Observer-based fuzzy adaptive fault control for a class of MIMO nonlinear systems

In this paper, the fault-tolerant control (FTC) problem is investigated for a class of multi-input multiple output nonlinear systems with time-varying delays, and an active FTC method is proposed. The controlled system contains unknown nonlinear functions, unknown control gain functions and actuator faults, which integrates time-varying bias and gain faults. Then, fuzzy logic systems are used to approximate the unknown nonlinear functions and unknown control gain functions, fuzzy adaptive observers are used for fault detection and isolation. Further, based on the obtained information, an accommodation method is proposed for compensating the actuator faults. It is shown that all the variables of the closed-loop system are semi-globally uniformly bounded, the tracking error converges to an arbitrary small neighbourhood of the origin. A simulation is given to demonstrate the effectiveness of the proposed approach.     

Fault estimation and controller compensation in Lure systems by LPV-embedding

Previous works have considered the use of set invariance theory for fault detection and isolation in nonlinear Lure systems. This paper extends those results and proposes a new actuator fault-tolerant control approach. The fault-tolerant control scheme is designed based on linear parameter-varying (LPV) models of Lure systems. The actuator fault situation is diagnosed by an invariant set-based fault detection and isolation algorithm. Faults are compensated by adapting the controller gain based on estimates of the fault magnitude. Conditions for correct fault detection and isolation, and closed-loop stability are derived. The proposed fault-tolerant control scheme is compared with a linearised model approach and the performance of both, LPV-embedding and linearised, approaches are analysed for scalar and second-order systems. An example of a chaotic Chua circuit is also provided to illustrate the proposed fault-tolerant control scheme in higher-order systems.     

Fault-tolerant control of a polyethylene reactor

This work focuses on fault-tolerant control of a gas phase polyethylene reactor. Initially, a family of candidate control configurations, characterized by different manipulated inputs, is identified. For each control configuration, a bounded nonlinear feedback controller, that enforces asymptotic closed-loop stability in the presence of constraints, is designed, and the constrained stability region associated with it is explicitly characterized using Lyapunov-based tools. Next, a fault-detection filter is designed to detect the occurrence of a fault in the control actuator by observing the deviation of the process states from the expected closed-loop behavior. A switching policy is then derived, on the basis of the stability regions, to orchestrate the activation/deactivation of the constituent control configurations in a way that guarantees closed-loop stability in the event of control system faults. Closed-loop system simulations demonstrate the effectiveness of the fault-tolerant control strategy.     

Command-filter-based distributed containment control of nonlinear multi-agent systems with actuator failures

In this paper, the problem of distributed containment fault-tolerant control for a class of nonlinear multi-agent systems in strict-feedback form is studied. The considered nonlinear multi-agent systems are subject to unknown nonlinear functions and actuator faults with loss of effectiveness and lock-in-place. By resorting to the universal approximation capability of fuzzy logical systems, the command filtered backstepping technique and nonlinear fault-tolerant control theory, distributed controllers are designed recursively. From the Lyapunov stability theory, it is proved that all signals of the resulting closed-loop systems are cooperatively semi-globally uniformly ultimately bounded and the containment errors converge to a small neighbourhood of origin by properly tuning the design parameters. Finally, a numerical example is provided to show the effectiveness of the proposed control method.     

一类不确定性离散非线性重复过程的迭代学习容错控制

针对一类具有非线性和执行器故障的重复运行不确定离散系统,提出了一种迭代学习鲁棒容错控制算法.首先通过定义执行器故障系数矩阵,将迭代学习控制过程转化为等价形式的不确定性非线性重复过程模型,然后基于混合李亚普若夫函数方法讨论非线性重复过程在时间轴和批次轴两个维度上的稳定性,并以线性矩阵不等式形式给出鲁棒容错控制器存在的充分条件和设计方法,同时保证系统正常和执行器故障情形下系统的容错稳定性能.最后,单杆机械手系统的输出跟踪控制仿真结果验证了本文算法的有效性.     

