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Typical fault scenarios such as actuator stuck, wingtip damage, and sudden center of gravity change usually bring great challenge to fault-tolerant flight control laws. In this paper, adaptive sliding mode disturbance observer (SMDO) is studied under the background of designing a fault-tolerant flight controller. This paper proposes a switched adaptive SMDO for observation of system uncertainties considering fault accommodation. It consists of two adaptive SMDOs: baseline gain-adaptation SMDO and fault-oriented gain-adaptation SMDO. The former is designed for observing slow-changing uncertainties, and can guarantee that the observer gains are small when disturbances are small; the latter aims at achieving fast observing and accommodating of sudden and large faults. Thereafter, a switching logic is developed for the switch between these two adaptive SMDO modes to ensure that the fast gain-adaptation SMDO only works in the case that the uncertainties are large and fast-changing. Finally, the switched adaptive SMDO is integrated with an incremental terminal sliding mode controller, and are validated using simulation experiments based on the nonlinear F-16 model.

This paper addresses a fault accommodation issue for flexible hypersonic vehicles by the static output feedback. Firstly, a longitudinal dynamics for hypersonic vehicles is established in the ODE-beam cascade form and the distributed fault model is built. Next, a novel fault accommodation scheme is developed to achieve fault accommodation and vibration suppression. Such a control strategy is based on the control separation formulation: one component is for accommodating the distributed fault, another one is for the closed-loop stability. The input-to-state stability of the closed-loop system is analysed by using the direct Lyapunov method and bilinear matrix inequalities technique. Then, a new algorithm is provided to obtain the control gain matrices of the fault-tolerant control law. Finally, the simulation results are given to illustrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

The control reconfigurability measure defines the capability of a control system to allow recovery of performance when faults occur; therefore, it has been intended to be a tool for designing and synthesizing approaches in the fault tolerant control context. Reconfigurability depends on the controllability gramian, also known as the second-order information (SOI) in a broad sense. This paper proposes the assignation, by feedback, of the deterministic SOI in order to set the control reconfigurability of a given linear system. The theory concerned with this assignation is reviewed, then constructive theorems are given for finding constant feedback gains that approximate a required control reconfigurability for ease implementation. Also an unification of the reconfigurability measures proposed in the fault tolerance literature is given. Once the SOI is assigned by feedback, it can be computed online by using an identification method, which uses process input/output data. Results from simulation of the three tanks hydraulic benchmark, show that this approach can provide information about the system performance for fault tolerant purposes, thus online control reconfigurability computation and fault accommodation are considered. The approach presented in the paper gives an alternative for supervision taking into account the reconfigurability assigned by design.

To improve the reliability of the attitude determination system with redundant gyroscopes, this article proposes a gyroscope fault accommodation method using a bank of dedicated Kalman filters. The redundant gyroscopes are divided into several groups and then a dedicated Kalman filter is designed for each group of gyroscopes. The residuals generated by the dedicated Kalman filters indicate the consistency levels between the measurements of the star sensor and the gyroscopes. Based on the estimation results provided by the Kalman filters, a fault accommodation method using online selection strategy is proposed to attenuate the effect of the fault. Numerical simulations are used to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper reviews some main results and process concerning with fault diagnosis and accommodation with flight control applications. The fault detection and diagnosis including the quantitative and qualitative methods and the fault-tolerant control including passive and active schemes are introduced, respectively. The control designs and developments of the fault diagnosis and accommodation for continuous-time systems and discrete-time systems, the fault diagnosis and fault-tolerant control for switched systems and interconnected systems as well as the applied flight control research including hypersonic vehicle, spacecraft and helicopter systems are summarised. [ABSTRACT FROM AUTHOR]

Faulty control surface actuator in a small Unmanned Aerial Vehicles (sUAV) could be overcome with a few techniques. Redundant actuators, analytical redundancy or combination of both are normally used as fault accommodation techniques. In this paper, the accommodation technique of faulty elevator actuator is presented. This technique uses a standby control surface as temporary control reallocation. Wind tunnel measurement facility is set up for the experimental validation and it is compared with FoilSim software. Flat plate airfoil which was used as horizontal stabilizer, is simulated using numerical model and it is validated using the wind tunnel test. Then, a flat airfoil is designed to be used as stabilator for the recovery of faulty elevator actuator. Results show the different deflection angle is needed when transferring from one control surface to another. From the analysis, the proposed method could be implemented without affecting the pitch stability during control surface transition. The alternate control surface accommodation technique proves to be promising for higher reliability sUAV in the case of a faulty on-board actuator.

