An adaptive sliding mode differentiator for actuator oscillatory failure case reconstruction

This paper proposes an adaptive sliding mode super-twisting differentiator which allows the gains to adapt based on the ‘quality’ of the sliding motion. A Lyapunov based analysis for the adaptive super-twisting scheme is presented to demonstrate its properties. As an example, the adaptive differentiator proposed in this paper has been used as part of a nonlinear FDI scheme for an Oscillatory Failure Case (OFC) in an actuator. The FDI scheme requires an estimate of the rod speed which is provided by the adaptive super-twisting differentiator. Due to the conditions in which the actuator operates, normally the differentiator gains are initialised at low values to ensure good rod speed estimation in fault free conditions. However for large amplitude/frequency OFCs, the gains must adapt in order to maintain sliding and provide a good estimation. Simulations on a high fidelity nonlinear aircraft benchmark model have been carried out for both liquid and solid OFCs.     

带有推进器故障的船舶动力定位系统的鲁棒滑模容错控制

由于海洋工作环境具有复杂性和不可预测性,船舶动力定位系统的可靠性一直备受关注.针对带有推进器故障的船舶动力定位系统的鲁棒容错控制问题展开研究.首先,建立更一般且统一的推进器故障模型,该模型能全面描述推进器失效、卡死、中断3种故障情形;然后,设计一种不依赖故障检测模块(FDI)和故障信息上下界的自适应滑模控制器, 其中自适应机制用于在线估计故障信息和未知外部扰动的上界,基于李雅普诺夫稳定性理论和滑模控制理论,所设计的自适应滑模控制器能保证船舶动力定位系统在有推进器故障发生和海洋环境外部有界扰动存在情况下的所有信号一致有界;最后,在一艘过驱动船舶模型上进行仿真,其结果验证了所设计方法的有效性.     

Fault tolerant control using sliding modes with on-line control allocation

This paper proposes an on-line sliding mode control allocation scheme for fault tolerant control. The effectiveness level of the actuators is used by the control allocation scheme to redistribute the control signals to the remaining actuators when a fault or failure occurs. The paper provides an analysis of the sliding mode control allocation scheme and determines the nonlinear gain required to maintain sliding. The on-line sliding mode control allocation scheme shows that faults and even certain total actuator failures can be handled directly without reconfiguring the controller. The simulation results show good performance when tested on different fault and failure scenarios.     

Fault tolerant sliding mode control for T-S fuzzy stochastic time-delay system via a novel sliding mode observer approach

In this paper, a fault estimation and fault-tolerant control problem for a class of T-S fuzzy stochastic time-delay systems with actuator and sensor faults is investigated. A novel sliding mode observer is proposed, which can simultaneously estimate the system states, actuator and sensor faults with good accuracy. Based on the state and actuator fault estimation, a new sliding mode control scheme is developed, which can effectively eliminate the influence of actuator fault. Sufficient conditions for the existence of the proposed observer and fault-tolerant sliding mode controller are provided in terms of linear matrix inequality, and moreover, the reachability of the sliding mode surface can be guaranteed under the proposed control scheme. The propose sliding mode observer and fault-tolerant sliding mode controller can overcome the restrictive assumption that the input matrix of all local modes is the same. Finally, a numerical example is provided to verify the effectiveness of the proposed sliding mode observer and fault-tolerant sliding mode control technique.     

Robust decentralized actuator fault detection and estimation for large-scale systems using a sliding mode observer

In this paper, robust decentralized actuator fault detection and estimation is considered for a class of non-linear large-scale systems. A sliding mode observer is proposed together with an appropriate coordinate transformation to find the sliding mode dynamics. Then, based on the features of the observer, a decentralized fault estimation strategy is proposed using an equivalent output error injection, and a decentralized reconstruction scheme follows by further exploiting the structure of the uncertainty which is allowed to have non-linear bounds. The estimation and reconstruction signals only depend on the available measured information and thus the proposed strategy can work on-line. The theoretical results which have been obtained are applied to an automated highway system. Simulation shows the feasibility and effectiveness of the proposed scheme.     

Development and evaluation of an integral sliding mode fault‐tolerant control scheme on the RECONFIGURE benchmark

This paper describes the development, application, and evaluation of a linear parameter‐varying integral sliding mode control allocation scheme to the Reconfiguration of Control in Flight for Integral Global Upset Recovery benchmark model to deal with an actuator failure/fault scenario. The proposed scheme has the capability to maintain close to nominal (fault free) load factor control performance in the face of elevator failures/faults by including a retrofitted integral sliding mode term and then rerouting (via control allocation) the augmented control signal to healthy elevators without reconfiguring the baseline controller. In order to mitigate any chattering appearing in the elevator demands, the retrofitted signal is based on a super‐twisting sliding mode structure. This produces a control signal that is continuous and does not have the discontinuous switching nature of traditional sliding mode schemes. The scheme is evaluated using an industrial Functional Engineering Simulator developed as part of the Reconfiguration of Control in Flight for Integral Global Upset Recovery project. Monte Carlo campaign results are shown to demonstrate the performance of the proposed scheme.     

