Fault Accommodation Scheme Research Articles

Event-Triggered Learning-Based Fault Accommodation for a Class of Nonlinear Interconnected Systems.

In this article, a distributed learning-based fault accommodation scheme is proposed for a class of nonlinear interconnected systems under event-triggered communication of control and measurement signals. Process faults occurring in the local dynamics and/or propagated from interconnected neighboring subsystems are considered. An event-triggered nominal control law is used for each subsystem before detecting any fault occurrence in its dynamics. After fault detection, the corresponding event-triggered fault accommodation law is utilized to reconfigure the nominal control law with a neural-network-based adaptive learning scheme employed to estimate an ideal fault-tolerant control function online. Under the asynchronous controller reconfiguration mechanism for each subsystem, the closed-loop stability of the interconnected systems in different operating modes with the proposed event-triggered learning-based fault accommodation scheme is rigorously analyzed with the explicit stabilization condition and state upper bound derived in terms of event-triggering parameters, and the Zeno behavior is shown to be excluded. An interconnected inverted pendulum system is used to illustrate the proposed fault accommodation scheme.

Fault Accommodation for a Class of Nonlinear Uncertain Systems With Event-Triggered Input

The event-triggered fault accommodation problem for a class of nonlinear uncertain systems is considered in this paper. The control signal transmission from the controller to the system is determined by an event-triggering scheme with relative and constant triggering thresholds. Considering the event-induced control input error and system fault threat, a novel event-triggered active fault accommodation scheme is designed, which consists of an event-triggered nominal controller for the time period before detecting the occurrence of faults and an adaptive approximation based event-triggered fault accommodation scheme for handling the unknown faults after detecting the occurrence of faults. The closed-loop stability and inter-event time of the proposed fault accommodation scheme are rigorously analyzed. Special cases for the fault accommodation design under constant triggering threshold are also derived. An example is employed to illustrate the effectiveness of the proposed fault accommodation scheme.

Finite-frequency fault estimation and accommodation for continuous-time Markov jump linear systems with imprecise statistics of modes transitions

In this paper, the issues of both fault estimation and accommodation are studied for a class of continuous-time Markov jump linear systems under actuator fault, sensor fault and external disturbance in the framework of finite frequency domain. The imprecise statistic of modes transitions are considered here, which means that the transition rates are uncertain. Firstly, the sensor fault is defined as a new state, and then an adaptive observer is developed to estimate the actuator fault and the newly defined state with the aid of the descriptor system approach. By using the obtained fault estimation, a novel fault accommodation scheme is proposed based on the sample point controller design approach to satisfy the stochastic stability requirement of the closed-loop system with a prescribed H∞ performance bound. Moreover, for the convenience of design, the presented sample point controller design is successfully transformed into resolving a class of input-delay control issues. Finally, two numerical examples, including a practical F-404 aircraft engine system, are illustrated to show the effectiveness and applicability of the developed design methods.

Adaptive Sensor Fault Accommodation for Vehicle Active Suspensions via Partial Measurement Information.

In this article, an adaptive sensor fault accommodation scheme is proposed for uncertain vehicle active suspensions via output-feedback control where vehicle body displacement is the only measurable output signal corrupted by sensor bias. An adaptive observer with variable gains is constructed to obtain state estimates whose design procedure involves parameter adaption of the uncertain system parameters and sensor bias, and an output-feedback controller is designed to attenuate the vehicle body displacement based on the partial measurement information, estimates of the states, and unknown parameters. Compensation for measurement error is made both in the design process of the adaptive observer and output-feedback controller in order to weaken the influence brought about by sensor bias fault. In order to guarantee system stability, the variable observer gains are determined in real time using a switching strategy where their values can be modified in finite times by monitoring the state estimates generated by the observer itself. It is proved that the vehicle body displacement will converge to a small neighborhood around zero, and all the signals of the closed-loop system are ensured to be bounded through selecting suitable control parameters. Simulation is carried out to show the effectiveness of the proposed method and results indicate that better stabilization of the suspension vertical motion can be achieved through adaptive compensation for sensor bias.