For offshore wind farms, the power loss caused by the wake effect is large due to the large capacity of the wind turbine. At the same time, the operating environment of the offshore wind farm is very harsh, and the cost of maintenance is higher than that of the onshore wind farm. Therefore, it is worthwhile to study through reasonable control how to reduce the wake loss of the wind farm and minimize the losses caused by the fault. In this paper, the Particle Swarm Optimization (PSO) algorithm is used to optimize the active power dispatch of wind farms under generator cooling system faults. The optimization objectives include avoiding the further deterioration of the generator fault, reducing unnecessary power loss of the faulty wind turbine, tracking the power demand from the Transmission System Operator (TSO), and reducing the power fluctuation caused by the PSO algorithm. The proposed optimal power dispatch strategy was compared with the two generally-used fault-handling methods and the proportional dispatch strategy in simulation. The result shows that the proposed strategy can improve the power generation capacity of the wind farm and achieve an efficient trade-off between power generation and fault protection. [ABSTRACT FROM AUTHOR]

Highlights • A methodological framework for sensor fault-tolerant control. • Active accommodation strategies for stability and performance degrading faults. • Rigorous closed-loop stability and performance assessments. • Insight into interplays of sensor errors, sampling rates and control parameters. • A simulated application to the control of non-isothermal chemical reactors. Abstract This work presents model-based strategies for the accommodation of sensor faults in dynamic processes with multi-rate sampled state measurements. The developed strategies account explicitly for both closed-loop stability and performance considerations. Initially, a model-based feedback control system, in which a model predictor compensates for the unavailability of state measurements between sampling times, is designed. The stability and performance characteristics of the multi-rate sampled-data closed-loop system are analyzed and explicitly characterized in terms of the state sampling rates, the fault parameters, and the various process, model and controller design parameters. The resulting characterizations provide insight into the robustness and margins of tolerable faults that can be accommodated, and are used to develop both stability-based and performance-based fault accommodation schemes that aim to maintain closed-loop stability and minimize the degradation of closed-loop performance in the presence of sensor faults. Two types of sensor faults are considered. These include faults that manifest themselves as improper sensor readings, as well as faults that cause drift in the sensor sampling rate. The first type of fault introduces errors in the model state updates at the sampling times, while the second type of fault alters the rate at which the sensors sample the process states. The developed methods are illustrated through a case study involving a cascade of two non-isothermal continuous-stirred tank reactors with plant-model mismatch and access to full state measurements that are sampled at different rates. The case study gives some insight into the effects of sensor faults on the stability and performance of the sampled-data state feedback control system, and how these effects can be mitigated through use of fault-tolerant control. [ABSTRACT FROM AUTHOR]

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Quadruped robots provide better stability and speed in comparison to other legged robots. However, its joint actuator or sensor failure severely affects locomotion. Strategies for actuator and sensor fault accommodation in a compliant legged quadruped are presented here. A pair of orthogonally mounted moving appendages mechanism is proposed here to accommodate locked joint failure. These appendages as rack mounted inertias perform controlled motion during actuator failure. A strategy for sensor fault accommodation is also presented. A three-dimensional multi-body dynamics model of quadruped robot and its fault accommodation strategies are developed using bond graph modeling approach. The control performance is validated both through simulations and experiments. [ABSTRACT FROM AUTHOR]