Unified FDI and FTC Scheme for Air Path Actuators of a Diesel Engine Using ISM Extended with Adaptive Part

A unified fault detection and isolation (FDI) and fault tolerant control (FTC) strategy for the diesel engine's air management system has been formulated. Diesel engines need to comply with the strict emission requirements for which they are equipped with specialized sub‐systems for the purpose, such as the variable geometry turbo (VGT) charger and exhaust gas recirculation (EGR). Hardware‐based controls tend to make the system more complex and prone to structured and unstructured faults. This calls for an advanced FTC technique that can ensure desired level of emissions even in the presence of minor system malfunctions. The scheme proposed in this paper detects, isolates and estimates the structured faults and minimizes their effects by re‐positioning the actuators using integral sliding mode (ISM) control. Estimating the magnitude of structured faults help to reduce the ISM controller gains, eventually reducing the chattering. The stability of the system is analyzed using Lyapunov stability criterion. Simulations have been performed using fully validated industrial scale model of a diesel engine to elucidate the effectiveness of our scheme.     

双电机同步驱动伺服系统故障诊断与容错控制

本文针对双电机同步驱动伺服系统中执行器失效会导致系统性能下降甚至失稳的情况,提出了一种基于自适应滑模的故障诊断和容错控制策略.该方法通过设计各电机转速的自适应滑模状态观测器,在线估计各执行器的失效因子:当单个执行器部分失效时,通过自适应的方法调整控制器增益;当单个执行器全部失效时,重构系统的控制律.对于系统中存在非匹配不确定项的情况,提出在期望虚拟信号中引入基于扩张状态观测器的补偿项抑制方案;利用Lyapunov理论证明了闭环系统在正常和故障状况下的稳定性以及观测器的收敛性;仿真结果表明,所设计的控制策略能保证系统稳定跟踪指令信号,在单个执行器失效的情况下系统跟踪性能基本不下降.     

A robust fault diagnosis and accommodation scheme for robot manipulators

This paper investigates an algorithm for robust fault diagnosis (FD) in uncertain robotic systems by using a neural sliding mode (NSM) based observer strategy. A step by step design procedure will be discussed to determine the accuracy of fault estimation. First, an uncertainty observer is designed to estimate the uncertainties based on a first neural network (NN1). Then, based on the estimated uncertainties, a fault diagnosis scheme will be designed by using a NSM observer which consists of both a second neural network (NN2) and a second order sliding mode (SOSM), connected serially. This type of observer scheme can reduce the chattering of sliding mode (SM) and guarantee finite time convergence of the neural network (NN). The obtained fault estimations are used for fault isolation as well as fault accommodation to self-correct the failure systems. The computer simulation results for a PUMA560 robot are shown to verify the effectiveness of the proposed strategy.     

Sliding mode fault‐tolerant control of uncertain system: A delta operator approach

This paper is concerned with the sliding mode control of uncertain nonlinear systems against actuator faults and external disturbances based on delta operator approach. The nonlinearity, actuator fault, and external disturbance are considered in this study, and the bounds of Euclidean norms of the nonlinearity and the specific lower and upper bounds of the actuator faults and the disturbances are unknown knowledge. Our attention is mainly focused on designing a sliding mode fault‐tolerant controller to compensate the effects from the nonlinearity, unknown actuator fault, and external disturbance. Based on Lyapunov stability theory, a novel‐adaptive fault‐tolerant sliding mode control law is deigned such that the resulting closed loop delta operator system is finite‐time convergence and the actuator faults can be tolerated, simultaneously. Finally, simulation results are provided to verify the effectiveness of the proposed control design scheme. Copyright © 2017 John Wiley & Sons, Ltd.     

New results in robust actuator fault reconstruction for linear uncertain systems using sliding mode observers

This paper presents a robust actuator fault reconstruction scheme for linear uncertain systems using sliding mode observers. In existing work, fault reconstruction via sliding mode observers is limited to either linear certain systems subject to unknown inputs, relative degree one systems or a specific class of relative degree two systems. This paper presents a new method that is applicable to a wider class of systems with relative degree higher than one, and can also be used for systems with more unknown inputs than outputs. The method uses two sliding mode observers in cascade. Signals from the first observer are processed and used to drive the second observer. Overall, this results in actuator fault reconstruction being feasible for a wider class of systems than using existing methods. A simulation example verifies the claims made in this paper. Copyright © 2007 John Wiley & Sons, Ltd.     

Development and application of sliding mode LPV fault reconstruction schemes for the ADDSAFE Benchmark

This paper describes the development and the evaluation of a robust sliding mode observer fault detection scheme applied to an aircraft benchmark problem as part of the ADDSAFE project. The ADDSAFE benchmark problem which is considered in this paper is the yaw rate sensor fault scenario. A robust sliding mode sensor fault reconstruction scheme based on an LPV model is presented, where the fault reconstruction signal is obtained from the so-called equivalent output error injection signal associated with the observer. The development process includes implementing the design using AIRBUS׳s the so-called SAO library which allows the automatic generation of flight certifiable code which can be implemented on the actual flight control computer. The proposed scheme has been subjected to various tests and evaluations on the Functional Engineering Simulator conducted by the industrial partners associated with the ADDSAFE project. These were designed to cover a wide range of the flight envelope, specific challenging manoeuvres and realistic fault types. The detection and isolation logic together with a statistical assessment of the FDD schemes are also presented. Simulation results from various levels of FDD developments (from tuning, testing and industrial evaluation) show consistently good results and fast detection times.     

