Supervisory fault tolerant control for a class of uncertain nonlinear systems

This paper focuses on the design of a unique scheme that simultaneously performs fault isolation and fault tolerant control for a class of uncertain nonlinear systems with faults ranging over a finite cover. The proposed framework relies on a supervisory switching among a family of pre-computed candidate controllers without any additional model or filter. The states are ensured to be bounded during the switching delay, which ends when the correct stabilizing controller has been selected. Simulation results about a flexible joint robotic example illustrate the efficiency of the proposed method.     

可重构模块机器人分散容错控制

针对可重构模块机器人的执行器故障,提出一种基于自适应模糊系统的分散被动容错控制方法.该方法不需要机器人动力学模型与模块之间的信息交换,模块控制器分别采用间接和直接自适应方法设计,自适应参数的更新律基于Lyapunov稳定性理论设计,保证了系统的稳定性和H∞跟踪性能.数值仿真结果表明了所提出方法的有效性.     

Fault tolerant control for a dearomatisation process

In this paper, a fault tolerant control (FTC) for a dearomatisation process in the presence of faults in online product quality analysers is presented. The FTC consists of a fault detection system (FDI) and a logic for triggering predefined FTC actions. FDI is achieved by combining several process data driven approaches for detecting faults in online quality analysers. The FTC exploits the diagnostic information in adapting a quality controller (MPC) to the faulty situation by manipulating tuning parameters of the MPC to produce both proactive and reactive strategies. The proposed FTC was implemented, tested offline and validated onsite at the Naantali oil refinery. The successful testing and plant validation results are presented and discussed.     

Interval Type-2 fuzzy voter design for fault tolerant systems

A voting scheme constitutes an essential component of many fault tolerant systems. Two types of voters are commonly used in applications of real-valued systems: the inexact majority and the amalgamating voters. The inexact majority voter effectively isolates erroneous modules and is capable of reporting benign outputs when a significant disagreement is detected. However, an application specific voter threshold must be provided. On the other hand, amalgamating voter, such as the weighted average voter, reduces the influence of faulty modules by averaging the input values together. Unlike the majority voters, amalgamating voters are not capable of producing benign outputs. In the past, a Type-1 (T1) fuzzy voting scheme was introduced, allowing for both smooth amalgamation of voter inputs and effective signalization of benign outputs. The presented paper proposes an extension to the fuzzy voting scheme via incorporating Interval Type-2 (IT2) fuzzy logic. The IT2 fuzzy logic allows for an improved handling of uncertain assumptions about the distributions of noisy and erroneous inputs which are essential for correct design of the fuzzy voting scheme. The proposed voter design features robust performance when the uncertainty assumptions dynamically change over time. The IT2 fuzzy voter architecture was compared against the average voter, inexact majority voter, and the T1 fuzzy voter using a refined experimental harness. The reported results demonstrate improved availability, safety and reliability of the presented IT2 fuzzy voting scheme.     

Robust adaptive fault tolerant control for a process with actuator faults

This paper studies design and implementation of an enhanced multivariable adaptive control scheme for an uncertain nonlinear process exposed to actuator faults. For adaptive fault compensation, a model reference adaptive control (MRAC) strategy is utilized as main controller. A new adaptation algorithm making possible to improve transient performance of adaptive control is integrated to the controller. With the help of further modifications, some restrictive conditions on multivariable adaptive design are relaxed so that the system requires less plant information. The resulting controller has a simpler structure than the other matrix factorization based controllers. At the final stage of design, a robust adaptive control scheme is obtained with consideration of practical implementation problems such as sensor noises, external disturbances and unmodeled​ system dynamics. It is proved that the controller guarantees closed-loop signal boundedness and asymptotic output tracking. Real-time experiment results acquired from quadruple tank benchmark system are presented in order to exhibit the effectiveness of the proposed scheme.     

非线性系统主动容错控制综述

以故障发生部位为分类视角,分别从传感器故障、执行器故障及其他部件故障3个方面,较为详细地对近5年非线性系统主动容错控制的研究进展情况进行了归纳和总结,重点讨论了执行器故障的容错控制问题,并对所存在的问题与未来的发展趋势进行了探讨。     

Differential geometry based active fault tolerant control for aircraft

This work shows how to use a differential geometry tool to design a novel nonlinear active fault tolerant flight control system for aircraft. The proposed control scheme consists of two main subsystems: a controller, which is designed for the nominal plant, and a fault detection and diagnosis module, which provides fault estimation. A further feedback loop exploits the fault estimation to accommodate faults affecting the system. The estimate convergence and the stability of the active fault tolerant flight controller are theoretically proved. Finally, high fidelity simulations show the effectiveness of the scheme.     