Summary: This study proposes an improved adaptive fault estimation and accommodation algorithm for a hypersonic flight vehicle that uses an interval type‐2 Takagi‐Sugeno fuzzy model and a quantum switching module. First, an interval type‐2 Takagi‐Sugeno fuzzy model for the hypersonic flight vehicle system with elevator faults is developed to process the nonlinearity and parameter uncertainties. An improved adaptive fault estimation algorithm is then constructed by adding an adjustable parameter. The quantum switching module is also applied to the estimation part to select an appropriate algorithm in different fault cases. The estimation results from the given fuzzy observer are used to design a type‐2 fuzzy fault accommodation controller to stabilize the fuzzy system. The stability of the proposed scheme is analyzed using the Lyapunov stability theory. Finally, the validity and availability of the method are verified by a series of comparisons on numerical simulation results. [ABSTRACT FROM AUTHOR]

The control reconfigurability measure defines the capability of a control system to allow recovery of performance when faults occur; therefore, it has been intended to be a tool for designing and synthesizing approaches in the fault tolerant control context. Reconfigurability depends on the controllability gramian, also known as the second-order information (SOI) in a broad sense. This paper proposes the assignation, by feedback, of the deterministic SOI in order to set the control reconfigurability of a given linear system. The theory concerned with this assignation is reviewed, then constructive theorems are given for finding constant feedback gains that approximate a required control reconfigurability for ease implementation. Also an unification of the reconfigurability measures proposed in the fault tolerance literature is given. Once the SOI is assigned by feedback, it can be computed online by using an identification method, which uses process input/output data. Results from simulation of the three tanks hydraulic benchmark, show that this approach can provide information about the system performance for fault tolerant purposes, thus online control reconfigurability computation and fault accommodation are considered. The approach presented in the paper gives an alternative for supervision taking into account the reconfigurability assigned by design. [ABSTRACT FROM AUTHOR]

A framework of self-triggered fault diagnosis (FD) and fault tolerant control (FTC) for networked control systems (NCSs) is presented in this paper. The self-triggered scheduler is implemented in a smart sensor node. By means of uncertain polytopic theory, we first design a fault diagnosis observer, which has a similar structure with Kalman filter, to simultaneously estimate the fault and state using the self-triggered nonuniform sampled outputs. Then, based on the obtained fault and state information, an active fault tolerant controller with a state-estimate-dependent self-triggered scheduler is provided. We prove that the closed-loop faulty system is input-to-state stable (ISS) under the proposed self-triggered sampling mechanism. Finally, simulation results are provided to verify that the proposed self-triggered FD and FTC scheme can significantly reduce the sampling cost while preserving the desired fault estimation and FTC performance. [ABSTRACT FROM AUTHOR]

The design of neural-network-based iterative learning control for non-linear systems is addressed in the setting of a fault tolerant control regime. Taking advantage of the repetitive character of the control task, the inherent uncertainty related to a potential faulty system state can be properly accommodated in terms of a data-driven iterative learning scheme with neural networks used for forward/inverse modeling as well as for controller synthesis. The resulting control technique is supposed to be flexible enough to accurately compensate the faults occurring on both the sensors and actuators and, additionally, take into account the disturbances and noise acting on the system. A complete characterization of the novel fault-tolerant iterative learning scheme is provided including system identification, fault detection and accommodation. Also, the painstaking convergence analysis is presented and the resulting sufficient conditions can be constructively used to determine the update of control law in the consecutive process trial. The excellent performance of the developed control scheme is illustrated by a nontrivial example of tracking control for a magnetic brake system on various scenarios involving actuator and/or sensor faults. • Fault-tolerant iterative learning control (FT-ILC) scheme employing neural networks. • Convergence analysis of the proposed FT-ILC scheme. • Comprehensive analysis of fault diagnosis, fault estimation and fault accommodation stages. • Magnetic brake control experimental study. • Sensor and actuator fault accommodation. [ABSTRACT FROM AUTHOR]