Robust actuator fault isolation and management in constrained uncertain parabolic PDE systems

This paper presents a methodology for the design of an integrated robust fault detection and isolation (FDI) and fault-tolerant control (FTC) architecture for distributed parameter systems modeled by nonlinear parabolic Partial Differential Equations (PDEs) with time-varying uncertain variables, actuator constraints and faults. The design is based on an approximate finite-dimensional system that captures the dominant dynamics of the PDE system. Initially, an invertible coordinate transformation-obtained through judicious actuator placement-is used to transform the approximate system into a form where the evolution of each state is excited directly by only one actuator. For each state, a robustly stabilizing bounded feedback controller that achieves an arbitrary degree of asymptotic attenuation of the effect of uncertainty is then synthesized and its constrained stability region is explicitly characterized in terms of the constraints, the actuator locations and the size of the uncertainty. A key idea in the controller synthesis is to shape the fault-free closed-loop response of each state in a prescribed fashion that facilitates the derivation of (1) dedicated FDI residuals and thresholds for each actuator, and (2) an explicit characterization of the state-space regions where FDI can be performed under uncertainty and constraints. A switching law is then derived to orchestrate actuator reconfiguration in a way that preserves robust closed-loop stability following FDI. Precise FDI rules and control reconfiguration criteria that account for model reduction errors are derived for the implementation of the FDI-FTC structure on the distributed parameter system. Finally, the results are demonstrated using a tubular reactor example.     

Finite-time Adaptive Fault-tolerant Control for Nonlinear Systems With Multiple Faults

This paper focuses on the problem of adaptive finitetime fault-tolerant control for a class of non-lower-triangular nonlinear systems. The faults encountered in the control system include the actuator faults and the abrupt system fault. By applying backstepping design and neural networks approximation, an adaptive finite-time fault-tolerant control scheme is developed. It is shown that the proposed controller ensures that all signals in the closed-loop system are semi-globally practically finite-time stable and the track-ing error converges to a small neighborhood around the origin within finite time. The simulation is carried out to explain the validity of the developed strategy.      

Asymptotic tracking control of uncertain MIMO nonlinear systems with extended condition for controllability

For uncertain multiple-inputs multi-outputs nonlinear systems, it is nontrivial to achieve asymptotic tracking due to the intrinsic coupling among inputs, while the controllability conditions in most existing methods are rather restrictive or even impractical especially when unexpected actuator faults are involved. In this article, we focus on extending such controllability condition by resorting to the existence (instead of a priori knowledge) of some feasible auxiliary matrix, upon which a robust adaptive control scheme is first presented in the absence of actuator faults that is not only able to achieve asymptotic tracking even in the presence of non-parametric uncertainties with all the closed-loop signals globally ultimately uniformly bounded, but also able to deal with a larger class of system models. Furthermore, for the case with intermittent actuator faults, we develop a fault-tolerant control scheme with extended condition for controllability that is able to accommodate such faults automatically without using any fault detection or fault diagnosis unit. The effectiveness and benefits of the proposed method are verified via simulation on robotic systems.     

Fault estimation and active fault-tolerant control for a class of nonlinear systems with actuator and sensor faults based on unknown input iterative learning

In this paper, fault estimation and active fault-tolerant control are studied for a class of nonlinear systems with simultaneous actuator and sensor faults, as well as unknown external disturbances. Firstly, the state equation of a class of nonlinear systems is transformed into an augmented system state equation by extending the sensor fault as an auxiliary state. Then, a novel fault estimation observer based on iterative learning with unknown inputs is designed to estimate the system state, as well as actuator and sensor faults. Subsequently, by using the fault estimation information, a dynamic output feedback active fault-tolerant control scheme is proposed to compensate for the influence of faults on the system. Lyapunov stability theory is used to prove the stability of the closed-loop system and the convergence of the fault estimation observer. The gain matrices of the fault estimation observer and fault-tolerant controller are obtained by solving linear matrix inequalities. Furthermore, the paper avoids the use of the $$ norm in the convergence proof of the conventional iterative learning algorithm, which reduces the amount of calculation in the derivation process. Finally, the effectiveness and accuracy of the proposed method are verified through simulation of the DC motor angular velocity system.     

Adaptive actuator fault compensation for linear systems with matching and unmatching uncertainties

The problem of process systems subject to actuator faults (partial loss of actuator effectiveness) is considered. An active fault compensation control law is designed that utilizes compensation in a way that accounts for matching and unmatching uncertainties and the occurrence of actuator faults. The main idea is designing the robust compensation controller to guarantee closed-loop stability in the presence of faults, based on a neural network representation of the fault dynamics. Changes in the system due to faults are modeled as unknown nonlinear functions. The updating control law is derived such that all the parameters of the closed-loop system are bounded. An output feedback controller is used to the “healthy” system and the adaptive feedback controller is used to compensate for the effect of the dynamics caused by the fault. The advantage of fault compensation is the dynamics caused by faults can be accommodated online. The proposed design method is illustrated on a three-tank system.     

