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This paper presents a novel approach for designing reconfiguration blocks for fault hiding of linear systems subject to actuator faults based on the passivity/dissipativity theory. For this purpose, the concept of passivation block is used to design virtual actuators (VAs) which guarantee that the faulty plant achieves the desired passivity indices and consequently the stability. Linear matrix inequalities (LMI)-based conditions are provided for designing the proposed VAs for ensuring the stability recovery for linear systems. Finally, a numerical example is used for assessing the proposed approach., This work was supported by the Brazilian agencies CNPq, FAPEMIG, FAPEAM, and the PROPG-CAPES/FAPEAM Scholarship Program. This work has also been partially co-financed by the Spanish State Research Agency (AEI) and the European Regional Development Fund (ERFD) through the project SaCoAV (ref. MINECO PID2020-114244RB-I00) and the ERDF Operational Program of Catalonia 2014-2020 (ref. 001-P-001643 Looming Factory).

Based on the delta operator approach, a new method of actuator fault estimation for a two-stage chemical reactor system is presented with time-delay and outside disturbances. Firstly, a nonlinear delta operator mathematical model is established to describe the two-stage chemical reactor systems by using the mechanism analysis method. In order to estimate the actuator fault, the proportional–integral observer (PIO) is employed as the state estimator. Meanwhile, a novel delta operator-based actuator fault estimation algorithm is proposed. Then, by means of the Lyapunov–Krasovskii functional technique, sufficient conditions are derived to guarantee that the error system is asymptotically stable with a predefined H ∞ performance index. Next, the desired PIO can be designed. Finally, simulation results are given to illustrate the effectiveness of the proposed methods.

This paper tackles the observer-based finite-time H ∞ control problem for networked nonlinear semi-Markovian jump systems (SMJSs) with actuator fault, parameter uncertainties and partly unknown transition rates via an improved dynamic event-triggered scheme (DETS). In comparison with traditional dynamic event-triggered scheme, the observer-based improved dynamic event-triggered scheme which is not restricted by real system states and could save more network resources is firstly proposed in this paper. Then, a more general actuator fault model is considered and the reliable observer-based state feedback controller is designed. Sufficient conditions are proposed to guarantee the closed-loop system is stochastically finite-time bounded with a prescribed H ∞ disturbance attenuation level. Lastly, two simulation examples are given to affirm the validity of the results obtained in this paper.

This paper proposes a new modus of fault estimation and isolation, which based on fault estimation filter using iterative leaning scheme combine with robust observer for descriptor linear parameter varying (D-LPV) systems with disturbance. According to the p actuators of the D-LPV multi-input multiple-output (MIMO) system, we designed p robust isolation observers and fault estimation filters. Firstly, assuming that the j t h actuator fails, the corresponding j t h robust isolation observer is designed by using the H ∞ method, so that the residual signal is only sensitive to the j t h actuator fault, but robust to disturbance and remaining faults. Next, by comparing the norm of residual signal with threshold of the designed filter, we can judge whether to start fault estimation filter. Then, iterative learning fault estimator use the filtered residual signal to modify the estimated value. Thus, this method of fault estimation and isolation is realized. Finally, the effectiveness and correctness of this method are verified in a simulation experiment.

The tracking control of a flexible hypersonic vehicle with system perturbation and actuator fault is investigated in this paper. A control-oriented model is constructed, which is composed of velocity loop and altitude loop. A double-layer fast adaptive-gain super-twisting disturbance observer (ASTDO) is designed to provide finite-time estimation of the lumped terms of external disturbances and actuator faults. The ASTDO has the property of the non-overestimation of adaptive gains and chattering reduction with higher precision. Based on the estimation of ASTDO, a novel finite-time command filtered backstepping (FCFB) scheme is proposed for the high-order altitude loop. The merit lies in the modified compensating signals and new virtual commands to compensate the command filter errors. The remarkable features of the developed algorithm include the finite-time convergence with higher accuracy and the chattering suppression. Finally, comparative simulation results are given to demonstrate the superiority of the proposed method.