Distributed Fault Accommodation of Multiple Sensor Faults for a Class of Nonlinear Interconnected Systems

This article considers the design and analysis of a distributed sensor fault accommodation scheme for a class of nonlinear systems, modeled as interconnected subsystems. Each subsystem is subject to possible local sensor faults or may be impacted by a sensor fault in a neighboring subsystem due to the exchange of information between neighboring controllers. The proposed adaptive approximation-based distributed fault accommodation scheme is triggered in the event that a sensor fault is detected. The stability of the closed-loop system in the presence of sensor faults is rigorously analyzed both for the period prior to the detection of the fault, as well as after the detection of the fault when the fault accommodation scheme is activated. The effectiveness of the proposed scheme is illustrated by a simulation example.

Control separation based fault accommodation for flexible hypersonic vehicles

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.

Robust fault accommodation strategy of the reentry vehicle: a disturbance estimate-triggered approach

This study proposes a novel fault accommodation scheme for the strong coupled attitude system of the hypersonic reentry vehicle (HRV) with both actuator drift and loss of efficiency. A general coupling/fault/uncertainty effect-triggered control concept is first introduced for the HRV attitude tracking system to improve its robustness and dynamic performance, which can be derived easily via Lyapunov stability. The design of such a control approach is based on an improved adaptive disturbance observer (ADO) to estimate the lumped uncertainties and actuator faults. The proposed scheme can achieve graceful degradation in tracking performance for the fault-tolerant control system by eliminating the detrimental uncertainty and actuator fault while keeping the beneficial uncertainty and actuator fault. A detailed design procedure has been presented with consideration of the implementation problem. Simulation results obtained on the HRV have demonstrated the effectiveness of the approach proposed.

Fixed-Time Actuator Fault Accommodation Applied to Hypersonic Gliding Vehicles

This article presents a fixed-time accommodation strategy of actuator faults for hypersonic gliding vehicles (HGVs). The approach against actuator faults is incorporated by sliding mode control (SMC), bilimit homogeneity, and adaptive techniques, with consideration of practical constraints and model uncertainties. The resulting fault-tolerant attitude control law allows the fault compensation to be completed in a fixed time, in view of the limited time available for recovery of a faulty HGV. The effectiveness of the presented scheme is validated by comparing it to the finite-time fault accommodation scheme. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Hypersonic vehicles have drawn significant interests due to the features of super-fast and flexible maneuverability. The use of advanced fault-tolerant control (FTC) techniques is expected to guarantee safety during hypersonic vehicle operation. A challenging problem is how to counteract actuator faults promptly and effectively in the presence of practical constraints and model uncertainties. This article presents a fixed-time FTC algorithm for a hypersonic gliding vehicle.

Actuator fault-tolerant control study of an underwater robot with four rotatable thrusters

This paper presents the mathematical design and implementation of an actuator fault-tolerant control system for an underwater robot having four rotatable thrusters where the rotatable action of the thrusters is unconventional to a conventional underwater robotic system. Initially, the dynamic model of the robot is presented. Later, a motion control scheme using a backstepping control technique is made to track a desired spatial trajectory. Two techniques of active fault tolerance control viz., Elimination of Column Method, and Weighted-Pseudo Inverse Method are implemented successfully for single actuator faults on an infinity-shaped trajectory, which is a critical aspect of this study as most of the previous literature reported only on set point control. The methods mentioned above are extended to multiple thrusters failure, but both of them could not handle more than a single thruster failure. Hence, an attempt is made to accommodate two thrusters' failure through the line of sight approach by considering the vehicle as under-actuated. The desired vehicle performance is achieved with this approach. Finally, oceanic currents are modeled to simulate the effectiveness of the methods discussed in the paper to prove the performance capabilities of the control system and fault accommodation schemes under realistic conditions.

Soft Sensors for Instrument Fault Accommodation in Semiactive Motorcycle Suspension Systems

This article describes the development and experimental verification of an instrument fault accommodation (IFA) scheme for front and rear suspension stroke sensors in motorcycles equipped with electronically controlled semiactive suspension systems. In particular, the IFA scheme is based on the use of nonlinear autoregressive with exogenous inputs (NARX) neural networks (NNs) employed as soft sensors for feeding the suspension control strategy back with measurement even in the presence of faults occurred on the sensors. Different NN architectures have been trained and tuned by considering real data acquired during several measurement campaigns. The performance has been compared with that of the well-known half-car model (HCM). Very satisfying results allow the soft sensor to be really integrated into fault-tolerant control systems. In experimental road tests, an implementation of the proposed IFA scheme on a low-cost microcontroller for automotive applications showed to be in real time. In this article, these experimental results are shown to prove the good performance of the IFA scheme in different motorcycle operating conditions.

