Fault-tolerant Control Approach Research Articles

Modified SVPWM Scheme for Fault-Tolerant Control of AC–DC PWM Converter

This article proposes a new SVPWM-based fault-tolerant control (FTC) approach for a three-phase two-level ac-dc converter. Voltage vectors deviation and affected voltage space sectors under faulty conditions are first analyzed. Then, a 12-sector division-based FTC approach is proposed. With the division scheme, sectors affected by faulty switches can be effectively separated from unaffected ones, and SVPWM strategies are implemented to compensate for distorted reference voltage vector in each sector. The scheme to determine the compensation ratio of vectors is also provided to maximize fault-tolerant performance. Six types of defined failure modes, including single and multiple switch faults, are analyzed and tested in experiments. Evaluations on results of current averaged total harmonic distortions, fluctuation of generator speed, torque oscillations, and stability of dc-link voltage verify its capability to achieve maximum system recovery. The approach proposed is an SVPWM-based method for ac-dc converters that require no additional hardware equipment and provide an effective and low-cost fault-tolerant solution.

Event-triggered reinforcement learning [formula omitted] control design for constrained-input nonlinear systems subject to actuator failures

In the paper, a novel input-constrained H∞ fault-tolerant control approach is developed by using sliding mode control technology and event-triggered reinforcement learning (RL) algorithm. To reduce or even eliminate the impacts of the time-varying actuator failures, a properly sliding mode control strategy is proposed for the controlled system, while the event-triggered H∞ control scheme is established via RL algorithm for the equivalent sliding mode dynamics. By utilizing a single neural network (NN), the Hamilton–Jacobi–Bellman (HJB) equation can be solved approximately, thereby gaining time-triggered worst-case disturbance law, as well as event-triggered optimal control policy. Besides, it is unnecessary to given a initial stabilizing control input in the learning process of neural networks (NNs) in this paper. Moreover, the Lyapunov stability principle is applied to guarantee that the controlled system is uniformly ultimately bounded (UUB). Finally, to verify the feasibility and efficient performance of the developed approach, three simulations are carried out.

Integrated fault‐tolerant control system design based on continuous model predictive control for longitudinal manoeuvre of hypersonic vehicle with actuator faults

In this study, an integrated fault-tolerant control (IFTC) approach with a two-layer structure is proposed for longitudinal manoeuvre of the hypersonic vehicle with elevator deflection faults. On the top, longitudinal manoeuvre trajectory optimisation problem being subjected to state and input constraints is formulated. The minimum oscillation is taken as the objective function, and the direct collocation method is introduced to calculate the optimal manoeuvre reference trajectory online. On the bottom, diverse elevator deflection faults of the hypersonic vehicle are considered. The faulty longitudinal model is reformulated by input–output feedback linearisation, and the faults are equivalently lumped into additional uncertainties. For the lumped uncertainties and high-order derivatives of velocity and altitude of manoeuvre feasible trajectory, an extended state observer is used for online estimation. The fault-tolerant control based on continuous model predictive control is designed, where predictive models are derived by Taylor expansion approximation. To guarantee that the control inputs do not violate constraints, the analytical control law is improved by the optimal-aim distance criterion. The stability of the closed-loop control system and boundedness of observation errors are proved. The simulations verify the effectiveness of the proposed IFTC approach.

Neural Network-Based Adaptive Fault-Tolerant Control for Markovian Jump Systems With Nonlinearity and Actuator Faults

The fault-tolerant control (FTC) issue is considered in this article for Markovian jump systems (MJSs) in which both nonlinearity and actuator faults exist simultaneously. The existed nonlinearity in the considered MJSs means that there exist limitations to employ the renown sliding mode control (SMC) method directly. In this work, the radial basis function (RBF) neural network (NN) technique is exploited to model the nonlinearity on which no knowledge whatsoever is available. Then, with the help of the adaptive backstepping method, an NN-based FTC approach is proposed to overcome the considered challenging case. The adverse effects, arising from the nonlinearity and the actuator faults can be completely compensated by the proposed adaptive controller. With the proposed controller and the adaptation laws, the bounded stability of the considered closed-loop plant can be guaranteed. Furthermore, only two types of adaptive parameters are adopted in the proposed approach to achieve the purpose of FTC, and this reduces the computational burden and thus extends its applicability. Finally, the effectiveness of the developed approach is demonstrated on a practical system: a wheeled mobile manipulator.