At present, the hierarchical control strategy which includes cyber and physical layers is one of the most widely used control strategies in networked direct current microgrid. In general, through the controller and actuator, the communication data in cyber layer can be used to accomplish the control missions in physical layer, e.g. achieving stable operation or economic operation etc. However, when actuator fault occurs in communication, the normal operation of cyber layer will be affected. Thus, the control effect of physical layer will be also affected. Considering with the above problems, a hierarchical control strategy based on adaptive dynamic program and event-triggered consensus algorithms is proposed to realize the economic operation of microgrid. In this strategy, the main designs are as follows: 1. To deal with the actuator fault problem in the process of consensus control, the fault observer and adaptive dynamic program-based controller are designed in the cyber layer; 2. Also in the cyber layer, an event-triggered consensus algorithm is proposed to adjust distributed energy resources to output their optimal power and make microgrid run economically; 3. To maintain the voltage stable while the power is adjusted, a secondary control strategy is proposed in the physical layer. Finally, the experimental results have verified the effectiveness of the designed strategies.

This paper presents a robust actuator fault diagnosis algorithm for hexacopter Unmanned Aerial Vehicles (UAVs). The algorithm, based on Adaptive eXogenous Kalman Filter (AXKF), consists of two-stage operations: (i) a nonlinear observer and (ii) a linearized adaptive Kalman filter. To this end, we provide a sufficient condition for the nonlinear observer and recursive formulas for the linearized adaptive Kalman filter. The algorithm is tested for actuator fault diagnosis of a hexacopter UAV. Simulation results show that the proposed cascaded algorithm is able to accurately estimate the magnitude of the actuator fault.

In this paper, the problem of distributed fault-tolerant control for multi-agent systems is studied. In the proposed method, the communication graph of the network is not needed to be known by the agents. The leader agent is active with a bounded non-zero control input. The control input of the leader and its bound is not known by any follower. Moreover, it is assumed that the leader is non-cooperative and does not communicate with any other agent. By considering all these limitations, the control input of the followers are designed such that the followers can track the leader in the presence of bounded additive actuator faults. A numerical simulation is provided to illustrate the effectiveness of the proposed approach. Qatar FoundationQatar National Research Fund Scopus

International audience; The main contribution of this paper consists of the development of two methods for actuator fault estimation in dealing with the partially decoupled disturbances of the descriptor system, which is divided into decoupled and non-decoupled unknown inputs (UI). Based on the conventional UI observer, both of the solutions decouples the fault estimation with the first group of UI, while the second UI group is handled differently by each method. Finally, a numerical example with comparisons points out the performance of each approach.

The problem of intermittent, random actuator faults is important in many applications, such as in networked systems, in which there may be intermittent losses of communication between the actuators and the plant. However, state estimation of such systems is rarely addressed, with the majority of the work focusing on fault-tolerant control. In this work, the Kalman filter is modified for state estimation of systems with intermittent actuator faults when the fault rate is known. The proposed estimator is then extended to the case when the actuator fault rate is unknown using the multiple model estimation algorithm. In addition, a sketch of a proof of convergence for this technique is provided. Several simulations involving a DC motor that experiences random actuator faults demonstrate the effectiveness of the proposed techniques.

This paper presents a novel Time Shift Approach for actuator fault reconstruction of systems with output time-delay based on a sliding mode observer (SMO). Arbitrary output delay duration, possibly uncertain and time-varying, can be considered. Ideal sliding mode is made possible even in the presence of delay. This is particularly important since chattering problems can be circumvented so that the proposed approach is conveniently applicable to the case of sampled-output systems. In order to allow a smooth fault reconstruction using noncausal filters, an intentional output delay of one or more sampling periods is introduced. Numerical simulations illustrate the effectiveness of the proposed methodology.