For offshore wind farms, the power loss caused by the wake effect is large due to the large capacity of the wind turbine. At the same time, the operating environment of the offshore wind farm is very harsh, and the cost of maintenance is higher than that of the onshore wind farm. Therefore, it is worthwhile to study through reasonable control how to reduce the wake loss of the wind farm and minimize the losses caused by the fault. In this paper, the Particle Swarm Optimization (PSO) algorithm is used to optimize the active power dispatch of wind farms under generator cooling system faults. The optimization objectives include avoiding the further deterioration of the generator fault, reducing unnecessary power loss of the faulty wind turbine, tracking the power demand from the Transmission System Operator (TSO), and reducing the power fluctuation caused by the PSO algorithm. The proposed optimal power dispatch strategy was compared with the two generally-used fault-handling methods and the proportional dispatch strategy in simulation. The result shows that the proposed strategy can improve the power generation capacity of the wind farm and achieve an efficient trade-off between power generation and fault protection.

A model-based fault accommodation control scheme that uses a recurrent wavelet Elman neural network (RWENN) is proposed to achieve satisfactory control without performance degradation for biped robot locomotion with unknown uncertainties and faults. In the fault accommodation scheme, a computed torque control is the main control that is used to track the desired trajectory when there is no fault; and a compensation control is used to eliminate the unknown model uncertainties. The proposed RWENN has an input from a context layer with self-feedback and an output recurrent layer to the hidden layer, which increases the precision and convergence time of the network compared with a recurrent neural network, a recurrent fuzzy neural network, and a recurrent wavelet neural network, so that any dynamic change, such as a fault on the system, can be estimated properly. Thus, it enhances the capability of fault accommodation. The adaptive laws of the RWENN-based fault accommodation control are derived from the Lyapunov theorem; hence, the stability of the system can be guaranteed. Finally, a case study of biped robot control with multiple faults and uncertainties is analyzed, and the effectiveness of the proposed fault accommodation scheme is demonstrated by simulation results. Its superiority is also assessed by a numerical comparison with other neural-network-based control schemes. [ABSTRACT FROM PUBLISHER]

In this paper, an adaptive robust output feedback control approach is proposed for a class of uncertain non-linear systems with unknown input deadzone non-linearity, unknown failures and unknown bounded disturbances. By constructing the dead-zone inverse and applying the backstepping recursive design technique, a robust adaptive backstepping controller is proposed, in which adaptive control law is synthesized to handle parametric uncertainties and a novel robust control law to attenuate disturbances. The robust output feedback control law is developed by integrating a switching function s algorithm at each step of the backstepping design procedure. In addition, K-filters are designed to estimate the unmeasured states and neural networks are employed to approximate the unknown non-linear functions. By ensuring boundedness of the barrier Lyapunov function, the major feature of the proposed controller is that it can theoretically guarantee asymptotic output tracking performance, in spite of the presence of unknown input dead-zone non-linearity, various actuator failures and unknown bounded disturbances via Lyapunov stability analysis. The effectiveness of the proposed approach is illustrated by the simulation examples. [ABSTRACT FROM AUTHOR]

The integration of modern renewable energy sources is enabled by the grid side converter (GSC) based on power electronic technology. The operation of the GSC is properly regulated by the GSC controller according to sensor measurements (i.e., of the grid voltage, of the line currents, and of the voltage at the dc-link). However, in case of current sensor faults, the operation of the GSC and of the entire renewable system can be critically affected and catastrophic failures may occur if the sensor fault is not accommodated on time. This paper proposes a model-based Fault Detection, Isolation, and Accommodation (FDIA) scheme, which enables the GSC to overcome faults that may occur on the associated current sensors. The sensor fault detection and isolation scheme has been designed based on analytical redundancy relations, while the accommodation of the faults is based on an adaptive estimation scheme. The proposed FDIA scheme has been applied on a modern GSC and the effectiveness of the scheme has been tested under several multiple current sensor faults and under several grid conditions. Furthermore, the FDIA scheme enables the GSC to operate properly (without causing failures or damages to its components) under current sensor faults and thus, the reliability of the GSC is enhanced. [ABSTRACT FROM PUBLISHER]

