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Journal ArticleDOI

Fault Detection and Isolation for Affine Fuzzy Systems With Sensor Faults

01 Oct 2016-IEEE Transactions on Fuzzy Systems (IEEE)-Vol. 24, Iss: 5, pp 1058-1071
TL;DR: This paper investigates the fault detection and isolation (FDI) problem for a class of nonlinear systems with sensor outage faults and proposes a multiple-model scheme based on the affine fuzzy model that describes the system in the presence of a specified fault.
Abstract: This paper investigates the fault detection and isolation (FDI) problem for a class of nonlinear systems with sensor outage faults. The considered nonlinear systems are described as affine fuzzy models, and the system outputs are chosen as the premise variables of fuzzy models. Different from the existing results, the influence of sensor faults on premise variables is considered. As a result, the well-known parallel distributed compensation scheme cannot be used for FDI filters design. By using the structural information encoded in the fuzzy rules, the affine fuzzy system is represented by multiple operating-regime-based models in fault-free case and faulty cases. In the multiple-model scheme, a bank of piecewise FDI filters are constructed, each of them is based on the affine fuzzy model that describes the system in the presence of a specified fault. The fault-dependent residual signals generated from the filters are used for detecting and isolating the specified fault. The FDI filter design conditions are obtained in the formulation of linear matrix inequalities. Finally, a numerical example is given to illustrate the effectiveness and merits of the proposed method.
Citations
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Journal ArticleDOI
TL;DR: A new fault isolation scheme for T–S fuzzy systems with sensor faults is proposed, which consists of a set of fuzzy observers that corresponds to a specified sensor, where the antecedent and consequent parts of the observer are independent on the sensor output.
Abstract: This paper is concerned with the fault isolation problem for T–S fuzzy systems with sensor faults. With the help of a set theoretic description of T–S fuzzy models, a new fault isolation scheme is proposed. It consists of a set of fuzzy observers and each of them corresponds to a specified sensor, where the antecedent and consequent parts of the observer are independent on the sensor output. Different from the existing approaches, the premise variables, which do not depend on the specified sensor output but depend on the other sensor outputs, are used in the proposed observer, which has the potential to lead to a better fault isolation performance. In the end, an example is given to show the effectiveness of the fault isolation method.

95 citations


Cites background from "Fault Detection and Isolation for A..."

  • ...[22] studied the FDI problem for affine T–S systems with sensor faults....

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Journal ArticleDOI
TL;DR: This paper investigates the event-triggered predictive control problem for networked nonlinear systems with imperfect premise matching and uses a common Lyapunov theory to ensure the asymptotical stability of the studied system and find the controller gains.
Abstract: This paper investigates the event-triggered predictive control problem for networked nonlinear systems with imperfect premise matching First, a model of networked nonlinear system is well constructed, which has integrated the event-triggered communication scheme (ETCS) and the predictive control together, in which, an ETCS is introduced to alleviate the communication burden by reducing the number of transmitted packets; and a fuzzy predictive controller is designed to predict future states and control signals between two successfully transmitted instants Therefore, the data dropout induced by the networks can be actively compensated Second, by using a common Lyapunov theory, a stability criterion and two stabilization criteria are deduced to ensure the asymptotical stability of the studied system and find the controller gains, respectively Different from the traditional parallel distributed compensation method, the synchronous premise variables between the T–S fuzzy system and the fuzzy event-triggered predictive controller (FETPC) are no longer needed again Since the imperfect premise matching condition is well considered in the derivation of the main results, the design flexibility and low cost of the FETPC implementation can be expected Finally, the validity of the method proposed in this paper is demonstrated by a nonlinear mass-spring example

92 citations


Additional excerpts

  • ...presented novel fault detection and isolation method and fault-tolerant tracking control method for nonlinear systems [11], [12] with point-to-point connection....

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Journal ArticleDOI
TL;DR: Two subsequent optimization problems are investigated, one is to seek the minimal ellipsoidal region for the best estimation performance, and the other is to minimize the triggering-annulus so as to reduce the triggering frequency with guaranteed estimation performance.

44 citations

Journal ArticleDOI
TL;DR: It is shown that the proposed event-driven FD technique is effective to optimize performance compared with the existing FD strategy and two examples are presented to verify the advantages of the novel design technique.
Abstract: This article considers the event-driven fault detection (FD) problem for discrete-time interval type-2 (IT2) fuzzy networked control systems (NCSs) with nonlinear perturbations. To reduce signal transmission, an event-driven mechanism in the NCSs is introduced. A novel FD fuzzy filter is designed for generating a residual signal and detecting actuator faults by considering the event-driven strategy, nonlinear perturbations, communication delay, and mismatched membership functions. It is shown that the proposed event-driven FD technique is effective to optimize performance compared with the existing FD strategy. Finally, two examples are presented to verify the advantages of the novel design technique.