This paper proposes a sensor and actuator fault diagnosis method for small pressurized water reactors (SPWRs), with an innovative labeled fault dictionary established to map complex fault modes, using long short-term memory (LSTM) networks. It can directly learn features from multivariable time-series data and capture long-term dependencies through the cyclic behavior and gate mechanism of LSTM to realize the end-to-end fault diagnosis of SPWRs. Experimental results on a SPWR fault dataset show that the method can effectively diagnose the location, type, and extent of sensor and actuator faults from raw time-series signals with an average accuracy of 92.06% and outperforms three other widely-used fault diagnosis methods. Furthermore, the diagnosis results on the SPWR fault dataset injected with different noise signals demonstrate the strong noise immunity capability of the established LSTM network. Therefore, the proposed method is expected to achieve satisfactory fault diagnosis performances in actual operating environments of SPWRs.

In the close formation flight, the wake vortex induced by the leading aircraft will have adverse effects on the safe flight of the trailing unmanned aerial vehicle (UAV). Hence, this paper investigates a difficult problem of safe control for the trailing UAV against actuator faults, input saturation, and wake vortex effect. By using disturbance observers, external wake vortex, disturbances, and internal actuator faults are estimated. Then, with the help of estimated knowledge of disturbance, backstepping control laws are developed for the longitudinal dynamics and the lateral-directional dynamics, respectively. One of the key features of the proposed strategy is that, the inherent problem, i.e., “explosion of complexity” in conventional backstepping control, is solved by the presented dynamic surface control scheme. Another key feature is that external wake vortex, disturbances, and internal actuator faults, input saturation are simultaneously considered. It is shown by Lyapunov stability analysis that the closed-loop system is uniformly ultimately bounded with safety requirements guaranteed even in the presence of wake vortex and actuator faults. The effectiveness of the proposed approach is further validated by simulation results.

This paper investigates the adaptive fault-tolerant control problem for a class of continuous-time Markovian jump systems with digital communication constraints, parameter uncertainty, disturbance and actuator faults. In this study, the exact information for actuator fault, disturbance and the unparametrisable time-varying stuck fault are totally unknown. The dynamical uniform quantizer is utilized to perform the design work and the mismatched initializations at the coder and decoder sides are also considered. In this paper, a novel quantized adaptive fault-tolerant control design method is proposed to eliminate the effects of actuator fault, parameter uncertainty and disturbance. Moreover, it can be proved that the solutions of the overall closed-loop system are uniformly bounded, which is asymptotically stable almost surely. Finally, numerical examples are provided to verify the effectiveness of the new methodology.

This paper investigates the fault-tolerant control problem of a receiver unmanned aerial vehicle (UAV) against actuator fault and wake vortex induced by the tanker aircraft under the aerial refueling formation flight conditions. In autonomous aerial refueling (AAR), the relative distance of the receiver UAV with respect to the tanker aircraft/UAV is essential for the flight safety of the receiver UAV and the tanker aircraft/UAV. To design the fault-tolerant controller for the receiver UAV, disturbance observer technique is used to estimate the lumped uncertainties including wake vortex and actuator fault. Based on the estimated lumped uncertainties, backstepping architecture is utilized to construct the control scheme. Furthermore, it is shown that the relative forward distance and the relative perpendicular distance tracking errors are uniformly ultimately bounded. Finally, simulations are presented to show the effectiveness of the proposed fault-tolerant control scheme.

Comunicació presentada a SAFEPROCESS 2018. 10th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes (Warsaw, Poland, 29–31 August 2018) In this work, we develop a control structure which can be added to an existing closed loop in order to mitigate the effect of actuator faults. We analyze the initial performance of the closed loop in terms of robustness and time response under references, faults and measurement noises. In the design of the proposed active fault tolerant control structure, we keep the initial robustness and time response to references. At the same time, we try to improve some performance indices under faults at the cost of a higher control action activity caused by the measurement noises that affect the system. The design of the controller depends on a unique parameter so it can be easily understood. We show that although the response under step faults becomes oscillatory, the active fault tolerant structure reduces the integral of the absolute value of the tracking error under step faults and it attenuates the effect of ramp faults in steady state. Several examples show the goodness and drawbacks of the approach and show some aspects to be considered in the design.

