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 eventtriggered 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.     

基于一个学习逼近的非线性系统的故障调节

很多学者对故障诊断和容错控制问题给予很大关注.特别是对于安全系统,故障诊断固然重要,最快地调节故障系统也是很重要的.例如当今的高性能飞行器即使发生故障仍需保持基本的运行状态.对于非线性系统提出一种故障调节控制器的设计方法,通过修正控制律补偿故障所带来的影响.故障发生后使用的神经网络用于逼近故障函数并提供故障的修正行为.即主动容错.故障调节后闭环系统是稳定的.仿真算例证明了此方法的有效性.     

Fault accommodation for nonlinear systems using fuzzy adaptive sliding control

An active fault accommodation control law is developed for a class of nonlinear systems to guarantee the closed-loop stability in the presence of a fault, based on a fuzzy logic system representation of the dynamics due to faults. It uses fuzzy logic system to approximate the dynamic caused by the fault. Through the adaptive process of the parameters, the dynamics caused by the fault is counteracted. The fuzzy sliding mode control is introduced to attenuate the fuzzy approximation error. Simultaneity, the closed-loop system is stable in Lyapunov sense and the tracking error converges to a neighbourhood of zero. The example of the proposed design indicates that the fault accommodation control law is effective for a nonlinear system.     

基于模糊自适应滑模的非线性系统的故障调节

对于非线性系统提出故障调节控制的设计方法,通过附加控制律补偿故障所带来的影响．利用模糊逻辑系统估计故障并提供故障的修正行为,即主动容错．引入滑模控制抵消模糊逼近误差,经故障调节后闭环系统是稳定的．通过仿真算例证明了该方法的有效性．     

基于神经网络观测器的一类非线性系统的故障调节

将一般形式的非线性模型线性化为输出反馈型．针对该类系统,首先利用神经网络的一致逼近任意非线性连续函数的性质,构造神经网络自适应观测器,以获取反映故障信息的残差;然后根据残差信息在线估计故障;最后通过修正控制律来补偿故障所带来的影响．并采用Lyapunov稳定性理论证明了系统的稳定性．仿真结果验证了该方法的有效性．     

Fault Detection, Isolation, and Accommodation Control in Robotic Systems

In this paper, fault diagnosis and accommodation control are developed for robotic systems. First, a nonlinear observer in the proposed method is designed based on the available model. The fault detection is carried out by comparing the observer states with their signatures. Secondly, state observers are constructed based on possible fault function sets. Thirdly, the accommodation control design is developed using a normal controller plus a neural network compensator to capture the nonlinear characteristics of faults. Finally, if the fault isolation is completed successfully, the second fault accommodation controller is presented based on the fault information obtained by the isolation scheme.      

基于逆系统迭代学习观测器的故障调节方法

针对一类满足Lipschitz条件的多输入多输出非线性可逆系统执行器故障问题,提出了一种基于迭代学习观测器的逆系统内模故障调节方法。引入PD型迭代学习策略,设计了迭代学习故障诊断观测器,用于对执行器未知时变故障进行快速、准确估计。根据故障估计值,结合逆系统方法对逆模型进行补偿,使得补偿后的逆模型与非线性被控对象串联仍为伪线性系统;再结合内模控制实现了伪线性系统的容错控制。最后,通过仿真算例验证了该方案的有效性。     

Fault detection and accommodation of a class of nonlinear systems with unknown multiple time-delayed faults

This paper investigates a fault detection and accommodation (FDA) problem of a class of nonlinear time-delay systems in the presence of unknown multiple time-delayed faults. Compared with existing literature, a main contribution of this paper is to design a time-delay independent FDA scheme, namely, the exact information on time delays is not required to implement the proposed FDA scheme. Under the assumption that the magnitude and occurrence time of multiple faults are unknown, we first design a delay-independent fault detection scheme with a detection threshold for time-delay systems and analyze the fault detectability. Then, an approximation-based fault accommodation design activated after the detection of the first fault is presented for compensating multiple faults. The robustness of the fault detection scheme and asymptotic stability of the tracking error are established through Lyapunov stability analysis. A simulation example is used to illustrate the proposed FDA scheme.     

Robust adaptive fault accommodation for a robot system using a radial basis function neural network

A discrete-time radial basis function (RBF) neural network is designed for the fault accommodation of robotic systems. A robust learning algorithm using the adaptive dead-zone technique is presented to train the network parameters (weights and centres). This scheme assures the convergence of the estimate errors of both the neural network and the fault-monitoring system in the presence of system uncertainties. Simulations have been done on applying the RBF-network-based fault accommodation scheme to a two-link robotic manipulator. The main advantage of the adaptive algorithm is that the upper bound of system uncertainties is not known in advance, which makes the system more practical for the fault accommodation scheme as demonstrated.     

