Detection Filter Design Research Articles

Design of low-complexity Farrow structure-based reconfigurable filters for parallel spectrum hole detection

Reconfigurability with extremely low hardware complexity is the demanding requirement of today’s 5G world. The use of Farrow structure-based design of variable bandwidth (VBW) filters can effectively realize tunability in the filter structure with minimum hardware overhead. Low-complexity VBW filters play a vital role in applications such as spectrum hole detection, where reconfigurability is to be ensured with minimum delay, along with minimum power and area utilization. This paper proposes a novel reconfigurable filter structure based on Farrow filters and frequency translation, for effective detection of spectrum holes of any arbitrary bandwidth, available within the user-occupied and user-unoccupied frequency bands. The precise spectrum hole detection from the occupied spectral bands, with an added advantage of reduced hardware complexity, is an attractive feature of the proposed approach, that can effectively replace the existing filter bank-based detection methods.

Simple Adaptive Control Against Sensor Failures

In various fields, for practical plants, Simple Adaptive Control (SAC) has provided good control performances in spite of its simple structure. Although many theories and applications of the SAC have been explored, sensor failure issues have not been well considered. As a remedy, in the previous work, a fault-tolerant SAC system (SACS) is developed that can automatically replace failed sensors with healthy backups to maintain its performance. However, an additional condition is imposed on controlled plants, and a class of detectable failures is slightly limited. This problem comes from a design of detection filters introduced to the SACS. In this paper, to remove the above-mentioned restrictions, a new design method for a nonlinear detection filter is presented. This paper also shows a theoretical analysis on control performance and several simulation results to confirm the effectiveness.

Robust Fault Detection Filter Design of Networked Control Systems

A robust fault detection scheme is developed for networked control systems (NCSs) with limited quality of services (QoS), such as network-induced time delay, data dropout, and error sequence. An augmented Markov jump systems (MJSs) model is constructed, based on which a robust fault detection filter is designed. Such a design solved by using Ricatti inequality can guarantee that the error dynamic system is stochastic stable and the residual is sensitive to the fault. A numerical example and an aircraft application simulation study are provided to verify the effectiveness of the proposed method.

Switched <img width="58" height="55" src="http://article.sciencepublishinggroup.com/journal/248/2481135/image001.png" /> Detection Filter Design for Nonlinear Systems

This paper presents the application of the concept of detection filters to the detection of faults in nonlinear systems. The nonlinear dynamics in specific meaningful points of the operation is approximated by means of a matched array of linear systems. Then, linear filters are designed for each particular subsystem and a switching scheme is applied to carefully choose the most suitable filter regarding the operational characteristics of the plant in real time. Stability of the switching process is guaranteed by keeping the switching time between two consecutive switching large enough to ensure a proper falloff of filter transients. Therefore, apart from the solution of the standard linear-quadratic optimization problem represented by the detection filter design problem one has to derive sufficient conditions for the observation error dynamics to be globally asymptotically stable during switching. The goal is to find a common minimum of the switching time to each specific level calculated separately for every single filter that can be used as a restriction for the switching signal. The idea is demonstrated with the application to the detection of faults in the air path of a diesel engine. The results can be considered as the extension of the standard linear fault detection filtering problem to nonlinear systems.

Robust non-fragile [formula omitted] fault detection filter design for delayed singular Markovian jump systems with linear fractional parametric uncertainties

This paper investigates the problem of non-fragile H∞ fault detection filtering for a class of uncertain time-varying-delay singular Markovian jump systems (SMJSs). Linear fractional parameter uncertainties are considered and the designed filter is supposed to contain gain variations. The main objective is to design a mode-dependent non-fragile fault detection filter to guarantee the fault detection system to be stochastically admissible with an H∞ performance index for all admissible uncertainties. First, by constructing a novel mode-dependent stochastic Lyapunov–Krasovskii functional and employing integral inequality approach, sufficient delay-dependent conditions on stochastic admissibility and H∞ performance analysis for the fault detection system are presented in terms of linear matrix inequalities (LMIs). Then, the existence conditions of the desired fault detection filter and the explicit expressions for calculating the filter parameters are established. Finally, a numerical example and a DC motor are employed to show that our methods are effective.