In this paper, time-varying loss of effectiveness and time-varying additive actuator faults in nonlinear heterogeneous multi-agent systems (MAS) are considered and an adaptive fault tolerant-control (FTC) scheme based on the virtual actuator framework is proposed. The proposed FTC scheme does not need any separate fault detection, isolation, and identification module. Furthermore, the design of the proposed FTC is independent of the mission of MAS. It is shown that before and after the occurrence of actuator faults, the difference between states of each agent can be arbitrarily reduced and the ultimate bounds of the state error are also calculated. A network of manipulators is considered as a simulation example to illustrate the effectiveness of the proposed FTC methodology. Qatar Foundation; Qatar National Research Fund Scopus

International audience; In the paper, a novel methodology of actuator fault estimation for linear discrete-time systems is proposed. To solve such a challenging problem, a quadratic boundedness approach is used to guarantee the convergence of the proposed state and actuator fault estimation method. In the proposed methodology, the robustness is achieved through the unknown input decoupling while an unappealing effect of the undecoupled disturbances is minimized. Moreover, the developed approach enables to obtain a feasible set of joint system state and fault estimation error. Based on this knowledge, a novel methodology of calculating the uncertainty intervals of the system state and actuator fault is proposed. The illustrative part of the paper presents results obtained for the laboratory DC servo-motor and compares the proposed approach with two alternative methods. Based on this real-data example, the efficiency of the developed methodology is clearly exposed.

The paper deals with the problem of a neural network-based robust state and actuator fault estimator design for non-linear discrete-time systems. It starts from a review of recent developments in the area of robust estimators and observers for non-linear discrete-time systems and proposes less restrictive procedure for designing a neural network-based H observer. The proposed approach guaranties a predefined disturbance attenuation level and convergence of the observer, as well as unknown input decoupling and state and actuator fault estimation. The main advantage of the design procedure is its simplicity. The paper presents an observer design procedure that is reduced to solving a set of linear matrix inequalities. The final part of the paper presents an illustrative example concerning an application of the proposed approach to the multi-tank system benchmark.

This paper proposes a fault-tolerant tracking control for the elevation and pitch angles of a 3-DOF helicopter system, subject to actuator faults and input saturation. The effects of the fault and saturation are combined as a composite actuator fault, which is estimated together with the system state using an adaptive two-step sliding mode observer. An adaptive backstepping controller is then designed to compensate for the composite fault effect and achieve angle tracking. The control design can ensure system stability and achieve described tracking performance in spite of actuator fault and saturation, as verified through comparative simulations for the 3-DOF helicopter system.

This paper proposes an adaptive sliding mode control allocation scheme for accommodating simultaneous actuator fault/failure. A control allocation and re-allocation scheme is synthesized to redistribute the control signals among the working actuators. In the case of the desired virtual control not being achieved, the proposed on-line adaptive scheme can seamlessly adjust the control gain to stabilize the overall system. The effectiveness of the proposed algorithm is demonstrated by the simulation results based on a modified unmanned multirotor helicopter under simultaneous actuator fault/failure conditions.

This paper presents an actuator fault detection and interval reconstruction scheme based on interval observers for systems with both actuator faults and disturbances. To begin with, two full-order interval observers which are sensitive to actuator faults are designed to achieve the goal of actuator fault detection. Then, two reduced-order interval observers are constructed, and they are robust to the actuator faults in that the interval observer constructions are fulfilled without using the boundary information of the actuator faults. An interval actuator fault reconstruction method is developed based on the reduced-order interval observers. Finally, the validities of the proposed methods are verified by a numerical simulation example.