Study on the sliding mode fault tolerant predictive control based on multi agent particle swarm optimization

For a class of uncertain discrete-time systems with time varying delay, the problem of robust fault-tolerant control for such systems is studied by combining the design of sliding mode control (SMC) and model predictive control (MPC). A sliding mode fault tolerant predictive control based on multi agent particle swarm optimization (PSO) is presented, and the design, analysis and proof of the scheme are given in detail. Firstly, the sliding mode prediction model of the system is designed by assigning poles of the output error of the system. The model has time varying characteristics, and it can improve the motion quality of the system while ensuring the sliding mode is stable. Secondly, a new discrete reference trajectory considering time-delay systems subjected simultaneously to parameter perturbations and disturbances is proposed, which not only can ensure that the state of the system has good robustness and fast convergence in the process of approaching sliding mode surface, but also can inhibit chattering phenomenon. Thirdly, the multi agent PSO improves the receding-horizon optimization, which can quickly and accurately solve the control laws satisfying the input constraints, and can effectively avoid falling into local extrema problem of the traditional PSO. Finally, the theoretical proof of robust stability of the proposed control scheme is given. Experimental results of quad-rotor helicopter semi physical simulation platform show that the state of uncertain discrete-time systems with time varying delay is stable under the action of the proposed control scheme in this paper. The advantages of fast response, less overshoot and small control chattering prove the feasibility and effectiveness of the proposed control scheme.     

Sensor fault diagnosis for a class of time delay uncertain nonlinear systems using neural network

In this paper, a sliding mode observer scheme of sensor fault diagnosis is proposed for a class of time delay nonlinear systems with input uncertainty based on neural network. The sensor fault and the system input uncertainty are assumed to be unknown but bounded. The radial basis function (RBF) neural network is used to approximate the sensor fault. Based on the output of the RBF neural network, the sliding mode observer is presented. Using the Lyapunov method, a criterion for stability is given in terms of matrix inequality. Finally, an example is given for illustrating the availability of the fault diagnosis based on the proposed sliding mode observer.     

The merits of exergy-based fault detection in petrochemical processes

The complexity and multi-domain nature of petrochemical (PC) plants make the application of conventional model-based fault detection and isolation (FDI) techniques a challenging endeavour. Although hybrid FDI schemes aim to address this shortfall, many are simply a combination of data-driven techniques that exclude physical system information. In this work, a hybrid approach to FDI of a PC process is proposed that is based on an exergy-data abstraction. Data from an actual system is abstracted to system exergy, based on physical knowledge of the system and then used as a diagnostic metric for the FDI scheme. In this paper, it is shown why energy-based approaches are lacking when considering petrochemical processes. After presenting a novel method for the real-time, automatic calculation of chemical exergy in Aspen HySys^® the applicability of exergy-based fault detection is investigated. Application of the exergy-based fault detection scheme shows a marked improvement over the energy-based approach with perfect detectability and isolability of the considered process faults. The exergy-based fault detection technique shows merit in comparison to the energy-based detection scheme. Additionally, and more importantly, exergy-based characterisation allows the use of more sophisticated model-based fault detection schemes to petrochemical processes.     

Robust sliding mode observer-based actuator fault detection and isolation for a class of nonlinear systems

In this article, an actuator fault detection and isolation scheme for a class of nonlinear systems with uncertainty is considered. The uncertainty is allowed to have a nonlinear bound which is a general function of the state variables. A sliding mode observer is first established based on a constrained Lyapunov equation. Then, the equivalent output error injection is employed to reconstruct the fault signal using the characteristics of the sliding mode observer and the structure of the uncertainty. The reconstructed signal can approximate the system fault signal to any accuracy even in the presence of a class of uncertainty. Finally, a simulation study on a nonlinear aircraft system is presented to show the effectiveness of the scheme.     

Fault reconstruction for delay systems via least squares and time‐shifted sliding mode observers

In this article, we address the problem of fault reconstruction in delayed systems by introducing a time‐shifted sliding mode observer (SMO). While time‐varying delays of arbitrary duration are considered in the measured output signal, the actuator fault is parametrized as a weighted sum of known regressor functions with unknown coefficients. The prediction scheme utilizes the variation of constants formula to obtain the present time estimate of the unmeasured state. The fault is also identified at present time by means of the continuous‐time Least Squares approaches. Ideal sliding mode can be guaranteed in theory, even in the presence of such adverse delays, since there is no chattering in the output estimation error of the SMO. An application to petroleum engineering with numerical simulations is presented to show the effectiveness of the proposed method.