Multisensor switching control strategy with fault tolerance guarantees

In this paper we propose a novel fault tolerant multisensor switching strategy for feedback control. Each sensor of the proposed multisensor scheme has an associated state estimator which, together with a state feedback gain, is able to individually stabilise the closed-loop system. At each instant of time, the switching strategy selects the sensor-estimator pair that provides the best closed-loop performance, as measured by a control-performance criterion. We establish closed-loop stability of the resulting switching scheme under normal (fault-free) operating conditions. More importantly, we show that closed-loop stability is preserved in the presence of faulty sensors if a set of conditions on the system parameters (such as bounds on the sensor noises, maximum and minimum values of the reference signal, etc.) is satisfied. This result enhances and broadens the applicability of the proposed multisensor scheme since it provides guaranteed properties such as fault tolerance and robust closed-loop stability under sensor fault. The results are applied to the problem of automotive longitudinal control.     

Fault tolerant control of a simulated hydroelectric system

This paper analyses the application of two fault tolerant control schemes to a hydroelectric model developed in the Matlab and Simulink environments. The proposed fault tolerant controllers are exploited for regulating the speed of the Francis turbine included in the hydraulic system. The nonlinear behaviour of the hydraulic turbine and the inelastic water hammer effects are taken into account in order to develop a high-fidelity simulator of this dynamic plant. The first fault tolerant control solution relies on an adaptive control design, which exploits the recursive identification of a linear parametric time-varying model of the monitored system. The second scheme proposed uses the identification of a fuzzy model that is exploited for the reconstruction of the fault affecting the system under diagnosis. In this way, the fault estimation and its accommodation is possible. Note that these strategies, which are both based on identification approaches, are suggested for enhancing the application of the suggested fault tolerant control methodologies. These characteristics of the study represent key issues when on-line implementations are considered for a viable application of the proposed fault tolerant control schemes. The faults considered in this paper affect the electric servomotor used as a governor, the hydraulic turbine speed sensor, and the hydraulic turbine system, and are imposed both separately and simultaneously. Moreover, the complete drop of the rotational speed sensor is also analysed. Monte-Carlo simulations are also used for analysing the most important issues of the proposed schemes in the presence of parameter variations. Moreover, the performances achieved by means of the proposed solutions are compared to those of a standard PID controller already developed for the considered model. Finally, these strategies serve to highlight the potential application of the proposed control strategies to real hydraulic systems.     

Model-based diagnosis and fault tolerant control for ensuring torque functional safety of pedal-by-wire systems

This paper presents a model based approach for defining automotive functional safety requirements and provides a solution to ensure functional safety through model-based diagnosis and fault tolerant control. This model-based approach is consistent with ISO 26262 – functional safety standard. In particular, this paper presents the necessary steps for defining and implementing functional safety requirements, including item and function definition, Hazard Analysis and Risk Assessment, as well as the design of a model-based diagnostic and fault tolerant control (FTC) system that can lead to a systematic solution to automotive functional safety problems. The methodology proposed in this paper is applied to the problem of torque functional safety of pedal-by-wire systems.     

Control performance‐based fault detection and fault‐tolerant control schemes for a class of nonlinear systems

The objective of this paper is to develop performance‐based fault detection (FD) and fault‐tolerant control (FTC) schemes for a class of nonlinear systems. To this end, the representation forms of nonlinear systems with faults and the controller parameterization forms are studied first with the aid of the nonlinear factorization technique. Then, based on the stable kernel representation and the stable image representation of the faulty nonlinear system, the stability performance of the closed‐loop system is addressed, respectively. The so‐called fault‐tolerant margin is defined to evaluate the system fault‐tolerant ability. On this basis, two performance‐based FD schemes are developed aiming at detecting the system performance degradation caused by system faults. Furthermore, to recover the system stability performance, two performance‐based FTC strategies are proposed based on the information provided by the FD unit. In the end, a numerical example and a case study on the three‐tank system are given to demonstrate the proposed results.     

Statistical signal processing approaches to fault detection

The parity space approach to fault detection and isolation (FDI) has been developed during the last 20 years, and the focus here is to describe its application to stochastic systems. A mixed model with both stochastic inputs and deterministic disturbances and faults is formulated over a sliding window. Algorithms for detecting and isolating faults on-line and analyzing the probability for correct and incorrect decisions off-line are provided. A major part of the paper is devoted to discussing properties of this model-based approach and generalizations to cases of incomplete model knowledge, and non-linear non-Gaussian models. For this purpose, a simulation example is used throughout the paper for numerical illustrations, and real-life applications for motivations. The final section discusses the reverse problem: fault detection approaches to statistical signal processing. It is motivated by three applications that a simple CUSUM detector in feedback loop with an adaptive filter can mitigate the inherent trade-off between estimation accuracy and tracking speed in linear filters.     

A virtual actuator and sensor approach for fault tolerant control of LPV systems

In this paper, a fault tolerant control (FTC) strategy using virtual actuators and sensors for linear parameter varying (LPV) systems is proposed. The main idea of this FTC method, initially developed for LTI systems, is to reconfigure the control loop such that the nominal controller could still be used without need of retuning it. The plant with the faulty actuator/sensor is modified adding the virtual actuator/sensor block that masks the actuator/sensor fault. The suggested technique is an active FTC strategy that reconfigures the virtual actuator/sensor on-line taking into account faults and operating point changes. The stability of the reconfigured control loop is guaranteed if the faulty plant is stabilizable/detectable. The LPV virtual actuator/sensor is designed using polytopic LPV techniques and linear matrix inequalities (LMIs). A two-tank system simulator is used to assess the performance of the proposed method. In particular, it is shown that the application of the proposed technique results in an improvement, in terms of performance, with respect to the LTI counterpart.     