This paper presents an actuator fault reconstruction scheme that can be classified into an algebraic decomposition approach in which the original system is decomposed into two subsystems: a fault-free subsystem and a fault-dependent one. From the result of such algebraic decomposition, the fault estimate is obtained as a set of combinational functions of the system input, the measurement output, the estimate of certain linear functionals involving the state of the fault-free subsystem and the first-order derivative of the measurement output. Here a functional observer and robust exact differentiators are adopted to provide the estimate of the linear functionals of the state of the fault-free subsystem and the derivative of the measurement output, respectively. The proposed method is verified through two numerical examples of seventh-order aircraft and fourth-order crane models.

This paper investigates the problems of actuator fault estimation and accommodation for discrete-time switched systems with state delay. By using reduced-order observer method and switched Lyapunov function technique, a fault estimation algorithm is achieved for the discrete-time switched system with actuator fault and state delay. Then based on the obtained online fault estimation information, a switched dynamic output feedback controller is employed to compensate for the effect of faults by stabilizing the closed-loop systems. Finally, an example is proposed to illustrate the obtained results.

(c) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. This is the authors' accepted and refereed manuscript to the article, postprint. Author's post-print must be released with a Creative Commons Attribution Non-Commercial No Derivatives License.

A cooperative actuator fault accommodation strategy for a team of linear time-invariant (LTI) multi-agent systems with a switching topology and directed communication network graph is studied in this paper. The faults can simultaneously occur in more than one agent. The proposed fault accommodation strategy is based on a consensus algorithm that weights the effort that each agent contributes to the consensus achievement of the team. The stability property of the proposed weighted consensus algorithm is investigated based on Lyapunov analysis. Moreover, a fault index is introduced to quantitatively measure the effects of inaccuracy in estimation of fault severities on consensus performance of the multi-agent team. This index is exploited to reconfigure the agents weights in such a manner that healthier agents contribute more control efforts to compensate for the faulty agents controller degradations. Both actuator loss-of-effectiveness and actuator saturation faults are investigated and the capabilities and effectiveness of our proposed approach is shown by numerical simulations and comparisons with centralized and decentralized fault recovery approaches that are available in the literature.

In this paper, a new continuous impact angle constraint guidance law in the presence of actuator fault is presented based on sliding mode control theory. The robustness and finite-time convergence of the basic guidance law is established using Lyapunov stability theory. For actuator compensation, an additional term is augmented in the original guidance law to guarantee finite-time stability of the closed-loop guidance system. Theoretical analysis and simulation results demonstrate the effectiveness of the proposed method.

This paper proposes an active fault-tolerant control strategy for a quadrotor helicopter against actuator faults and model uncertainties while explicitly considering fault estimation errors based on adaptive sliding mode control and recurrent neural networks. Firstly, a novel adaptive sliding mode control is proposed. In virtue of the proposed adaptive schemes, the system tracking performance can be guaranteed in the presence of model uncertainties without stimulating control chattering. Then, due to the fact that model-based fault estimation schemes may fail to correctly estimate fault magnitudes in the presence of model uncertainties, a fault estimation scheme is proposed by designing a parallel bank of recurrent neural networks. With the trained networks, the severity of actuator faults can be precisely estimated. Finally, by synthesizing the proposed fault estimation scheme with the developed adaptive sliding mode control, an active fault-tolerant control mechanism is established. Moreover, the issue of actuator fault estimation error is explicitly considered and compensated by the proposed adaptive sliding mode control. The effectiveness of the proposed active fault-tolerant control strategy is validated through real experiments based on a quadrotor helicopter subject to actuator faults and model uncertainties. Its advantages are demonstrated in comparison with a model-based fault estimator and a conventional adaptive sliding mode control.

This paper is concerned to address the problem of quantized event-based H ∞ control for networked control systems (NCS’s) under time-varying delay with actuator fault. The feedback NCS’s has been demonstrated as a nonlinear system with time-varying. Event-triggered communication scheme and a quantization scheme are also co-designed to overcome the bandwidth utilization. According to this scheme, data will only transmit when it reaches the threshold value. Furthermore a T–S fuzzy delay model is employed to approximate the nonlinear dynamics of the NCS’s. In addition a novel Lyapunov function is introduced to establish H ∞ performance index in the term of linear matrix inequalities (LMIs). Finally, a truck-trailer example is provided to demonstrate the advantage and effectiveness of the anticipated results.