A New Observer-Based Cooperative Fault-Tolerant Tracking Control Method With Application to Networked Multiaxis Motion Control System

In a networked multiaxis motion control task, faults in any motor will cause the performance degradation of cooperative operation, which may considerably affect the whole network and the quality of products. The main objective of this article is to propose an improved observer-based fault-tolerant tracking control approach for industrial multiagent systems. First, a group of new distributed intermediate estimators is presented, where the design structure is modified to enhance the feasibility of the estimation scheme. It is shown that both of the nominal distributed intermediate estimator and the traditional extended state observer are special cases of the proposed estimator. Second, the estimation performance can be improved significantly via an online reinforcement learning estimation strategy, whose core is an adaptive switching mechanism integrated with a function block of source fault mode localization. Benefiting from satisfactory estimation results, good fault-tolerant tracking control performance can be guaranteed despite of multiple faults and disturbances. The application to a networked multiaxis motion control system demonstrates the effectiveness and superiority of the proposed method.

Fault-tolerant control for four-wheel independent actuated electric vehicle using feedback linearization and cooperative game theory

This paper presents a novel fault-tolerant control (FTC) approach based on the cooperative game to guarantee the stability of four-wheel independent drive electric vehicles, in which four different players are modeled and interacted to find a solution to the FTC problem. First, a feedback linearization approach is employed to handle the nonlinearities in the system. Then, to study the interaction among actuators in an actuator failure scenario, the FTC problem can be viewed as a cooperative game so that its four players, namely the four in-wheel motors can cooperate to provide more stability of the vehicle. The distributed model predictive control theory is adopted as a general framework, the Pareto strategies among the players are derived using an interactive model based on a convex iterative method. Furthermore, the conditions that guarantee the practical stability of the closed-loop system are provided. The intrinsic differences between the cooperative game and noncooperative game are investigated via a numerical simulation. The effectiveness and real-time of the proposed control strategy are verified in a real-time hardware-in-the-loop test, and the results prove that the control strategy can effectively guarantee the stability of the vehicle in various actuator failure scenarios.

A Detail of Fault Tolerant Flight Control Techniques

Fault tolerant flight control (FTFC) system deals with the detection and diagnosis of faults and looks at the task of regaining control in the presence of the fault. Current modern aircraft are made highly complex for comfort or high performance. The study of improvement in safety, redundancy, and adapting the flight control laws after its occurrence of faults has fascinated the thoughtfulness of several investigators in the previous two decades. Overall illustration of different fault diagnosis and fault-tolerant flight control approaches involved are provided in this review paper.

Fault tolerant control for linear parameter varying systems: An improved robust virtual actuator and sensor approach

This paper presents a robust Fault-Tolerant Control (FTC) methodology for the design of virtual sensors and virtual actuators for discrete-time Linear Parameter Varying (LPV) systems. Conditions based on Linear Matrix Inequalities (LMIs) are proposed for the synthesis of a reconfiguration block composed of a virtual actuator and a virtual sensor, guaranteeing input-to-state stability (ISS). The main contribution of the proposed FTC approach is to deal with LPV models where input and output matrices can be parameter-dependent. Moreover, differently from results found in the literature, a single reconfiguration block can be designed to be robust to different kinds and magnitudes of faults. Real-time level-control experiments illustrate the efficiency of the proposed procedure; the system used in the experiments consists of a nonlinear two coupled tanks with two inputs and two outputs, represented by an LPV model subject to sensor and actuator faults. Experimental results and comparisons with results in the literature indicate that the proposed approach is able to mitigate the fault effects with better performance indices than the literature approaches.

Design of an Active Approach for Detection, Estimation and Short-Circuit Stator Fault Tolerant Control in Induction Motors

Design of an Active Approach for Detection, Estimation and Short-Circuit Stator Fault Tolerant Control in Induction Motors

Neural network-based fault-tolerant control approach considering a submarine system

The stability and satisfactory performance of a fault-tolerant control approach is important for designers and therefore the corresponding closed-loop systems are essential to be dealt with. Considering one of the most important faults including the operator fault in robotic systems leads us to reach the better performance, usually. The radial basis function neural network-based fault-tolerant control method is designed in this research to estimate the model uncertainties, the noise affecting the system, and the operator fault, in order to compensate this one. The results of simulating the fault-tolerant control system propose that this technique successfully secured the tracking function of the control system besides ensuring closed-loop stability. Since the traditional control methods fail to effectively fix the aforementioned problem, a new method so-called neural-network-based fault-tolerant control is proposed. This study proposes the design of a nominal controller, its examinations under operator faults, and finally the expansion of the controller into a fault-tolerant controller. In a word, the contribution made in the research over the state-of-the-art materials focusing on fault-tolerant controls designed in the area of submarine systems is briefly taken into real consideration as its nonlinearity, its fixed structure, the lack of need for switching systems, resistance to noise, and the ability to compensate the effect of the performance drop fault on the collective fault of the operators. Subsequently, the simulation results verified the effectiveness of the proposed approach in coping with the operator’s performance faults, tangibly.