Identification and Accommodation of Control Actuator Faults Using Multi-rate Sampled Measurements

Abstract This work presents a model-based approach for the detection, estimation and accommodation of control actuator faults in dynamic processes controlled using multi-rate sampled state measurements. Initially, a model-based state feedback controller that employs an inter-sample model predictor to compensate for the unavailability of continuous state measurements is designed. Characterizations of both the stability and performance properties of the multi-rate sampled-data closed-loop system are obtained and expressed in terms of the measurement sampling rates, the magnitudes of the faults, and the various predictor and controller design parameters. A parameter estimator that estimates the magnitudes of the faults by minimizing the error between the estimated and sampled states over a moving horizon is then introduced and used to determine the fault or health status of the control actuators at the sampling times. The identification of faults triggers a fault accommodation scheme that adjusts selected predictor and controller design parameters to simultaneously preserve closed-loop stability and optimize a pre-defined performance metric. The implementation of the developed approach is illustrated using a simulated model of a solid oxide fuel cell system subject to both stability and performance-degrading actuator faults. A discussion of some of the intricacies of the multi-rate sampling scheme and how they impact the practical implementation of the fault identification and accommodation schemes is presented.

Model-based strategies for sensor fault accommodation in uncertain dynamic processes with multi-rate sampled measurements

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.

Forecast-Triggered Model Predictive Control of Constrained Nonlinear Processes with Control Actuator Faults

This paper addresses the problem of fault-tolerant stabilization of nonlinear processes subject to input constraints, control actuator faults and limited sensor–controller communication. A fault-tolerant Lyapunov-based model predictive control (MPC) formulation that enforces the fault-tolerant stabilization objective with reduced sensor–controller communication needs is developed. In the proposed formulation, the control action is obtained through the online solution of a finite-horizon optimal control problem based on an uncertain model of the plant. The optimization problem is solved in a receding horizon fashion subject to appropriate Lyapunov-based stability constraints which are designed to ensure that the desired stability and performance properties of the closed-loop system are met in the presence of faults. The state-space region where fault-tolerant stabilization is guaranteed is explicitly characterized in terms of the fault magnitude, the size of the plant-model mismatch and the choice of controller design parameters. To achieve the control objective with minimal sensor–controller communication, a forecast-triggered communication strategy is developed to determine when sensor–controller communication can be suspended and when it should be restored. In this strategy, transmission of the sensor measurement at a given sampling time over the sensor–controller communication channel to update the model state in the predictive controller is triggered only when the Lyapunov function or its time-derivative are forecasted to breach certain thresholds over the next sampling interval. The communication-triggering thresholds are derived from a Lyapunov stability analysis and are explicitly parameterized in terms of the fault size and a suitable fault accommodation parameter. Based on this characterization, fault accommodation strategies that guarantee closed-loop stability while simultaneously optimizing control and communication system resources are devised. Finally, a simulation case study involving a chemical process example is presented to illustrate the implementation and evaluate the efficacy of the developed fault-tolerant MPC formulation.

Fault accommodation in compliant quadruped robot through a moving appendage mechanism

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.

Fault Accommodation Control for a Biped Robot Using a Recurrent Wavelet Elman Neural Network

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.

Fractional-order active fault-tolerant force-position controller design for the legged robots using saturated actuator with unknown bias and gain degradation

Abstract In this paper, a novel fault accommodation strategy is proposed for the legged robots subject to the actuator faults including actuation bias and effective gain degradation as well as the actuator saturation. First, the combined dynamics of two coupled subsystems consisting of the dynamics of the legs subsystem and the body subsystem are developed. Then, the interaction of the robot with the environment is formulated as the contact force optimization problem with equality and inequality constraints. The desired force is obtained by a dynamic model. A robust super twisting fault estimator is proposed to precisely estimate the defective torque amplitude of the faulty actuator in finite time. Defining a novel fractional sliding surface, a fractional nonsingular terminal sliding mode control law is developed. Moreover, by introducing a suitable auxiliary system and using its state vector in the designed controller, the proposed fault-tolerant control (FTC) scheme guarantees the finite-time stability of the closed-loop control system. The robustness and finite-time convergence of the proposed control law is established using the Lyapunov stability theory. Finally, numerical simulations are performed on a quadruped robot to demonstrate the stable walking of the robot with and without actuator faults, and actuator saturation constraints, and the results are compared to results with an integer order fault-tolerant controller.

