http://www.ifac-papersonline.net/ en Copyright 06:17 PM Tuesday 07, 2012 IFAC-PapersOnline http://www.ifacpapersonline.com 06:17 PM Tuesday 07, 2012 06:17 PM Tuesday 07, 2012 ET webmaster@ifac-papersonline.net webmaster@ifac-papersonline.net http://www.ifac-papersonline.net/Detailed/40096.html 04:00 PM Wednesday 31, 1969 A large transport aircraft simulation benchmark (REconfigurable COntrol for Vehicle Emergency Return RECOVER) has been developed within the GARTEUR Flight Mechanics Action Group 16 on Fault Tolerant Control (2004-2008) for the integrated evaluation of fault detection and identification (FDI) and reconfigurable flight control strategies. The benchmark includes a suitable set of challenging assessment criteria and failure cases, based on reconstructed accident scenarios, to assess the potential of new adaptive control strategies to improve aircraft survivability. The application of reconstruction and modeling techniques, based on accident flight data, has resulted in high fidelity non-linear aircraft and fault models to evaluate new Fault Tolerant Flight Control (FTFC) concepts and their real-time performance to accommodate in-flight failures. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/40244.html 04:00 PM Wednesday 31, 1969 This paper presents a supervisory control strategy based on fuzzy cognitive map (FCM) and genetic algorithm (GA). Fuzzy cognitive maps are a neuro-fuzzy methodology that can model complexly system accurate. In the proposed methodology, the expert knowledge about the process behavior is used to build an initial FCM. This FCM is extended and refined to incorporate control strategies by means of a GA which runs with simulated process data. The resulting FCM is used to generate set points for the regulatory loops in the plant lower level. The developed supervisory control methodology is applied to an alcoholic fermentation process from chemical industry. Comparison of performance is made with another intelligent approach (Fuzzy-PD), and also with a predictive approach based on DMC (Dynamic Matrix Control). http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/40294.html 04:00 PM Wednesday 31, 1969 Nowadays systems are more and more complex, there is intense pressure to continuously reduce and eliminate costly, unscheduled maintenance of these systems. In such case, using physics-based damage model is not adequate in term cost/benefit analysis. While, recent technological advances of new sensors, coupled with robust processing algorithms offer an elegant and theoretically sound approach to Condition-Based Maintenance (CBM)/Prognostic Health Management of such complex systems. A new strategy based on forecasting of system degradation through a prognostic data-driven method is required. This paper introduces the development of a data-driven methodology to predict remaining useful life (RUL) of an unspecified complex system. Remaining useful life prediction is performed by recent machine learning techniques without including any system or domain specific informations. The solution is efficient and easy to implement and has the potential to be applicable to a variety of complex systems (automobiles, aerospace systems). http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/40127.html 04:00 PM Wednesday 31, 1969 In this paper, a fault detection (FD) filter design method is proposed for linear parameter-varying (LPV) systems, which are subject to abrupt changes in their structure. Such a phenomenon is modeled by a finite states Markov chain whose outcome is supposed to be directly available along with its rate transition matrix. The FD Filter is designed as a bank of H_inf Luenberger observers, derived by optimizing frequency conditions which ensure guaranteed level of disturbance rejection and fault sensitivity. It is proved that, resorting to stochastic stability concepts, the design method can be recast as a Linear Matrix Inequality (LMI) program in the observer bank gains. The resulting residual generator is a jump parameter dependent observer and exploits jointly the deterministic plant parameter knowledge and the instantaneous Markov chain realization. A FD threshold logic is proposed in order to reduce the generation of false alarms. The effectiveness of the design technique is illustrated via a numerical example. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/40137.html 04:00 PM Wednesday 31, 1969 This paper presents a MatLab/SIMULINK based toolbox for fault diagnosis. It has been witnessed that while the fault detection methods must be tailored specifically to the process that is to be supervised, the fault diagnosis methods on the other hand are very similar in most applications. Therefore, a MatLab/SIMULINK-based toolbox was developed by the authors which shall be presented in this paper and is available for download. The software is designed such that it can be used with the Real-Time Workshop and can thus be compiled and downloaded to a wide range of rapid control prototyping system. Depending on the type and availability of a-priori knowledge, one can either employ classification or inference methods. Both approaches are supported by development environment. Classification is used whenever there are experimental data available which describe the influence of the faults on the symptoms. The available implementations encompass the Bayes classifier, the k-nearest neighbor and the polynomial classifier. Inference methods are used, whenever rules or expert knowledge describing the influence of the fault on the symptoms are available. In the paper, a Fuzzy-Logic based inference engine is presented, where the symptoms are first fuzzified to account for the uncertainty in the reaction of residuals. Then, the individual symptoms are combined using Fuzzy-Logic AND and OR operators respectively. The mapping of the fuzzy outputs to the diagnosed fault is accomplished by determining the maximum fault possibility among all fault possibilities. The different diagnostic engines have already successfully been applied to a wide range of prototype fault management realizations at the institute and have proven very capable. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/40173.html 04:00 PM Wednesday 31, 1969 A multisensor estimation scheme with the ability to accommodate multiple sensor faults is presented. A switching strategy is employed such that, at each sampling time, a sensor-estimator pair is selected to provide the best state estimate as measured by an optimisation criterion. We show that, if a set of conditions on the system parameters (such as bounds on the sensors noises, disturbances, operating conditions, etc.) is satisfied then the switching estimation scheme is able to guarantee fault tolerant capabilities under multiple sensor failures. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/40100.html 04:00 PM Wednesday 31, 1969 This paper describes the application of a recently developed on-line sliding mode control allocation scheme for fault tolerant control of the lateral and longitudinal axes of the civil aircraft GARTEUR FM-AG16 benchmark problem. The control allocation scheme incorporates the novel use of actuator effectiveness levels to redistribute the control signals to the functioning healthy actuators when a fault or failure occurs, within a sliding mode framework. The paper will discuss the design issues associated with the controller - including the design of the sliding surface, the nonlinear gain required to maintain sliding, and sufficient conditions to ensure the closed-loop system remains stable for a class of faults and failures. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/40152.html 04:00 PM Wednesday 31, 1969 The paper deals with the design of active detector and input signal generator for stochastic discrete-time systems. The active detection problem is formulated for the jump Markov linear Gaussian model. Since the optimal solution is intractable, some simplifications and approximations are considered. Firstly, the problem of discrimination between several models and its optimal solution are obtained as a special case of the active detection problem for jump Markov linear Gaussian model. Then, two different approximations of the optimal solution are carried out to obtain feasible design techniques of the active detector and input signal generator. The first approximation is based on interchanging the minimization and expectation operators. It is shown that this approximation leads to a known approach that uses the Bayesian risk as design criterion. The second approximation is based on l-step lookahead policy and rollout algorithm. Both feasible design techniques are compared in the numerical example. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/40322.html 04:00 PM Wednesday 31, 1969 Fault Detection and Diagnostic (FDD) is usually employed for maintenance management. This paper presents an intelligent system applied to FDD. The method is based on a dynamic B-spline approximation. In case that the fault is verified, then the probability of failure is calculated by employing the Fault Tree Analysis (FTA) technique. A Binary Decision Diagram (BDD) is used to provide an alternative to the traditional cutest-based methods for FTA. The BDD method does not analyse the FTA directly, but converts the tree to a BDD that represents the Boolean equation for the top event. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/40119.html 04:00 PM Wednesday 31, 1969 In this study, a hybrid dynamic Artificial Neural Network (ANN)-based fault diagnosis and tolerance method is developed. The adopted hybrid ANN is a combination of feedforward ANN and recurrent ANN forming a dynamic identification model for the non-linear time-varying system. It has three work modes and can perform the fault and degradation diagnosis and tolerance by using these modes alternately. The result of its application in an Electro-Hydraulic Servomechanism in Hydroelectric Generation Unit shows its effectiveness and ability of online implementation without importing disturbance signals to the system. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/40233.html 04:00 PM Wednesday 31, 1969 A general concern in industrial world is related to process maintenance, safety and availability problems in the presence of faults. Most industrial processes are very large or/and complex. Because of size and complexity, it is very difficult to make a diagnostic system for an entire process and to ensure the availability of it. Designing a Fault Tolerant Networked Control System (FTNCS) to deal with large-scale complex networked control systems is a very difficult task due to the large number of sensors and actuators spatially distributed and networked connected. This paper presents a toolkit to implement multi-agent approaches on distributed FTNCS. The design methodology is made easier using the toolkit presented in this paper. The FTNCS design method is able to use simple and verifiable principles coming mainly from a decentralized design, based on causal modelling partitioning of the NCS and distributed computing using multi-agents systems, allowing the use of well established fault tolerant control methodologies, or new ones, developed taking into account the NCS specificities. A platform with a real process and four computers is used to test the toolkit and network infrastructure. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/40206.html 04:00 PM Wednesday 31, 1969 Diesel engines are today considered leading candidates for the new generations of passenger vehicles due to their fuel efficiency and drivability. One of the key elements for the future acceptability is the compliance with emission standards (particularly on nitrogen oxides), which will require precise control of the aftertreatment system. Furthermore, in light of OBD-II regulations, considerable research must be devoted to the design of fault diagnosis algorithms. The definition of fault diagnosis strategies is a complex process that involves thorough studies of the system behavior in healthy and faulty conditions. Such studies can be done in multiple ways, including experimentation and mathematical modeling. In both cases, a thorough knowledge of the system components, sensors and actuators is required. The proposed paper presents an approach to model-based fault diagnosis of Diesel NOx aftertreatment systems. The proposed methodology is based on a functional and structural analysis of the system, at the level of individual components and assemblies. This facilitates the mapping and characterization of system faults through FTA and FMEA methods, allowing for the design of control-oriented models to be used for fault detection and isolation. In this paper, the outlined approach is applied to a Lean NOx Trap system. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/40068.html 04:00 PM Wednesday 31, 1969 This paper addresses the problem of fault detection and isolation for helicopters used as Unmanned Aerial Vehicles. First a model for a reduced-scale helicopter is presented, then this model is linearized and used to design unknown input observers for fault diagnosis. The developed system is tested and analyzed. The results prove that it represents an effective solution to fault diagnosis problems in Unmanned Aerial Vehicles. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/40065.html 04:00 PM Wednesday 31, 1969 This paper address the problem of fault identification for Reusable Launch Vehicles (RLV) control surfaces. The identification scheme is based on a modified extended Kalman filter which is easy to implement. A solution is provided for systematic tuning the filter noise covariance matrices. It is shown that this problem can be formulated as an optimization problem using a quadratic criterion which can be solved using a Particle Swarm Optimization (PSO) algorithm. A prior trimmability deficiency analysis procedure is also proposed using a state-space modeling approach. The simulation results are quite encouraging and suggest that the proposed fault identification scheme could be an efficient tool for advanced diagnosis algorithm for RLV actuators. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/40270.html 04:00 PM Wednesday 31, 1969 Model-based diagnosis enables the identification of minimal faulty component sets that explain encountered inconsistencies between a system's observed behavior and that of a ``golden'' system model. In this paper, we present a compositional model for the (online-)diagnosis of transient faults (like malfunctioning transportation segments, sensor errors, misrouting, ...) in industrial transportation systems. Instead of analyzing flow parameters or modeling temporal behavior via finite state machines, we consider the temporal and logic constraints about a distributed item's progress separately, and at different abstraction levels. Initial results from an industrial facility show the applicability of our consistency-based diagnosis approach. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/40104.html 04:00 PM Wednesday 31, 1969 In this paper we introduce a method for change detection which uses randomised subsamples of the data. The method is based on the LSCR (Leave-out Sign-dominant Correlation Regions) algorithm for finite sample system identification which generates a region in parameter space which has a guaranteed probability of containing the true parameter. The change detection problem is formulated as a hypothesis testing problem, and the null-hypothesis is accepted if the parameter representing the hypothesis belongs to the confidence set constructed by the LSCR algorithm. This approach delivers a test with a guaranteed low probability of a false alarm for any finite number of observed data points. The test and the associated theory can be applied under very general conditions reducing the amount of necessary prior information to a minimum. The approach is illustrated on two common change detection problems. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/40087.html 04:00 PM Wednesday 31, 1969 This paper presents a speed control of an induction motor. The design uses an feedforward Artificial Neural Network (ANN) to implement a rotor speed estimator, and a robust control strategy based on the sliding-mode. The proposed control scheme also make use of the field oriented control theory to simplify the proposed control design. The stability analysis of the presented control scheme is provided using the Lyapunov stability theory. Finally simulated results show that the presented controller with the proposed observer provides high-performance dynamic characteristics and that this scheme is robust with respect to plant parameter variations and external load disturbances. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/40251.html 04:00 PM Wednesday 31, 1969 This paper deals with the design of guaranteed set-membership fault detection tests based on a continuous time linear dynamical system with parametric uncertainties. A guaranteed discretization preserving affine dependencies on the parameters of the initial continuous time model is proposed. Then, a domain shaping procedure is used in conjunction with a collision detection algorithm to implement a set-membership fault detection test ensuring a guaranteed robustness to bounded parametric uncertainties. Care is taken to ensure the logical consistency of the test results with respect to the initial uncertain continuous time model. The application to an ore crushing and classification process shows the ability to detect some parametric faults. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/40143.html 04:00 PM Wednesday 31, 1969 This paper discusses a knowledge-base encoding methodology for diagnostic tasks. It transform "expert"-provided rules into algebraic expressions so inference of the "possible" disorders is carried out via associated constrained optimisation problems. In this way, the need of conventional fuzzy inference systems or uncertain-logic schemes is no longer present in the particular setting in this paper. The problem is solved by efficient linear programming tools, in principle able to cope with large-scale problems. Direct introduction of the inequalities and cost indices is cumbersome and error-prone so a user-friendly front-end has been developed. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/40115.html 04:00 PM Wednesday 31, 1969 This paper investigates the fault detection and diagnosis for a class of rolling-element bearings using signal-based methods based on the motor's vibration and phase current measurements, respectively. The envelope detection method is employed to preprocess the measured vibration data before the FFT algorithm is used for vibration analysis. The average of a set of Short-Time FFT (STFFT) is used for the current spectrum analysis. A set of fault scenarios, including single and multiple point- defects as well as generalized roughness conditions, are designed and tested under different operational conditions, including different motor speeds, different load conditions and samples from different operating time intervals. The experimental results show the powerful capability of vibration analysis in the bearing point-defect fault diagnosis under stationary operation. The current analysis showed a subtle capability in diagnosis of point-defect faults depending on the type of fault, severity of the fault and operational condition. The generalized roughness fault can not be detected by the proposed frequency methods. The temporal features of the considered faults and their impact on the diagnosis analysis are also investigated. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/40228.html 04:00 PM Wednesday 31, 1969 A new approach to Fault-Tolerant Control(FTC)of distributed and interconnected systems is proposed based on applying sliding mode control (SMC) to the subsystems of a level de-centralised and hierarchical scheme. The SMC approach involves a new optimal control strategy for the design of local sliding functions for the subsystem controllers, replacing the conventional approach based on constrained locally linear LQ receding horizon control. The linear SMC gains handle the reachability for the sliding surfaces and the interaction effects from subsystem interconnections as well as small fault effects (i.e. giving passive fault-tolerance), whilst the non-linear (discontinuous) SMC gains facilitate a powerful way of accounting for larger but bounded system non-inearities and faults and can fulfill the role of an active FTC scheme. The local and global performance constraints are retained and implemented under autonomous learning supervision via the interaction-prediction principle. The scheme for an Autonomous Control and Supervision System (ACSS) is described that is capable of learning its coordination function and carrying out fault-tolerant balancing of the distributed system. The paper describes how the two-level learning strategy offers advantages over single-level FTC distributed SMC. The design concepts are illustrated using a non-linear 3-tank liquid level and heating control system with component faults. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/40159.html 04:00 PM Wednesday 31, 1969 In this article the design of a fault tolerant thrust vector control (TVC) for the automated ascent of the Hopper reusable launch vehicle is presented. The considered ascent starts at the pull-up maneuver performed immediately after horizontal take off and ends at main-engine-cut-off. The TVC law uses nonlinear dynamic inversion (NDI) to obtain the required engine gimbal deflections for robust tracking of the angle of attack and bank angle from a guidance law. The NDI–based TVC is characterized by the use of the Hopper’s engine redundancy layout and by the interpretation of NDI as an achievable dynamics identification scheme. The resulting TVC design has been validated using a Monte Carlo campaign with realistic aerodynamic mismatch, corrupted measurements, parametric uncertainty and high fidelity atmospheric and 6DoF vehicle dynamics models. Evaluation of the design with a wide array of thrust and engine gimbal faults yields that the resulting TVC improves the closed loop fault tolerant capabilities. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/40300.html 04:00 PM Wednesday 31, 1969 On-line diagnosis must accommodate the existing sensoring capabilities of a system, which often results in limited diagnosability. However, in the context of hybrid systems, although faults may not be always discriminable, there are generally operating modes of the system in which they are. Active diagnosis relies on applying specific inputs to the system so as to exhibit additional symptoms that help refining the diagnosis. The idea of this paper is to use hybrid systems diagnosability analysis to drive the system towards modes with increased diagnosability with respect to safety considerations. The active diagnosis problem is formulated as a conditional planning problem. From an ambiguous state returned by the diagnoser, the plan defines how to find a controllable paths leading to a non ambiguous state. The decision about the active diagnosis actions is guided by the observable response of the system. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/40077.html 04:00 PM Wednesday 31, 1969 This paper deals with design of active fault detection of non-linear stochastic systems. As general solution of the problem is extremely difficult, a special case of active detector design for a given set of controllers for jump Markov non-linear Gaussian models is considered. The optimal active detector for a given set of controllers is intractable and therefore, the rolling horizon technique will be used to reduce computational costs. The system is modelled using a multi-layer perceptron neural network where structure and unknown parameters are obtained by means of an off-line training process based on the extended Kalman filter estimation method and structure optimization using pruning of the insignificant connections. The proposed active detector is compared with a passive one based on open-loop feedback strategy and the performance is illustrated in an example by simulation and Monte Carlo analysis. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif http://www.ifac-papersonline.net/Detailed/40156.html 04:00 PM Wednesday 31, 1969 The focus of this paper is on stochastic change detection applied in connection with active fault diagnosis (AFD). An auxiliary input signal is applied in AFD. This signal injection in the system will in general allow to obtain a fast change detection/isolation by considering the output or an error output from the system. It will be shown how it is possible to apply both the gain as well as the phase change of the output signal in the CUSUM tests. The method is demonstrated in an example. http://www.ifac-papersonline.net/static/luna/images/ifac/icon-download.gif