基于神经网络的非线性系统轨迹线性化自适应容错控制

针对一类仿射非线性系统,首先采用轨迹线性化方法将其等价表示为线性时变系统;然后利用神经网络构建伪逆模型以及动态故障模型：最后基于模型参数变化,应用李亚普诺夫稳定性理论构建标称系统控制器及故障补偿控制律,从而实现系统故障下的稳定有界容错控制．仿真结果表明了所提出算法的有效性．     

Distributed adaptive fault‐tolerant leader‐following formation control of nonlinear uncertain second‐order multi‐agent systems

This paper presents a distributed integrated fault diagnosis and accommodation scheme for leader‐following formation control of a class of nonlinear uncertain second‐order multi‐agent systems. The fault model under consideration includes both process and actuator faults, which may evolve abruptly or incipiently. The time‐varying leader communicates with a small subset of follower agents, and each follower agent communicates to its directly connected neighbors through a bidirectional network with possibly asymmetric weights. A local fault diagnosis and accommodation component are designed for each agent in the distributed system, which consists of a fault detection and isolation module and a reconfigurable controller module comprised of a baseline controller and two adaptive fault‐tolerant controllers, activated after fault detection and after fault isolation, respectively. By using appropriately the designed Lyapunov functions, the closed‐loop stability and asymptotic convergence properties of the leader‐follower formation are rigorously established under different modes of the fault‐tolerant control 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.     

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.     

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.     

Robust fault-tolerant control for a biped robot using a recurrent cerebellar model articulation controller.

A design technique of a recurrent cerebellar model articulation controller (RCMAC)-based fault-tolerant control (FTC) system is investigated to rectify the nonlinear faults of a biped robot. The proposed RCMAC-based FTC (RCFTC) scheme contains two components: 1) an online fault estimation module based on an RCMAC is used to provide approximation information for any nonnominal behavior due to the system failure and modeling error of the biped robot; and 2) a controller module consisting of a computed torque controller and a robust FTC is utilized to achieve FTC. In the controller module, the computed torque controller reveals a basic stabilizing controller to stabilize the system, and the robust FTC is utilized to compensate for the effects of the system failure so as to achieve fault accommodation. The adaptive laws of the RCFTC system are rigorously established based on the Lyapunov function, so that the stability of the system can be guaranteed. Finally, two simulation cases of a biped robot are presented to illustrate the effectiveness of the proposed design method. Simulation results show that the RCFTC system can effectively recover the control performance for the system in the presence of the nonlinear faults and modeling uncertainties.     

基于混合卡尔曼滤波器组的航空发动机双通道传感器故障检测

基于机载非线性模型与分段线性卡尔曼滤波器混合组成的混合卡尔曼滤波器组,结合双通道传感器的特点,建立了民用航空发动机传感器故障诊断系统;给出故障诊断原理及算法的同时,将该系统应用于民用涡扇发动机传感器常见典型故障进行了仿真;仿真结果表明,诊断系统可以在发动机发生健康蜕化后,通过只简单更新机载模型的蜕化因子,而保持线性卡尔曼滤波器的参数不变,便能准确地检测和隔离各类传感器故障而不发生误报;该更新过程可以在线自动完成,省时省力,易于工程实现。     

Fault accommodation in nonlinear dynamic systems

The problem of fault accommodation in nonlinear dynamic systems is solved by constructing a control law that provides full decoupling with respect to fault effects. Existence conditions are found, and calculating relations are given for the control law.     

A fault accommodation control for nonlinear systems

Based on the use of neural networks for representation of the dynamics of faults, an active fault accommodation control law is proposed that guarantees the closed-loop stability for a class of nonlinear systems with faults. An example of using the control design proposed demonstrates the efficiency of this law for a typical nonlinear system. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 1, pp. 10–18, January–February 2006.     

四旋翼无人机时延模糊自抗扰容错控制

针对四旋翼无人机系统执行器故障问题,为改善飞行控制系统性能,提出一种时延模糊自抗扰容错控制。首先,根据四旋翼无人机系统非线性数学模型和执行器故障模型,选择模糊自抗扰控制器作为基准控制器,在未发生执行器故障的情况下,使飞行控制系统保持稳定;其次,在发生执行器故障的情况下,利用时延控制技术估计故障信息,并与模糊自抗扰控制相结合,实现容错控制;最后,对所研究的容错控制算法进行数值仿真分析,仿真结果表明:把时延控制与模糊自抗扰控制相结合,能有效调节执行器故障,使飞行控制系统对故障产生的干扰具有良好的鲁棒性。     

Methods of fault accommodation in technical systems

We consider the design problem of methods of full decoupling from fault-generated actions in systems described by a nonlinear dynamical model, where by a fault we mean inadmissible deviations of the parameters of the system from their nominal values. The solution of the problem depends on the formation of a new control law taking into account the behavior of a system with faults. To solve this problem we propose using the logic-dynamic approach, in which the original model of the system is subject to certain transformations, which enables solving nonlinear problems by linear methods. Another feature of this approach is the possibility of dealing with nondifferentiable nonlinearities, such as saturation, backlash, and hysteresis. The solution proposed in this paper is based on the full decoupling from fault-generated actions, which requires the construction of an auxiliary system for the synthesis of a feedback which provides for the required decoupling. Implementation of this method will be instrumental in enhancing the efficiency of fault accommodation in the part of the reduction of computational and time costs when implementing the new control law.