This paper studies the fault accommodation problem for linear systems with time-varying delay, system uncertainties and external disturbances. A novel intermediate estimator-based fault tolerant control (FTC) scheme is proposed, where an intermediate estimator is constructed to estimate the states and the faults simultaneously, based on the estimation; an FTC compensation scheme is designed to eliminate the effects of faults, system uncertainties and time-varying delay. It is proved that the states of the closed-loop system are uniformly ultimately bounded. A simulation example shows the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents the development and approach of a model-based fault identification and accommodation framework applied to sampled-data controlled distributed energy resources subject to control actuator faults. The main objective of the proposed approach is to handle faults that degrade stability as well as performance, while remaining robust to false alarms. The proposed method allows for dual fault detection and estimation, through the use of an embedded system model that minimizes the residual between the estimated and sampled states at each sampling period by adjusting a fault parameter in the embedded model over a past horizon. The resulting fault parameter estimate is then used by the control system to find an optimal fault accommodation strategy by minimizing a predefined performance metric whilst ensuring closed-loop stability. The developed fault accommodation framework is then applied to a simulated model of a solid oxide fuel cell subject to both stability and performance degrading faults in the control actuators. A discussion of some of the practical implementation issues associated with the developed framework is also included. [ABSTRACT FROM AUTHOR]

This paper describes a novel thruster fault-tolerant control system (FTC) for open-frame remotely operated vehicles (ROVs). The proposed FTC consists of two subsystems: a model-free thruster fault detection and isolation subsystem (FDI) and a fault accommodation subsystem (FA). The FDI subsystem employs fault detection units (FDUs), associated with each thruster, to monitor their state. The robust, reliable and adaptive FDUs use a model-free pattern recognition neural network (PRNN) to detect internal and external faulty states of the thrusters in real time. The FA subsystem combines information provided by the FDI subsystem with predefined, user-configurable actions to accommodate partial and total faults and to perform an appropriate control reallocation. Software-level actions include penalisation of faulty thrusters in solution of control allocation problem and reallocation of control energy among the operable thrusters. Hardware-level actions include power isolation of faulty thrusters (total faults only) such that the entire ROV power system is not compromised. The proposed FTC system is implemented as a LabVIEW virtual instrument (VI) and evaluated in virtual (simulated) and real-world environments. The proposed FTC module can be used for open frame ROVs with up to 12 thrusters: eight horizontal thrusters configured in two horizontal layers of four thrusters each, and four vertical thrusters configured in one vertical layer. Results from both environments show that the ROV control system, enhanced with the FDI and FA subsystems, is capable of maintaining full 6 DOF control of the ROV in the presence of up to 6 simultaneous total faults in the thrusters. With the FDI and FA subsystems in place the control energy distribution of the healthy thrusters is optimised so that the ROV can still operate in difficult conditions under fault scenarios.

This paper considers the best sensor configuration and fault accommodation problem for inertial navigation systems which use seven inertial sensors such as gyroscopes and accelerometers. We prove that when six inertial sensors are used, the isolation of a double fault cannot be achieved for some combinations of fault magnitudes, whereas when seven inertial sensors are used, the isolation of any double fault can be achieved. There are many configurations which provide the minimum position errors. This paper proposes four configurations which show the best navigation performance and compares their FDI performances. Considering the FDI performance and the complexity of the accommodation rule, we choose one sensor configuration and provide accommodation rules for double faults. A Monte Carlo simulation is performed to show that the accommodation rules work well.