Fault tolerant control using a fuzzy predictive approach

This paper proposes the application of fault-tolerant control (FTC) using fuzzy predictive control. The FTC approach is based on two steps, fault detection and isolation (FDI) and fault accommodation. The fault detection is performed by a model-based approach using fuzzy modeling and fault isolation uses a fuzzy decision making approach. The information obtained on the FDI step is used to select the model to be used in fault accommodation, in a model predictive control (MPC) scheme. The fault accommodation is performed with one fuzzy model for each identified fault. The FTC scheme is used to accommodate the faults of two systems a container gantry crane and three tank benchmark system. The fuzzy FTC scheme proposed in this paper was able to detect, isolate and accommodate correctly the considered faults of both systems.     

Adaptive fault-tolerant control of linear systems with actuator saturation and L2-disturbances

This paper studies the problem of designing adaptive fault-tolerant H-infinity controllers for linear timeinvariant systems with actuator saturation. The disturbance tolerance ability of the closed-loop system is measured by an optimal index. The notion of an adaptive H-infinity performance index is proposed to describe the disturbance attenuation performances of closed-loop systems. New methods for designing indirect adaptive fault-tolerant controllers via state feedback are presented for actuator fault compensations. Based on the on-line estimation of eventual faults, the adaptive fault-tolerant controller parameters are updated automatically to compensate for the fault effects on systems. The designs are developed in the framework of the linear matrix inequality （LMI） approach, which can guarantee the disturbance tolerance ability and adaptive H-infinity performances of closed-loop systems in the cases of actuator saturation and actuator failures. An example is given to illustrate the efficiency of the design method.     

Nonlinear Actuator Fault Detection for Small-Scale UASs

This paper presents a recursive strategy for online detection of actuator faults on a unmanned aerial system (UAS) subjected to accidental actuator faults. The proposed detection algorithm aims to provide a UAS with the capability of identifying and determining characteristics of actuator faults, offering necessary flight information for the design of fault-tolerant mechanism to compensate for the resultant side-effect when faults occur. The proposed fault detection strategy consists of a bank of unscented Kalman filters (UKFs) with each one detecting a specific type of actuator faults and estimating corresponding velocity and attitude information. Performance of the proposed method is evaluated using a typical nonlinear UAS model and it is demonstrated in simulations that our method is able to detect representative faults with a sufficient accuracy and acceptable time delay, and can be applied to the design of fault-tolerant flight control systems of UASs.     

Adaptive fault-tolerant control of nonlinear uncertain systems: an information-based diagnostic approach

This paper presents a unified methodology for detecting, isolating and accommodating faults in a class of nonlinear dynamic systems. A fault diagnosis component is used for fault detection and isolation. On the basis of the fault information obtained by the fault-diagnosis procedure, a fault-tolerant control component is designed to compensate for the effects of faults. In the presence of a fault, a nominal controller guarantees the boundedness of all the system signals until the fault is detected. Then the controller is reconfigured after fault detection and also after fault isolation, to improve the control performance by using the fault information generated by the diagnosis module. Under certain assumptions, the stability of the closed-loop system is rigorously investigated. It is shown that the system signals remain bounded and the output tracking error converges to a neighborhood of zero.     

临近空间飞行器的模型参考滑模容错控制

针对临近空间飞行器中未知的执行器控制效益损失和漂移故障,提出了一种模型参考滑模容错控制方法,保证故障系统对参考模型的稳定跟踪性能。利用跟踪误差系统设计容错控制器,首先构造积分滑模面,以增强系统鲁棒性并消除稳态误差;随后,在无需故障诊断单元的条件下设计模型参考滑模控制律,使其增益能实现自适应调节以处理未知故障影响,其中自适应律基于李雅普诺夫稳定性理论设计,保证闭环系统稳定。在临近空间飞行器纵向动力学模型上的仿真验证表明,该方法能处理执行器中发动机节流阀调节通道和升降舵偏转量通道的不同故障,保证系统获得满意的鲁棒容错跟踪性能。     

