Proposed Fault-tolerant Control Approach Research Articles

Neural Network Output-Feedback Consensus Fault-Tolerant Control for Nonlinear Multiagent Systems With Intermittent Actuator Faults.

In this article, the distributed adaptive neural network (NN) consensus fault-tolerant control (FTC) problem is studied for nonstrict-feedback nonlinear multiagent systems (NMASs) subjected to intermittent actuator faults. The NNs are applied to approximate nonlinear functions, and a NN state-observer is developed to estimate the unmeasured states. Then, to compensate for the influence of intermittent actuator faults, a novel distributed output-feedback adaptive FTC is then designed by co-designing the last virtual controller, and the problem of "algebraic-loop" can be solved. The stability of the closed-loop system is proven by using the Lyapunov theory. Finally, the effectiveness of the proposed FTC approach is validated by numerical and practical examples.

Adaptive fault-tolerant control of heterogeneous MASs based on dynamic event-triggered communication

This paper describes a solution to the problem of fault-tolerant control (FTC) problem for leader-following heterogeneous linear multi-agent systems (MASs) subject to loss of effectiveness and time-varying additive actuator faults. The main goal of the proposed FTC approach is to maintain the behaviour of the heterogeneous MASs in spite of actuator faults and to save on bandwidth required for the MASs communication by using a dynamic event-triggered communication mechanism. Firstly, a fault estimation observer, which deals with linear systems with matched disturbances, is constructed to estimate simultaneously the actuator faults and the followers' states. Then, an FTC with dynamic event-triggered communication is proposed. The latter is based on a dynamic internal reference for each agent and exploits the estimated faults. Thus, it is at first shown that the FTC problem can be indirectly solved through the consensus tracking of the defined internal references. Then, a sufficient condition of consensus tracking for the internal references with a dynamic event-triggered communication is proposed. Finally, a sufficient and necessary condition is derived for the FTC of linear heterogeneous multi-agent systems. The effectiveness of the proposed approach is illustrated with a numerical simulation.

Robust delay dependent fault-tolerant control for switched systems with actuator failures

This article concerns the problem of fault tolerant control (FTC) for switched systems with time varying delays and actuator faults. Based on an observer synthesis, a new strategy of fault detection, localization and reconfiguration is established to preserve asymptotic stability when an actuator fails temporary or permanently. The design conditions are formalized in the form of linear matrix inequalities (LMIs) using slack variables matrices. To show the efficiency of the proposed FTC approach, a numerical example is performed.

An integral sliding mode fault tolerant control for a class of non‐linear Lipschitz systems

This paper proposes an active fault-tolerant control (FTC) strategy for a class of non-linear Lipschitz systems. The proposed FTC approach employs the integral sliding mode control (ISMC) technique due to its inherent capability of dealing with system uncertainties. First, under the nominal fault-free condition, the linear matrix inequality technique is introduced to design the primary controller for the non-linear Lipschitz system. To accommodate the actuator faults/failures, the ISMC law is combined with a control allocation scheme that distributes the control signals to the redundant actuators. A non-linear octorotor system is then used as a test bench to validate the tolerance performance of the proposed FTC strategy. In particular, the proposed FTC strategy is applied for the inner-loop control, while in the outer loop, a fractional-order control approach is used to achieve the precise longitude and latitude control. Finally, various simulations are performed to justify the effectiveness of the proposed control scheme.

Design and Experimental Validation of Robust Self-Scheduled Fault-Tolerant Control Laws for a Multicopter UAV

In recent years, multicopter unmanned aerial vehicles (UAV) have been widely used in many commercial and military applications. Due to the increasing requirement for high autonomy and safety, UAVs should possess a fault-tolerant ability to accommodate malfunctions during flight. This article presents two fault-tolerant control (FTC) designs for a multicopter UAV subject to actuator faults. The proposed FTC approach is based on gain-scheduling (GS) control in the framework of structured <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathcal {H}_\infty$</tex-math></inline-formula> synthesis. The scheduled gains of the first controller are parameterized as polynomial functions of the loss of actuator effectiveness, given by an appropriate fault detection and diagnosis system. In order to facilitate the tuning process, the second controller uses the loss of virtual control effectiveness as the GS variable. Experimental results performed on an hexacopter UAV show the effectiveness and the robustness of these methods subject to multiple critical actuator faults.