Event-Triggered Fault Detection Filter Design for Nonlinear Networked Systems

This paper investigates the problem of event-triggered fault detection (FD) filter design for nonlinear networked systems in the framework of interval type-2 fuzzy systems. In the system model, the parameter uncertainty is captured effectively by the membership functions (MFs) with upper and lower bounds. For reducing the utilization of limited communication bandwidth, an event-triggered communication mechanism is applied. A novel FD filter subject to event-triggered communication mechanism, data quantization, and communication delay is designed to generate a residual signal and detect system faults, where the premise variables are different from those of the system model. Consequently, the augmented FD system is with imperfectly matched MFs, which hampers the stability analysis and FD. To relax the stability analysis and achieve a better FD performance, the information of MFs and slack matrices are utilized in the stability analysis. Finally, two examples are employed to demonstrate the effectiveness of the proposed scheme.

Full- and Reduced-Order Fault Detection Filter Design With Application in Flow Transmission Lines

The full- and reduced-order fault detection filter design is examined for fault diagnosis in linear time-invariant (LTI) systems in the presence of noise and disturbances. The fault detection filter design problem is formulated as an H∞ problem using a linear fractional transformation (LFT) framework and the solution is based on the bounded real lemma (BRL). Necessary and sufficient conditions for the existence of the fault detection filter are presented in the form of linear matrix inequalities (LMIs) resulting in a convex problem for the full-order filter design and a rank-constrained nonconvex problem for the reduced-order filter design. By minimizing the sensitivity of the filter residuals to noise and disturbances, the fault detection objective is fulfilled. A reference model can be incorporated in the design in order to shape the desired performance of the fault detection filter. The proposed fault detection and isolation (FDI) framework is applied to detect instrumentation and sensor faults in fluid transmission and pipeline systems. To this end, a lumped parameter framework for modeling infinite-dimensional fluid transient systems is utilized and a low-order model is obtained to pursue the instrumentation fault diagnosis objective. Full- and reduced-order filters are designed for sensor FDI. Simulations are conducted to assess the effectiveness of the proposed fault detection approach.

Event-triggered fault detection filter design for nonlinear networked systems via fuzzy Lyapunov functions

This paper investigates the problem of event-triggered fault detection filter design for nonlinear networked control systems with both sensor faults and process faults. First, Takagi–Sugeno (T–S) fuzzy model is utilized to represent the nonlinear systems with faults and disturbances. Second, a discrete event-triggered communication scheme is proposed to reduce the utilization of limited network bandwidth between filter and original system. At the same time, considering network-induced delays and event-triggered scheme, a novel T–S fuzzy fault detection filter is constructed to generate a residual signal, which has nonsynchronous premise variables with the original T–S fuzzy system. Then, the fuzzy Lyapunov functional based approach and the reciprocally convex approach are developed such that the obtained sufficient conditions ensure that the fuzzy fault detection system is asymptotically stable with H∞ performance and is less conservative. All the conditions are given in terms of linear matrix inequalities (LMIs), which can be solved by LMI tools in MATLAB environment. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed results.

Fault Detection for Linear Discrete Time-Varying Systems With Multiplicative Noise: The Finite-Horizon Case

This paper studies the problem of fault detection for linear discrete time-varying systems with multiplicative noise in finite-horizon, where our main object is to provide an optimal fault detection filter (FDF) design scheme such that stochastic sensitivity/robustness ratio for fault diagnosis is maximized in the sense of probability 1. An operator-aided optimization approach and a generalized FDF are proposed such that solutions to the filter design issues are derived in the operator forms. The relationships among the deduced solutions are explicitly revealed via the proposed operator-aided methodology. The parameter matrices of the filter are computed in an analytical way by solving some recursive matrix equations. It is shown that the addressed approaches establish an operator-based framework of optimal FDF design for some categories of linear discrete-time systems. An example is given to illustrate the efficacy of our algorithms.