Distributed active fault tolerant control design against actuator faults for multiple mobile robots

This paper investigates the active fault tolerant cooperative control problem for a team of wheeled mobile robots whose actuators are subjected to partial or severe faults during the team mission. The cooperative robots network only requires the interaction between local neighbors over the undirected graph and does not assume the existence of leaders in the network. We assume that the communication exists all the time during the mission. To avoid the system''s deterioration in the event of a fault, a set of extended Kalman filters (EKFs) are employed to monitor the actuators'' behavior for each robot. Then, based on the online information given by the EKFs, a reconfigurable sliding mode control is proposed to take an appropriate action to accommodate that fault. In this research study, two types of faults are considered. The first type is a partial actuator fault in which the faulty actuator responds to a partial of its control input, but still has the capability to continue the mission when the control law is reconfigured. In addition, the controllers of the remaining healthy robots are reconfigured simultaneously to move within the same capability of the faulty one. The second type is a severe actuator fault in which the faulty actuator is subjected to a large loss of its control input, and that lead the exclusion of that faulty robot from the team formation. Consequently, the remaining healthy robots update their reference trajectories and form a new formation shape to achieve the rest of the team mission.     

Industrial actuator benchmark for fault detection and isolation

Feedback control systems are vulnerable to faults within the control loop, because feedback actions may cause abrupt responses and process damage when faults occur. Such faults can be detected by model-based methods for fault detection and isolation (FDI) but research results have not been widely accepted in industry. One reason has been a scarcity of realistic examples for testing FDI methods against industrial systems. These special section papers focus on a common benchmark example, an electro-mechanical position servo, used in speed control of large diesel engines. The result is a platform for comparison of FDI methods and a gathering together of design experience on a simple, yet very realistic, industrial example. This paper introduces the benchmark problem, overviews the FDI methods used within the papers and discusses the results.     

A performance optimization algorithm for controller reconfiguration in fault tolerant distributed model predictive control

This paper presents a performance optimization algorithm for controller reconfiguration in fault tolerant distributed model predictive control for large-scale systems. After the fault has been detected and diagnosed, several controller reconfigurations are proposed as candidate corrective actions for fault compensation. The solution of a set of constrained optimization problems with different actuator and setpoint reconfigurations is derived by means of an original approach, exploiting the information on the active constraints in the non-faulty subsystems. Thus, the global optimization problem is split into two optimization subproblems, which enable the online computational burden to be greatly reduced. Subsequently, the performances of different candidate controller reconfigurations are compared, and the better performing one is selected and then implemented to compensate the fault effects. Efficacy of the proposed approach has been shown by applying it to the benzene alkylation process, which is a benchmark process in distributed model predictive control.     

Closed-loop fault diagnosis based on a nonlinear process model and automatic fuzzy rule generation

In this contribution a new approach for fault detection and diagnosis (FDD) for nonlinear processes is presented. A nonlinear fuzzy model with transparent inner structure is used for the generation of relevant symptoms. The resulting symptom patterns are classified with a new self-learning classification structure based on fuzzy rules. The approach is successfully applied to an electro-pneumatic valve in a closed control loop.     

Robust adaptive fault estimation and fault tolerant control for quadrotor attitude systems

ABSTRACT

This paper addresses the problem of fault estimation and fault tolerant control for quadrotor unmanned aerial vehicle. Firstly, a robust adaptive fault estimation observer (AFEO) is proposed to achieve fault estimation of quadrotor with actuator fault in the presence of external disturbances and parameter uncertainties. Furthermore, based on the estimation of fault, a dynamic output feedback fault tolerant controller (DOFFTC) is designed to stabilise the closed-loop system with faults and uncertainties. Sufficient conditions for the existence of both AFEO and DOFFTC are given in terms of linear matrix inequalities. Finally, simulation results are presented to illustrate the effectiveness of the proposed strategy.     

Robust fault diagnosis and fault‐tolerant control for non‐Gaussian uncertain stochastic distribution control systems

The purpose of fault diagnosis of stochastic distribution control systems is to use the measured input and the system output probability density function to obtain the fault estimation information. A fault diagnosis and sliding mode fault‐tolerant control algorithms are proposed for non‐Gaussian uncertain stochastic distribution control systems with probability density function approximation error. The unknown input caused by model uncertainty can be considered as an exogenous disturbance, and the augmented observation error dynamic system is constructed using the thought of unknown input observer. Stability analysis is performed for the observation error dynamic system, and the H_∞ performance is guaranteed. Based on the information of fault estimation and the desired output probability density function, the sliding mode fault‐tolerant controller is designed to make the post‐fault output probability density function still track the desired distribution. This method avoids the difficulties of design of fault diagnosis observer caused by the uncertain input, and fault diagnosis and fault‐tolerant control are integrated. Two different illustrated examples are given to demonstrate the effectiveness of the proposed algorithm. Copyright © 2016 John Wiley & Sons, Ltd.