State space model predictive fault-tolerant control for batch processes with partial actuator failure

This paper presents a state space model predictive fault-tolerant control scheme for batch processes with unknown disturbances and partial actuator faults. To develop the model predictive fault-tolerant control, the batch process is first treated into a non-minimal representation using state space transformation. The relevant concepts of the corresponding model predictive fault-tolerant control is thus introduced through state space formulation, where improved closed-loop control performance is achieved even with unknown disturbances and actuator faults, because, unlike traditional model predictive fault-tolerant control, the proposed control method can directly regulate the process output/input changes in the design. For performance comparison, a traditional model predictive fault-tolerant control is also designed. Application to injection velocity control shows that the proposed scheme achieve the design objective well with performance improvement.     

Adaptive fuzzy output-feedback fault-tolerant tracking control of a class of uncertain nonlinear switched systems

ABSTRACT

This paper considers the output-feedback fault-tolerant tracking control problem for a class of uncertain nonlinear switched systems with nonlinear faults and strict-feedback form, where the faults which are nonaffine occur on the actuator. As a kind of specialised function approximating tool, fuzzy logic systems (FLSs), are employed to approximate the unknown smooth nonlinear functions. A switched fuzzy observer is designed to address the problem of unmeasurable states, filtered signals are used to address algebraic loop problem and the average dwell time (ADT) method is further utilised to prove the stability of the resulting closed-loop systems under a type of slowly switching signals. Based on the backstepping recursive design technique and Lyapunov function method, an adaptive fuzzy output-feedback control scheme is developed. The developed control method can ensure all the signals are semi-globally uniformly ultimately bounded (SGUUB) and the system output tracks the reference signal tightly even if unknown fault occurs. A simulation carried on an example demonstrates the validity of the obtained control scheme.     

Distributed adaptive fault-tolerant control against actuator faults and lossy interconnection links

This paper presents an adaptive method to solve the robust fault-tolerant control （FTC） problem for a class of large scale systems against actuator failures and lossy interconnection links. In terms of the special distributed architectures, the adaptation laws are proposed to estimate the unknown eventual faults of actuators and interconnections, constant external disturbances, and controller parameters on-line. Then a class of distributed state feedback controllers are constructed for automatically compensating the fault and disturbance effects on systems based on the information from adaptive schemes. On the basis of Lyapunov stability theory, it shows that the resulting adaptive closed-loop large-scale system can be guaranteed to be asymptotically stable in the presence of uncertain faults of actuators and interconnections, and constant disturbances. The proposed design technique is finally evaluated in the light of a simulation example.     

Data-based Fault Tolerant Control for Affine Nonlinear Systems Through Particle Swarm Optimized Neural Networks

In this paper, a data-based fault tolerant control (FTC) scheme is investigated for unknown continuous-time (CT) affine nonlinear systems with actuator faults. First, a neural network (NN) identifier based on particle swarm optimization (PSO) is constructed to model the unknown system dynamics. By utilizing the estimated system states, the particle swarm optimized critic neural network (PSOCNN) is employed to solve the Hamilton-Jacobi-Bellman equation (HJBE) more efficiently. Then, a data-based FTC scheme, which consists of the NN identifier and the fault compensator, is proposed to achieve actuator fault tolerance. The stability of the closed-loop system under actuator faults is guaranteed by the Lyapunov stability theorem. Finally, simulations are provided to demonstrate the effectiveness of the developed method.      

Fault-tolerant control of nonlinear system

The design strategies of fault-tolerant control system (FTCS) are developed, which are categorized into two types: redundant design and fault compensation. In the first type, a certain degree of redundancy is introduced to controller. The resulting closed-loop system is stable not only when all actuators are operational but also only when one actuator experiences fault. In the second type, the online fault-tolerant control (FTC) scheme is developed based on the fuzzy logic system. The closed-loop stability is established based on Lyapunov’s sense. The resulting closed-loop system is stable by using the corrective control law. Compared with the existing results, the fault is accommodated by the fault compensator. The updating control law is so derived that all the parameters of the closed-loop system are bounded. The advantage of redundant design is that it is unnecessary to know the position and magnitude of the fault and is performed without FDI, which reduce the computing time and avoid the false alarms, non-detection and delay due to FDI. The advantage of fault compensation is the dynamics caused by faults that can be accommodated online. Examples of the proposed design indicate that the approaches are effective.