This paper investigates the problem of dynamic output feedback fault tolerant controller design for discrete-time switched systems with actuator fault. By using reduced-order observer method and switched Lyapunov function technique, a fault estimation algorithm is achieved for the discrete-time switched system with actuator fault. Then based on the obtained online fault estimation information, a switched dynamic output feedback fault tolerant controller is employed to compensate for the effect of faults by stabilizing the closed-loop systems. Finally, an example is proposed to illustrate the obtained results.

This paper deals with actuator fault reconstruction in an uncertain quadrotor using a linear parameter varying (LPV) sliding mode observer. First an LPV model of a quadrotor is presented and then an LPV sliding mode observer is developed to reconstruct faults in the actuators. Unlike many existing LPV fault detection schemes for quadrotors, in this paper the measured LPV scheduling parameter is also allowed to potentially be faulty. The main focus of this paper is to detect actuator faults in the motors of an uncertain quadrotor with inaccurate scheduling parameters using a sliding mode observer. Simulations are performed on the full nonlinear model to show the efficacy of the LPV sliding mode observer in reconstructing the faults.

This paper deals with actuator fault detection and estimation for the Lur’e differential inclusion system. An adaptive full-order observer is used to detect the occurrence of the actuator fault. Then, based on a reduced-order observer, an approach to estimate the actuator fault is presented. A simulation of rotor system is given to illustrate the effectiveness of the proposed method.

In this paper, an approach to isolate the sensor and control surface/actuator failures affecting the innovation of Kalman filter was proposed and applied to an UAV dynamic model. To diagnose if the fault is a sensor fault or an actuator fault, a two-stage Kalman filter (TSKF) insensitive to actuator faults is developed. In the proposed method, sensor faults are isolated by the normalized innovation of Kalman filter. Furthermore, an adaptive linear adaptive TSKF algorithm is used to estimate the loss of control effectiveness and the magnitude of degree of stuck faults in a UAV model. Control effectiveness factors and stuck magnitudes are used to quantify faults entering control systems through actuators. In the simulations, the longitudinal and lateral dynamics of the UAV model is considered, and detection and isolation of sensor and control surface/actuator failures are examined.

This paper focuses on the issue of non-fragile H"2 reliable control for switched linear systems with actuator faults and circular disk pole constraints. The state feedback and the switching law are designed to guarantee that the closed-loop H"2 performance is less than a specified scalar and all closed-loop poles are located in a specified circular disk, in terms of linear matrix inequalities (LMIs). An example is provided to illustrate the effectiveness of the proposed method.

In this paper, the problem of fault tolerant control (FTC) considering actuator fault for networked control systems (NCSs) with access constraints is addressed. A static scheduling method, periodic communication sequence (PCS), is applied to allocate network resource and schedule the access to the network. The novelty of this work lies in that the NCS with PCS and actuator fault are modeled as a periodic switching system and the schedule-dependent Lyapunov function method is used to design the fault tolerant controller. For the data packets dropped by scheduling strategy at each sampling time, 0 and the value of previous sampling time are respectively considered to recover them. Additionally, the problem of robust FTC for the controlled plant with external energy-bounded disturbance is also respectively discussed under these two situations. Numerical examples are given to illustrate the effectiveness of the proposed design methods.

In this paper we present a method for actuator fault detection and identification in Lure systems. The Lure plant is controlled by an observer-based feedback tracking controller, designed for the nominal (fault-free) system. A residual signal is constructed from measurable estimation errors associated with the nominal observer. Faults are diagnosed by on-line contrasting the residual signal trajectories against a set of values that the residuals can be shown to attain under healthy or faulty operation. These values are obtained via set-invariance analysis of the system closed-loop trajectories.