Mission independent fault‐tolerant control of heterogeneous linear multiagent systems based on adaptive virtual actuator

SummaryIn this article, a fault‐tolerant control (FTC) scheme for linear multiagent systems (MASs) subject to time‐varying loss of effectiveness and time‐varying additive actuator faults as well as external disturbance is investigated. The main objective of the proposed FTC approach is to keep the performance of an MAS after the occurrence of actuator faults similar to the healthy one. The envisaged adaptive virtual actuator for each agent does not require a separate fault detection, isolation, and identification unit nor does it require any information regarding the mission of the MAS. It is shown that the difference between the states of each agent before and after the occurrence of actuator faults can be made arbitrary small and the ultimate bounds of the state error are also obtained. Furthermore, it is shown that for constant actuator faults the state error of each agent converges to zero. Simulation results corresponding to a team of F‐8 aircraft and a heterogeneous MAS with the different order demonstrate and illustrate the effectiveness of our proposed FTC scheme.

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.

Command filter-based fuzzy adaptive nonlinear sensor-fault tolerant control for a quadrotor unmanned aerial vehicle

In this paper, a novel asymptotic fuzzy adaptive nonlinear fault tolerant control (FTC) scheme is presented for the under-actuated dynamics of a quadrotor unmanned aerial vehicle (UAV) subject to diverse sensor faults. The proposed FTC approach can deal with both additive sensor faults (bias, drift, loss of accuracy) and multiplicative sensor fault (loss of effectiveness). The overall dynamics is separated into position loop and attitude loop for FTC controllers design. Combining uncertain parameters and external disturbances, the four types of faults occurring in velocity sensors and Euler angle rate sensors are transformed equivalently into the unknown nonlinear function vectors and uncertain control gains. Fuzzy logic systems are used to approximate the lumped nonlinear functions, and adaptive parameters are estimated online. Nussbaum technique is introduced to deal with the unknown control gains. For both control loops, FTC controllers are designed via command filter-based backstepping approach, in which sliding mode control is introduced to establish asymptotic stability. All tracking error signals of the closed-loop control system are proved to converge to zero asymptotically. Finally, simulation comparisons with other methods demonstrate the effectiveness of the proposed FTC approach for quadrotor UAV with sensor faults.

Robust Sensors-Fault-Tolerance With Sliding Mode Estimation and Control for PMSM Drives

In general, permanent magnet synchronous motor (PMSM) drives require four sensors (one position, one dc-link voltage, and at least two current sensors) to obtain good dynamic control performance. If an unpredictable fault occurs in any of these sensors, the performance of the drive deteriorates or even becomes unstable. Most of the existing works are limited to fault diagnosis of one or two sensors due to complexity. Therefore, to provide a continuous drive operation regardless of any of the sensor faults, an advanced fault-tolerant control (FTC) scheme that comprises of higher order sliding mode (HOSM) based observers and controllers is proposed. Two HOSM observers and one Luenberger observer are designed to generate the respective residuals and provide the detection of all sensor faults. Moreover, HOSM controllers are developed to ensure finite-time convergence of the error trajectories after the fault reconfiguration. The proposed FTC scheme reduces the existing chattering phenomenon with good performance in terms of convergence speed and steady-state error. Evaluation results on a three-phase PMSM are presented to validate the effectiveness of the proposed FTC approach.