Fuzzy robust fault-tolerant control for offshore ship-mounted crane system

In this paper, a novel event-triggered fuzzy robust fault-tolerant control approach is designed to handle the offshore ship crane nonlinear system with actuator fault and external disturbance. The main objective of this study is to realize the tracking control ability of the outputs while saving the transmission resources, which is achieved by constructing the integrated adaptive sliding mode controller and event trigger mechanism. The fuzzy logic theory is used both in the observer and controller design processes to approximate the nonlinear unknown functions. First, the information of the crane system state, actuator fault, and lumped disturbance are acquired by designing a fuzzy composite observer. Then, a novel adaptive sliding mode controller is presented by using the estimated values. In the proposed control scheme, two adaptive parameters are contained to consider the disturbance elimination and to enhance the tracking performance. An adaptive law is also included to compensate for the fuzzy approximation error. Furthermore, a novel event-triggered controller is proposed to reduce the transmission load of the crane system while also maintaining the tracking ability of the crane system. The no Zeno phenomenon performance is analyzed and, finally, the application to the crane system is given to show the fault tolerance ability of the proposed method.

Velocity-based robust fault tolerant automatic steering control of autonomous ground vehicles via adaptive event triggered network communication

This paper proposes a velocity-based robust fault tolerant automatic steering control approach for autonomous ground vehicles via an adaptive event triggered network communication mechanism. Firstly, as the vehicle longitudinal velocity is not fixed but time-varying, a polytope with finite vertices is adopted to construct a linear parameter varying vehicle system model. Secondly, since network-induced delay and actuator fault inevitably occur in the control system, a novel Lyapunov function is formulated to guarantee the asymptotical stability of the closed-loop system. Moreover, an advanced event triggered communication scheme is proposed for the co-design of robust automatic steering controller, which is quite effective to reduce network communication burden and enhance resource utilization of the shared band-limited in-vehicle communication network. Finally, numerical simulations on two cases are carried out to evaluate and verify the effectiveness and robustness of the proposed controller. Compared with existing studies, the proposed controller contributes greatly to the economization of communication resource and improvement of path following performance and lateral stability.

Fault-tolerant control and vibration suppression of flexible spacecraft: An interconnected system approach

This paper considers a fault-tolerant control and vibration suppression problem of flexible spacecraft. The attitude dynamics is modeled by an interconnected system, in which the rigid part and the flexible part are coupled with each other. Such a model allows us to use the interconnected system approach to analyze the flexible spacecraft. Both distributed and decentralized observer-based fault-tolerant control schemes are developed, under which the closed-loop stability of flexible spacecraft can be ensured by using the cycle-small-gain theorem. Compared with the traditional method, this paper considers the faults occurred not only in the rigid parts, but also in the flexible parts. In addition, the application of the interconnected system approach simplifies the system model of flexible spacecraft, thereby the difficulty of theoretical analysis and engineering practice of fault-tolerant control of flexible spacecraft are greatly reduced. Simulation results show the effectiveness of the proposed methods and the comparison of different fault-tolerant control approach.

Improving the Performance of Doubly Fed Induction Generator Using Fault Tolerant Control—A Hierarchical Approach

The growth of using wind energy on a large scale increases the demand for wind energy conversion machines (WECMs), among these converters, the doubly-fed induction generator (DFIG) is the favorite choice. However, DFIG is very sensitive to wind speed variations and grid faults during operation. In order to overcome these undesirable characteristics, this paper proposes a hierarchical fault tolerant control (FTC) to improve the performance of DFIG. The hierarchical fault tolerant control (FTC) approach consists of pitch angle control (PAC) and maximum power point tracking (MPPT). This hierarchical approach demonstrates the robust response under various (low, rated, and high) wind speed ranges and reduces the undesirable DC voltage overshoots during short-circuit disorder. The simulation results are summarized in a logical table, which depicts the order of controlling scheme and operation for a sustainable energy generation system. The proposed control scheme achieved the healthy and the robust dynamic response without deteriorating the grid power quality or stressing the converters, and approved the effectiveness to suppress the DC voltage overshoots and tolerate the lower down short-circuit disorder to its rated range.

Integrated model predictive fault-tolerant control, and fault detection based on the parity space approach for a reverse osmosis desalination unit

Actuator faults are inevitable in small reverse osmosis desalination plants. It may cause energy losses and reduce the quality of the freshwater, which may endanger human life. This paper focuses on the integrated fault detection and fault-tolerant control approach. The primary motivation of this paper is to propose a novel integrated fault detection and fault-tolerant control approach. The actuator fault is estimated using the concept of parity space approach. Then the system model is updated in the fault-tolerant control block using the information of the estimated fault parameter. Moreover, the proposed approach uses the receding-horizon predictive control-bounded data uncertainties controller, which is the robust and stable variant of generalized predictive control. The remaining uncertainty caused by the model and observer is compensated by this controller. The structure of a small reverse osmosis desalination plant is deployed. In this plant, the permeate flow rate and conductivity are controlled by a retentate valve and a bypass valve, which add a small amount of inlet to the outlet. The performances of three predictive model controllers are evaluated, and a comparison is made between their computational costs, stability, and robustness. The plant is considered to be linear time-invariant and subject to model uncertainties, measurement noise, and actuator fault in the retentate valve as efficiency dropping. The results reveal the robustness of the proposed approach concerning noise and matched uncertainties as well as its accommodation to actuator fault up to 90%.