In this paper, a sliding mode based fault-tolerant control (SM-FTC) is designed, implemented and tested in a quadrotor unmanned small helicopter under the propeller damage and actuator fault conditions. Based on the concept of sliding mode control, both passive and active fault-tolerant control laws have been designed and experimentally testbed on a quadrotor UAV (unmanned aerial vehicle) testbed available at Concordia University. These two types of controllers are carried out and compared through both theoretical analyses and experimental tests on the quadrotor UAV system.

International audience; In this paper, a two-level reconfiguration action is used to design an FTC system. The objective is to adapt the corrective action accordingly to the fault severity. The first level of the procedure is triggered when the impact of the fault on the system performance is limited. At the second level a dynamic reference modification based on reference-offset governor is proposed. The idea consists of updating the controller by the new post-fault system model in first time and; in second time; modifying the set-point or reference according to the system constraints which become more strict after fault occurrence in order to avoid any actuator saturation and ensure system stability. The effectiveness of the proposed solution is illustrated by a wind turbine example subjects to actuator faults and constrained on the actuator dynamic ranges.

In this paper, a reliable control method is first proposed for discrete systems with strong uncertainties. Actuator fault compensation is also investigated based on state feedback controller. The reliable control approach uses analytical redundancy and does not need duplicated actuators. Fault compensation controller is designed using accommodation mechanism which compensates the fault effects. The closed-loop stability is established based on Lyapunov's sense. The novelty of this paper is in controller design part. This reliable control approach is applied to three-tank system. The fault compensation method is applied to winding machine in continuous annealing process systems. Applications of the proposed design indicate that the method is effective for three-tank system and continuous annealing process systems.

This work addresses the problem of handling actuator faults in a chemical plant. We consider a multi-unit nonlinear process system subject to input constraints and actuator faults in one unit that preclude the possibility of operating the unit at its nominal equilibrium point. The interconnected nature of the units in a plant brings forth unique opportunities as well as challenges that simply do not exist when handling faults in isolated units. In particular, the fact that the outlet streams from a faulty unit go through subsequent (well functioning) units raises the possibility of better restricting the effects of the fault to the faulty unit. At the same time, handling a fault in a unit may necessitate appropriate action in the downstream unit, which is not a result of a fault in the downstream unit. To address such issues that arise when handling faults in chemical plants, in this work we present a safe-parking framework (we define, in a previous work on handling faults in isolated units, a safe-park point as an operating point where in the event of a fault, a unit can be operated in a way that prevents onset of hazardous situation and allows smooth resumption of nominal operation) for plant-wide fault-tolerant control. We first consider the case where there exists a safe-park point for the faulty unit such that the effect of safe-parking can be completely rejected (via changing the nominal values of the manipulated variables) in the downstream unit. Steady-state as well as dynamic considerations (including the presence of input constraints) is used in determining the necessary conditions for safe-parking the multi-unit system. We next consider the problem where no viable safe-park point for the faulty unit exists such that its effect can be completely rejected in the subsequent unit. A methodology is presented to simultaneously safe-park the consecutive units. Finally, we incorporate performance considerations in the safe-parking framework and illustrate the implementation of the safe-parking framework using a multi-unit chemical reactor system.

—This paper presents Fault-Tolerant Control (FTC) architecture for vehicle dynamics represented by an LPV (Linear Parameter Varying) model with actuator failures. The type of faults considered in this work is total or partial loss of actuator effectiveness. This method does not need any on-line fault estimation, detection or identification mechanism. The proposed approach is applied to the actuator fault tolerant control of vehicle dynamics. It is based on the resolution of LMIs , using the concept of D C -stability and involving PDLM (Parameter-Dependent Lyapunov Matrix). In order to highlight the performance of the proposed control algorithm, numerical simulations are performed.