This paper proposes an integrated fault estimation and accommodation method for a class of linearly interconnected complex network systems. In order to simultaneously estimate the unknown state and fault(s) information, a set of novel distributed adaptive estimators are designed, based on which a decentralized fault accommodation scheme is further constructed to stabilize the whole interconnected system. An example of a network consisting of three one-link manipulators is presented to demonstrate the effectiveness of our proposed method. [ABSTRACT FROM AUTHOR]

In this letter, we solve the problem of quantifying and mitigating control authority degradation in real time. Here, our target systems are controlled nonlinear affine-in-control evolution equations with finite control input and finite- or infinite-dimensional state. We consider two cases of control input degradation: finitely many affine maps acting on unknown disjoint subsets of the inputs and general Lipschitz continuous maps. These degradation modes are encountered in practice due to actuator wear and tear, hard locks on actuator ranges due to over-excitation, as well as more general changes in the control allocation dynamics. We derive sufficient conditions for identifiability of control authority degradation, and propose a novel real-time algorithm for identifying or approximating control degradation modes. We demonstrate our method on a nonlinear distributed parameter system, namely a one-dimensional heat equation with a velocity-controlled moveable heat source, motivated by autonomous energy-based surgery.

This paper presents a data-based framework for distributed actuator fault identification and accommodation in networked process systems controlled over a resource-constrained communication medium. Initially, a quasi-decentralized networked control structure is designed to stabilize the plant in the absence of faults. The structure consists of a set of local model-based control systems that communicate with one another at discrete times. An explicit characterization of the networked closed-loop stability region is obtained in terms of the update period, the accuracy of the models, and the choice of controller design parameters. To address the actuator fault identification problem, a set of local fault diagnosis agents are designed and embedded within the various subsystems. Each agent uses a moving-horizon parameter estimation scheme to estimate on-line the size and location of the local faults using the locally sampled states and the model state estimates for the interconnected units. Potential discrepancies or ambiguities in the local fault diagnosis results, which may be caused by the strong dynamic coupling between the individual subsystems and the presence of plant-model mismatch, are reconciled by means of a fault estimation confidence interval which is obtained by analyzing the networked closed-loop dynamics at update times. Once the locations and magnitudes of the actuator faults are identified, the resulting estimates are transmitted to a higher-level supervisor to select and implement a suitable fault accommodation strategy. A number of stability-preserving fault accommodation strategies are devised, including updating the post-fault models, adjusting the controllers’ parameters, or a combination of both. The selection of the appropriate fault accommodation strategy is made on the basis of the estimated fault magnitude and the characterization of the networked closed-loop stability region. Finally, the developed methodology is illustrated using a reactor–separator process example subject to both sudden and incipient control actuator faults. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of fault estimation and accommodation for a class of networked control systems with nonuniform uncertain sampling periods. Firstly, the reason why the adaptive fault diagnosis observer cannot be applied to networked control systems is analyzed. Based on this analysis, a novel robust fault estimation observer is constructed to estimate both continuous-time fault and system states by using nonuniformly discrete-time sampled outputs. Furthermore, using the obtained states and fault information, a nonuniformly sampled-data fault tolerant control law is designed to preserve the stability of the closed-loop system. The proposed scheme can not only guarantee the impact of continuous-time uncertainties and discrete-time sampled estimation errors on the faulty system to satisfy a H ∞ performance index but also repress the negative effect of the unknown intersample behavior of continuous-time fault by use of an inequality technique. Finally, simulation results are included to demonstrate the feasibility of the proposed method. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this paper, a fault diagnosis and accommodation control scheme is designed, which is applicable to mechanical systems. First, the fault detection is developed by designing a nonlinear observer. Second, the fault isolation is achieved by using multiple fault observers. Third, when a fault is diagnosed, an adequate fault accommodation control is triggered to compensate the effects of the fault function. Finally, case study is given to illustrate the effects of the proposed method. [ABSTRACT FROM PUBLISHER]

The paper is devoted to the problem of fault accommodation in nonlinear dynamic systems related to constructing the control law which provides full decoupling with respect to fault effects. Existing conditions are formulated and calculating relations are given for the control law. The logic-dynamic approach is used to solve the problem whose features are consideration of the systems with non-smooth nonlinearities and the use of relatively simple linear methods which may be supported by existing programming systems, e.g. MatLab. [ABSTRACT FROM AUTHOR]