Nussbaum-based fuzzy adaptive nonlinear fault-tolerant control for hypersonic vehicles with diverse actuator faults

Stability is a challenging problem for control system of the hypersonic vehicle when partial loss of effectiveness fault and stuck fault happen on elevators and engine. In this paper, a fuzzy adaptive nonlinear fault-tolerant control (FTC) method based on Nussbaum gain technique is proposed for hypersonic vehicles with diverse faults. The cases that one of elevators is lock-in-place and another elevator or the engine is partial loss of effectiveness are addressed. The longitudinal model is transformed into the strict feedback formation. The baseline controllers for altitude and velocity commands tracking are designed using dynamic surface control (DSC) and dynamic inversion. The partial loss of effectiveness faults of elevators and engine are combined in the control gain functions, and Nussbaum approach is introduced to avoid singularity of controllers. The unknown nonlinear functions involving the stuck fault and original uncertain nonlinear items are approximated by fuzzy logic systems. The norm estimation technique is utilized to reduce the number of fuzzy adaptive parameters. This greatly alleviates the calculation burden. It is guaranteed that all signals of the closed-loop FTC system are semi-global uniformly ultimately bounded. Finally, the numerical simulations involving diverse faults demonstrate the effectiveness of the proposed FTC approach.

Data-Driven Output-Feedback Fault-Tolerant Compensation Control for Digital PID Control Systems With Unknown Dynamics

For digital proportional–integral–derivative control systems with unknown dynamics, the data-driven output-feedback fault-tolerant control (FTC) problem is studied in this paper. In a framework of active FTC, the issue of online recursive identification of the residual generator, the state observer, and the observability canonical form of the plant under consideration is addressed; the problem of reconfiguration of the data-driven fault-tolerant compensation controller with $L_2$ -gain properties is also dealt with by means of the above-obtained results, the prefilter and the Riccati equation related to $H_{\infty }$ control so as to accommodate faults and ensure tracking performance. The resulting fault-tolerant compensation control scheme is designed based on the closed-loop systems, and therefore has more practical significance than the existing FTC methodologies developed in terms of the open-loop systems. Finally, the effectiveness of the proposed FTC approach is validated by the speed control experiment on a dc motor.

Neural-Network-Based Adaptive Decentralized Fault-Tolerant Control for a Class of Interconnected Nonlinear Systems.

This paper is concerned with the adaptive decentralized fault-tolerant tracking control problem for a class of uncertain interconnected nonlinear systems with unknown strong interconnections. An algebraic graph theory result is introduced to address the considered interconnections. In addition, to achieve the desirable tracking performance, a neural-network-based robust adaptive decentralized fault-tolerant control (FTC) scheme is given to compensate the actuator faults and system uncertainties. Furthermore, via the Lyapunov analysis method, it is proven that all the signals of the resulting closed-loop system are semiglobally bounded, and the tracking errors of each subsystem exponentially converge to a compact set, whose radius is adjustable by choosing different controller design parameters. Finally, the effectiveness and advantages of the proposed FTC approach are illustrated with two simulated examples.

FAULT TOLERANT CONTROL FOR SENSOR FAULT OF A SINGLE-LINK FLEXIBLE MANIPULATOR SYSTEM

This paper presents a new approach for sensor fault tolerant control (FTC) of a single-link flexible manipulator system (FMS) by using Finite Element Method (FEM). In this FTC scheme, a new control law is proposed where it is added to the nominal control. This research focuses on one element without any payload assumption in the modelling. The FTC method is designed in such way that aims to reduce fault while maintaining nominal FMS controller without any changes in both faulty and fault free cases. This proposed FTC approach is achieved by augmenting Luenberger observer that is capable of estimating faults in fault detection and isolation (FDI) analysis. From the information provided by the FDI, fault magnitude is assessed by using Singular Value Decomposition (SVD) where this information is used in the fault compensation strategy. For the nominal FMS controller, Proportional- integral- derivative (PID) controller is used to control the FMS where it follows the desired hub angle. This work proved that the FTC approach is capable of reducing fault with both incipient and abrupt signals and in two types of faulty conditions where the sensor is having loss of effectiveness and totally malfunction. All the performances are compared with FTC with Unknown Input Observer (FTC-UIO) method via the integral of the absolute magnitude of error (IAE) method.