Forecast-Triggered Fault-Tolerant Model Predictive Control of Nonlinear Processes

In this work, we consider the problem of fault-tolerant stabilization of constrained nonlinear processes controlled over resource-constrained sensor-controller communication networks and subject to control actuator faults. A methodology for the design of resource-aware Lyapuonv-based model predictive control (MPC) systems that achieve the fault-tolerant stabilization objective with reduced sensor-controller communication is presented. In this approach, the control action is computed by solving on-line a finite-horizon optimal control problem based on an uncertain model of the plant subject to appropriate Lyapuonv-based stability constraints. The stability constraints are designed to ensure the desired closed-loop stability and performance properties in the presence of faults, and an explicit characterization of the state space region where fault-tolerant stabilization is guaranteed is obtained in terms of the fault size, the choice of the controller design parameters and the size of the plant-model mismatch. To keep sensor-controller communication to a minimum, a forecast-triggered communication strategy is used to determine when communication should be suspended or restored over the network. In this strategy, an update of the model state in the predictive controller using the sensor measurements at a given sampling time is triggered only when the Lyapunov function is forecasted to breach a certain threshold over the next sampling interval. The update-triggering threshold is derived using Lyapunov techniques and is explicitly parameterized in terms of the fault and a suitable fault accommodation parameter. Based on this characterization, fault accommodation strategies that guarantee closed-loop stability while simultaneously optimizing control and communication system resources are devised. Finally, the developed MPC formulation is illustrated using a chemical process example.

Decentralized fault tolerant control of a class of nonlinear interconnected systems

In this paper, a novel decentralized fault tolerant controller (DFTC) is proposed for interconnected nonlinear continuous-time systems by using local subsystem state vector alone in contrast with traditional distributed fault tolerant controllers or fault accommodation schemes where the measured or the estimated state vector of the overall system is needed. The proposed decentralized controller uses local state and input vectors and minimizes the fault effects on all the subsystems. The DFTC in each subsystem includes a traditional controller term and a neural network based online approximator term which is used to deal with the unknown parts of the system dynamics, such as fault and interconnection terms. The stability of the overall system with the proposed DFTC is investigated by using Lyapunov approach and the boundedness of all signals is guaranteed in the presence of a fault. Therefore, the proposed controller enables the system to continue its normal operation after the occurrence of a fault, as long as it does not cause failure or break down of a component. Although the decentralized fault tolerant controller is designed mainly for large-scale systems where continuous transmissions between subsystems is not possible, it can also be applied to small-scale systems where sensor measurements are available for use in all subsystems. Finally the proposed methods are verified and compared in simulation environment.

A Distributed Control Reconfiguration and Accommodation for Consensus Achievement of Multiagent Systems Subject to Actuator Faults

This paper tackles the development of distributed control reconfiguration and fault accommodation strategies for consensus achievement in multiagent systems in the presence of faulty agents whose actuators are unable to produce their nominal control efforts. A faulty agent can adversely affect and prevent the team from reaching agreement and lead to catastrophic mission performance degradations. To ensure that the faulty team pursues its consensus objectives, in this paper, on-line distributed control reconfiguration strategies are developed that employ only nearest neighbor information to guarantee the team consensus while minimizing a local cost performance index. Toward the above end, the distributed Hamilton–Jacobi–Bellman equations for the faulty agent are derived and novel reconfigured controllers are designed by solving the above equations subject to the faulty agent dynamics and network structure constraints to ensure fault accommodation of the entire team. Our proposed reconfigurable controllers are applied to a network of autonomous underwater vehicles subject to actuator faults to demonstrate and illustrate the effectiveness and capabilities of our proposed fault recovery control strategies.

An integrated fault estimation and accommodation design for a class of complex networks

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.