed by scientists and researchers, especially at the earliest stages of their career, as a way of increasing their expertise and developing soft skills. During the meeting, Prof. Xingjian Wang from Beihang University, China shared with us his research on Fault Diagnosis and Fault-tolerance Control for Aircraft Control System. In order to realize the highly reliable and healthy service of the aircraft control system, the health status assessment and remaining useful life prediction of the key components of the aircraft control system, the key technology of fault diagnosis for the airborne hydraulic system, and the high safety hierarchical active fault-tolerance control strategy were carried out to effectively improve the healthy service capability of the aircraft control system.This paper volume cover topics on Industrial Robots and Automatic Production Line, Automatic Control Technology, Intelligent Fault Detection and Identification, Man-Machine Interactions, etc. Given the recent experimental achievements in mechatronics, automation and intelligent control, several contributions were focused on the latest results obtained in these fields, presenting the impact of experiments to the community of young researchers and forecasting the future goals in these areas of research.The organizers of MAIC 2023 would like to thank all the keynote speakers, authors, peer reviewers, and everyone who contributed to the Conference. We owe gratitude to all the Committee members for providing necessary help and support throughout the meeting. The publication of the Proceedings of this Conference is supported by Journal of Physics: Conference Series.The Committee of MAIC 2023List of Committee Member is available in this pdf.