Fault-Tolerant Controller Design for a Class of Nonlinear MIMO Discrete-Time Systems via Online Reinforcement Learning Algorithm

This paper concentrates on the reinforcement learning (RL)-based fault-tolerant control (FTC) problem for a class of multiple-input-multiple-output (MIMO) nonlinear discrete-time systems. Both incipient faults and abrupt faults are taken into account. Based on the approximation ability of neural networks (NNs), an RL algorithm is incorporated into the FTC strategy, in which an action network is developed to generate the optimal control signal and a critic network is used to approximate the novel cost function, respectively. Compared with the existing results, a novel fault tolerant controller is proposed based on an RL method to reduce a long-term performance index after a fault occurs. The meaning of minimizing the performance index after a fault occurs in an MIMO system is that waste will be decreased and energy will be saved. Note that the weights of NNs are adjusted online rather than offline. Then, it is proven that the adaptive parameters, tracking errors, and optimal control signals are uniformly bounded even in the presence of the unknown fault dynamics. Finally, a numerical simulation is provided to show the effectiveness of the proposed FTC approach.

Design of a new nonlinear model predictive fault tolerant control system using multi-sensor data fusion technique based on UKF algorithm

Purpose– There are high expectations for reliability, safety and fault tolerance are high in chemical plants. Control systems are capable of potential faults in the plant processing systems. This paper proposes is a new Fault Tolerant Control (FTC) system to identify the probable fault occurrences in the plant.Design/methodology/approach– A Fault Diagnosis and Isolation (FDI) module has been devised based on the estimated state of system. An Unscented Kalman Filter (UKF) is the main innovation of the FDI module to identify the faults. A Multi-Sensor Data Fusion algorithm is utilized to integrate the UKF output data to enhance fault identification. The UKF employs an augmented state vector to estimate system states and faults simultaneously. A control mechanism is designed to compensate for the undesirable effects of the detected faults.Findings– The performance of the Nonlinear Model Predictive Controller (NMPC) without any fault compensation is compared with the proposed FTC scheme under different fault scenarios. Analysis of the simulation results indicates that the FDI method is able to identify the faults accurately. The proposed FTC approach facilitates recovery of the closed loop performance after the faults have been isolated.Originality/value– A significant contribution of the paper is the design of an FTC system by using UKF to estimate faults and enhance the accuracy of data. This is done by applying a data fusion algorithm and controlling the system by the NMPC after eliminating the effects of faults.

Linear Parameter-Varying Controller Design for Four-Wheel Independently Actuated Electric Ground Vehicles With Active Steering Systems

This paper presents a linear parameter-varying (LPV) control strategy to preserve stability and improve handling of a four-wheel independently actuated electric ground vehicle in spite of in-wheel motors and/or steering system faults. Different types of actuator faults including loss-of-effectiveness fault, additive fault, and the fault makes an actuator's control effect stuck-at-fixed-level, are considered simultaneously. To attenuate the effects of disturbance and address the challenging problem, a novel fault-tolerant (FT) robust linear quadratic regulator (LQR)-based $H_{\infty}$ controller using the LPV method is proposed. With the LQR-based $H_{\infty}$ control, the tradeoff between the tracking performance and the control input energy is achieved, and the effect from the external disturbance to the controlled outputs is minimized. The eigenvalue positions of the system matrix of the closed-loop system are also incorporated to tradeoff between the control inputs and the transient responses. The vehicle states, including vehicle yaw rate, lateral and longitudinal velocities, are simultaneously controlled to track their respective references. Simulations for different fault types and various driving scenarios are carried out with a high-fidelity, CarSim®, full-vehicle model. Simulation results show the effectiveness of the proposed FT control approach.