The contribution addressed by this paper refers to the development of a new dynamic co-active neuro-fuzzy system and its application to fault detection and isolation of an evaporation station. The training of the neuro-fuzzy system is done by a hybrid learning. This is based on a fuzzy clustering algorithm to determine the number of fuzzy rules and the values of the premise parameters, and steepestdescent algorithms to basically determine the consequent parameters. The developed dynamic co-active neuro-fuzzy system is then tested in the framework of an experimental case study. This refers to the sensor and actuator fault diagnosis of an evaporation station from a sugar factory. For this purpose, an extended neuro-fuzzy generalised observer scheme is designed to generate the residuals (symptoms) in the form of the one-step-ahead prediction errors. These are then processed by a neural classifier in order to take the appropriate decision regarding the actual behaviour (normal or faulty) of the process.

Actuator fault diagnosis problem is studied for a class of nonlinear systems with relative degrees from the inputs to the outputs higher than one. This type of nonlinear systems include many mechanical systems, and their actuator fault diagnosis problem can be very challenging because of nonlinearities and high relative degrees. In this paper, in order to solve the actuator fault diagnosis problem for the considered nonlinear systems, 2nd-order and 3rd-order sliding mode differentiators are used and actuator fault diagnosis schemes are proposed to achieve fault detection and isolation. Computer simulations are carried out to compare the efficacy of the proposed fault diagnosis schemes on a laboratory 3D Crane model with noisy measurements. The fault diagnosis schemes are further tested through experiments on a laboratory 3D Crane in terms of actuator fault detection and isolation.

The objective of a robust fault reconstruction scheme is to generate an accurate reconstruction of the fault that is unaffected by disturbances. A typical method for robust fault reconstruction is to reconstruct the faults and disturbances, which is conservative and requires stringent conditions. This paper investigates and presents conditions that guarantee a fault reconstruction that rejects the effects of disturbances, which are less stringent than those of previous work. A VTOL aircraft model is used to validate the work of this paper.

The contribution addressed by this paper refers to the development of a new dynamic neuro-fuzzy system and its application to fault detection and isolation of an evaporation station. Hybrid learning based on the fuzzy c-means clustering and steepest-descent method algorithms are used to train the neuro-fuzzy system. The experimental case study refers to the sensor and actuator fault diagnosis of an evaporation station from a sugar factory. An extended neuro-fuzzy generalised observer scheme is used to generate the residuals (symptoms) in the form of the one-step-ahead prediction errors. These are then analysed by a neural classifier in order to take the appropriate decision regarding the actual behaviour of the process.

Actuator fault diagnosis is often studied under strong assumptions on available sensors: typically it is assumed that either the sensors are fault-free or there is a sufficient redundancy among the sensors. The purpose of this paper is to propose a new method for actuator fault diagnosis which is robust to sensor distortion. It does not require sensor redundancy to compensate sensor distortion. The essential assumption is that sensor distortions are strictly monotonous. Despite the nonlinear and unknown nature of distortions, such sensors still provide useful information for fault diagnosis. A numerical example is provided to illustrate the efficiency of the proposed method. Copyright © 2006 IFAC

This paper presents a computational procedure to evaluate the admissibility of actuator fault configurations (AFC) when a nonlinear predictive/optimal control with constraints is used. The procedure is based on formulating a constraint satisfaction problem from the constraints of the predictive/optimal control law including the effect of faults either through reconfiguration or accommodation. Finally, the proposed admissibility evaluation method is tested on a real application based on the predictive control of a sewer network using its nonlinear model.

Process engineering systems encountered in many risky industries (nuclear, chemical…) are complex because of their multidomain energy character. Actuators are the main elements for their control design. They need for their safety a monitoring system. The monitorability model based analysis (ability to detect and to isolate an actuator fault) is based on the structured residual analysis using analytical redundancy or covering causal path based on bond graph methodology. The present paper proposes a new approach based on flatness topology for actuator monitorability analysis. The developed approach is illustrated by a thermofluid application (a non-linear multienergy system).

This article presents the synthesis and the real tests of an actuator fault diagnosis method applied to a winding process. Based on the variation, during operating conditions, of the winding reels radius, a linear time varying model is considered to describe the dynamic behavior of this system. A stochastic detection filter is defined in order to detect and isolate actuator faults. The implementation to the process is carried out with a DSP dSpace board interfaced with Matlab/Simulink.