Adaptive Fuzzy Fault-Tolerant Control for Markov Jump Systems With Additive and Multiplicative Actuator Faults

This article proposes a fault-tolerant compensation control approach against nonlinearity, simultaneous additive, and multiplicative actuator faults in Markov jump systems. In this article, we first exploit the fuzzy logic system (FLS) to approximate the nonlinear functions, which have no available knowledge. Then, by utilizing the adaptive backstepping technique, a FLS-based adaptive fault-tolerant compensation controller is proposed, which can completely compensate for the adverse effects, arising from the additive actuator faults, the multiplicative actuator faults, and the mismatched nonlinearity simultaneously. The stability of the closed-loop system can be guaranteed by the proposed FLS-based adaptive controller with the adaptation laws. The novelty of this article lies in the fact that the additive and multiplicative actuator faults, and mismatched nonlinearity are considered simultaneously. Besides, the renown sliding mode control approach has limitations to deal with the FTC problem considered in this article because the considered nonlinearity is a mismatched one. The proposed control approach can cope with the challenging case. Finally, a practical wheeled mobile manipulator system is used to demonstrate the effectiveness and validity of the proposed approach.

Adaptive fault tolerant attitude control of flexible satellites based on Takagi-Sugeno fuzzy disturbance modeling

This paper investigates the fault tolerance problem of flexible satellites subject to multiple disturbances and actuator faults. An adaptive fault tolerant control (FTC) approach based on disturbance observer is presented for attitude control system (ACS) with actuator faults, elastic modal, modeling error and environmental disturbance torque in this paper. Different from some existing disturbance observer-based control (DOBC) approaches, Takagi-Sugeno (T-S) fuzzy modeling technology is applied to describe the elastic modal. A fuzzy disturbance observer and a fault diagnosis observer are constructed to estimate the elastic modal and actuator fault, respectively. Then, based on fault accommodation and DOBC, a new adaptive FTC strategy is designed to achieve the anti-disturbance performance and improve the system reliability. Finally, the efficiency of the proposed FTC scheme is verified by simulation results.

Fault-Tolerant Control of Degrading Systems with On-Policy Reinforcement Learning

We propose a novel adaptive reinforcement learning control approach for fault tolerant control of degrading systems that is not preceded by a fault detection and diagnosis step. Therefore, a priori knowledge of faults that may occur in the system is not required. The adaptive scheme combines online and offline learning of the on-policy control method to improve exploration and sample efficiency, while guaranteeing stable learning. The offline learning phase is performed using a data-driven model of the system, which is frequently updated to track the system’s operating conditions. We conduct experiments on an aircraft fuel transfer system to demonstrate the effectiveness of our approach.

Universal Adaptive Fault-Tolerant Control of a Multicopter UAV

Abstract This paper presents a universal adaptive fault-tolerant control (FTC) design for multicopter unmanned aerial vehicles (UAVs). The proposed architecture consists of a two-loop control structure: a fault-tolerant controller generates normalized virtual control inputs to track the desired trajectory subject to actuator faults, and an adaptive augmentation controller deals with system uncertainties and also balances the design requirements for specific platform. The FTC approach is based on gain-scheduling control in the framework of structured H∞ synthesis. In order to implement the overall control system on most types of multicopter UAVs, an adaptive mapping algorithm is proposed. High fidelity simulations and experimental results, performed on various multicopters with different payload and configuration, show the effectiveness and robustness of the proposed approach in accommodating different levels of actuator degradation including total failures of the rotors as well as unknown mass and inertia, all using a single controller with fixed coefficients.

Distributed Adaptive Fault-Tolerant Control for Spacecraft Formation With Communication Delays

This paper investigates distributed adaptive fault-tolerant control schemes for spacecraft formation subject to external disturbances, model uncertainties and communication delays. Two novel adaptive fault-tolerant control approaches are presented based on directed communication interaction. The developed adaptive laws are used to estimate the actuator effectiveness, the spacecraft masses and the upper bound on external disturbances. Then, an adaptive fault-tolerant control algorithm with time-varying communication delays is proposed. In particular, the conditions on the controller parameters and the communication delays necessary to assure the asymptotic stability of the closed-loop system are given. Finally, numerical simulations are presented to validate the effectiveness of the two proposed fault-tolerant control schemes for the spacecraft formation system.