Linear parameter‐varying‐based fault‐tolerant controller design for a class of over‐actuated non‐linear systems with applications to electric vehicles

This study presents a passive fault-tolerant (FT) controller to preserve stability of a class of over-actuated non-linear systems in spite of actuator faults. In order to deal with different types of actuator faults, a generalised fault model is adopted such that the FT controller may have the advantage of being able to deal with different types of actuator faults. By grouping the control efforts which have similar effects on the system together, the original over-actuated system can be transferred into a square system, which makes the proposed FT controller has no requirement of the control effort distribution ratios for the actual control effects. The disturbances and uncertainties caused by the actuator faults are attenuated by an FT controller which is designed based on the linear-parameter varying method. The eigenvalue positions of the closed-loop system are constrained into a disk to obtain better transient responses. The proposed FT control method is applied to control a four wheel independently-actuated electric ground vehicle. Experimental results show the effectiveness of the proposed FT control approach.

Adaptive Fuzzy Observer-Based Active Fault-Tolerant Dynamic Surface Control for a Class of Nonlinear Systems With Actuator Faults

The problem of fault-tolerant dynamic surface control (DSC) for a class of uncertain nonlinear systems with actuator faults is discussed and an active fault-tolerant control (FTC) scheme is proposed. Using the DSC technique, a novel fault diagnostic algorithm is proposed, which removes the classical assumption that the time derivative of the output error should be known. Further, an accommodation scheme is proposed to compensate for both actuator time-varying gain and bias faults, and avoids the controller singularity. In addition, the proposed controller guarantees that all signals of the closed-loop system are semiglobally uniformly ultimately bounded, and converge to a small neighborhood of the origin. Finally, the effectiveness of the proposed FTC approach is demonstrated on a simulated aircraft longitudinal dynamics example.

Adaptive fault‐tolerant backstepping control against actuator gain faults and its applications to an aircraft longitudinal motion dynamics

SUMMARYThe problem of fault‐tolerant control (FTC) for a class of uncertain nonlinear systems with actuator faults is discussed, and an observer‐based FTC scheme is proposed. Adaptive fuzzy observers are designed to provide a bank of residuals for fault detection and isolation. Using a backstepping approach, we proposed a novel fault diagnosis algorithm, which removes the classical assumption that the time derivative of the output error should be known. Further, an accommodation scheme is proposed to compensate for the effect of the fault, where it is not needed to know the bounds of the time derivative of the fault. The proposed controller guarantees that all signals of the closed‐loop system are semi‐globally uniformly ultimately bounded and converge to a small neighborhood of the origin by appropriately choosing designed parameters. In addition, a sufficient condition for the existence of an fault detection and isolation observer is derived using Lyapunov stability theory. Finally, a numerical example and a practical aircraft longitudinal motion dynamics are used to demonstrate the effectiveness of the proposed FTC approach. Copyright © 2013 John Wiley &amp; Sons, Ltd.

Fuzzy Logic System-Based Adaptive Fault-Tolerant Control for Near-Space Vehicle Attitude Dynamics With Actuator Faults

This paper addresses the problem of fault-tolerant control (FTC) for near-space vehicle (NSV) attitude dynamics with actuator faults, which is described by a Takagi-Sugeno (T-S) fuzzy model. First, a general actuator fault model that integrated varying bias and gain faults, which are assumed to be dependent on the system state, is proposed. Then, sliding mode observers (SMOs) are designed to provide a bank of residuals for fault detection and isolation. Based on Lyapunov stability theory, a novel fault diagnostic algorithm is proposed, which removes the classical assumption that the time derivative of the output error should be known. Further, for the two cases where the state is available or not, two accommodation schemes are proposed to compensate for the effect of the faults. These schemes do not need the condition that the bounds of the time derivative of the faults should be known. In addition, a sufficient condition for the existence of SMOs is derived according to Lyapunov stability theory. Finally, simulation results of NSV are presented to demonstrate the efficiency of the proposed FTC approach.