39 citations

Journal ArticleDOI
TL;DR: It is shown that, for the considered discrete-time T–S fuzzy systems, using the nonsegmentation method, the results obtained by using the delay segmentation approach can be reduced to the existing results.
Abstract: This paper is concerned with the problem of ${H_{\infty }}$ filter design for discrete-time Takagi–Sugeno (T–S) fuzzy systems under an event-triggered (ET) communication mechanism. A partition method is adopted to overcome the asynchronous problem of the premise variables caused by introducing ET mechanism. The delay segmentation approach is used to deal with the network delay caused by network transmission, and new sufficient conditions are constructed to optimize the upper bound of network delay by combining each segments of the delay with the piecewise Lyapunov–Krasovskii functional. Moreover, it is shown that, for the considered discrete-time T–S fuzzy systems, using the nonsegmentation method, the results obtained by using the delay segmentation approach can be reduced to the existing results. Finally, an illustrative example is provided to show the advantages of the proposed design method.

36 citations

References
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Journal ArticleDOI
01 Jan 1985
TL;DR: A mathematical tool to build a fuzzy model of a system where fuzzy implications and reasoning are used is presented and two applications of the method to industrial processes are discussed: a water cleaning process and a converter in a steel-making process.
Abstract: A mathematical tool to build a fuzzy model of a system where fuzzy implications and reasoning are used is presented. The premise of an implication is the description of fuzzy subspace of inputs and its consequence is a linear input-output relation. The method of identification of a system using its input-output data is then shown. Two applications of the method to industrial processes are also discussed: a water cleaning process and a converter in a steel-making process.

18,803 citations

Book
02 May 2008
TL;DR: Fuzzy Control Systems Design and Analysis offers an advanced treatment of fuzzy control that makes a useful reference for researchers and a reliable text for advanced graduate students in the field.
Abstract: From the Publisher: A comprehensive treatment of model-based fuzzy control systems This volume offers full coverage of the systematic framework for the stability and design of nonlinear fuzzy control systems. Building on the Takagi-Sugeno fuzzy model, authors Tanaka and Wang address a number of important issues in fuzzy control systems, including stability analysis, systematic design procedures, incorporation of performance specifications, numerical implementations, and practical applications. Issues that have not been fully treated in existing texts, such as stability analysis, systematic design, and performance analysis, are crucial to the validity and applicability of fuzzy control methodology. Fuzzy Control Systems Design and Analysis addresses these issues in the framework of parallel distributed compensation, a controller structure devised in accordance with the fuzzy model. This balanced treatment features an overview of fuzzy control, modeling, and stability analysis, as well as a section on the use of linear matrix inequalities (LMI) as an approach to fuzzy design and control. It also covers advanced topics in model-based fuzzy control systems, including modeling and control of chaotic systems. Later sections offer practical examples in the form of detailed theoretical and experimental studies of fuzzy control in robotic systems and a discussion of future directions in the field. Fuzzy Control Systems Design and Analysis offers an advanced treatment of fuzzy control that makes a useful reference for researchers and a reliable text for advanced graduate students in the field.

3,183 citations


"Fault Detection and Isolation for A..." refers background in this paper

  • ...In the past studies of nonlinear systems, Takagi–Sugeno (T– S) fuzzy models [9], which are represented by some locally linear time-invariant systems in the form of IF–THEN rules, have been proved to be a well universal approximator to nonlinear behaviors [10]....

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Journal ArticleDOI
TL;DR: The approach exploits the gain-scheduling nature of fuzzy systems and results in stability conditions that can be verified via convex optimization over linear matrix inequalities, and special attention is given to the computational aspects of the approach.
Abstract: Presents an approach to stability analysis of fuzzy systems. The analysis is based on Lyapunov functions that are continuous and piecewise quadratic. The approach exploits the gain-scheduling nature of fuzzy systems and results in stability conditions that can be verified via convex optimization over linear matrix inequalities. Examples demonstrate the many improvements over analysis based on a single quadratic Lyapunov function. Special attention is given to the computational aspects of the approach and several methods to improve the computational efficiency are described.

775 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present new synthesis procedures for discrete-time linear systems based on a recently developed stability condition which contains as particular cases both the celebrated Lyapunov theorem for precisely known systems and the quadratic stability condition for systems with uncertain parameters.
Abstract: This paper presents new synthesis procedures for discrete-time linear systems. It is based on a recently developed stability condition which contains as particular cases both the celebrated Lyapunov theorem for precisely known systems and the quadratic stability condition for systems with uncertain parameters. These new synthesis conditions have some nice properties: (a) they can be expressed in terms of LMI (linear matrix inequalities) and (b) the optimization variables associated with the controller parameters are independent of the symmetric matrix that defines a quadratic Lyapunov function used to test stability. This second feature is important for several reasons. First, structural constraints, as those appearing in the decentralized and static output-feedback control design, can be addressed less conservatively. Second, parameter dependent Lyapunov function can be considered with a very positive impact on the design of robust H 2 and H X control problems. Third, the design of controller with mixed ...

675 citations

Journal ArticleDOI
TL;DR: The result provides a set of progressively less conservative sufficient conditions for proving positivity of fuzzy summations of Polya's theorems on positive forms on the standard simplex.

582 citations