H∞ fault detection filter design for discrete-time nonlinear Markovian jump systems with missing measurements

Fault detection filter (FDF) design problem for a class of discrete-time nonlinear Markovian jump systems subject to unreliable communication channel is addressed in this study. The considered system nonlinearity is assumed to satisfy global Lipschitz condition and the missing measurement phenomenon is modeled by Bernoulli binary distribution. By constructing an observer-based FDF as a residual generator, the fault detection issue is cast into a stochastic H∞ filtering framework. Sufficient existence conditions of the H∞-FDF are derived via matrix inequalities. Two cases for the Markovian parameters, one is completely known transition probabilities and the other is partially known transition probabilities, have been considered in the filter design procedure, respectively. Furthermore, parameter matrices of the FDF are obtained by solving a set of linear matrix inequalities. An illustrative example is addressed to show the efficacy of the proposed filter.

A Reduced-order Fault Detection Filter Design for Polytopic Uncertain Continuous-time Markovian Jump Systems with Time-varying Delays

In this article, the fault detection (FD) reduced-order filtering problem is investigated for a family of polytopic uncertain continuous-time Markovian jump linear systems (MJLSs) with time-varying delays. Under meeting the the premise of fault detection accuracy, the reduced order fault detection filters are desirable in applications where fast data processing and saving computing space are necessary. Then, by the aid of the Markovian Lyapunov-Krasovskii functional and convex polyhedron techniques, some novel time-varying delays and polytopic uncertain sufficient conditions are proposed to insure the existence of the FD reduced-order filter. Finally, a simulated continuous stirred tank reactor process example is provided to verify the feasibility of the proposed methodology.

Adaptive Event-Triggered Fault Detection for Fuzzy Stochastic Systems With Missing Measurements

This paper discusses adaptive event-triggered fault detection filter design for fuzzy stochastic models with missing measurements. First, a novel event-triggered strategy is introduced, while an adaptive law is provided to adjust communication threshold dynamically. Compared with traditional event-triggered methods with fixed threshold, the proposed strategy is more effective on saving network communication resources. Second, a Bernoulli stochastic process is proposed to describe the measurement missing phenomenon, which always appears in real network environment. Then, an integrated fault detection model for fuzzy stochastic systems is constructed by taking network-induced delays, adaptive event-triggered strategy and missing measurements into account. A new method is provided to achieve mean-square asymptotical stability of residual model with one desired fault detection objective. Finally, simulation cases are introduced to verify the validity of the designed strategy.

Design of robust nonfragile fault detection filter for uncertain dynamic systems with quantization

This paper investigates the fault detection problem for uncertain linear systems with respect to signal quantization. The measurement output transmitted via the digital communication link is considered to be quantized by a dynamic quantizer. Moreover, different from most of existing results on fault detection where the residual generator is assumed to be realized perfectly as the designed one, this study takes the inaccuracy and uncertainty on the implementation of residual generator into account. This paper pays much attention to designing a fault detection filter with quantization as the residual generator and formulates the design problem into the H∞ framework. The objective is to guarantee the asymptotical stability and prescribed performance of the residual system. The S-procedure and a two-step approach are adopted to handle the effects of quantization and uncertainties on residual system. Corresponding design conditions of a robust fault detection filter and a robust nonfragile ones are derived in the form of linear matrix inequalities. Finally, the efficiency of the theoretical results is illustrated by the numerical example.

Mixed H2/H∞ Fault Detection Filter for Markovian Jump Linear Systems

We tackle the mixed H2/H∞ fault detection filter problem for a Markov jump linear system (MJLS) in the discrete-time domain. We present three distinct formulations: the first one is to minimize an upper bound on the H2 subject to a given upper value on the H∞ norm; the second one is the opposite situation; that is, we minimize an upper bound on H∞, subject to a given restriction on the H2 norm; and the third one is the minimization of a weighted combination of the upper bound of both the H2 and H∞ norms. We present new conditions in the form of linear matrices inequalities (LMI) that provide the design of the fault detection filter. We also present results for the so-called mode-independent case and the design of robust H∞ filters in the sense that the system matrices are uncertain. In order to illustrate the feasibility of the proposed approaches, a numerical example is presented.

Finite-time robust fault detection filter design for interconnected systems concerning with packet dropouts and changing structures

ABSTRACT This paper studies the problem of finite-time robust fault detection filter design for interconnected systems with packet dropouts and changing structures. There are some packet dropouts occurring in the network before transmitting to the robust fault detection filter. Different from previous results, taking cases of randomly disconnected interconnections among these subsystems into account, a switched scheme is introduced to address the problem of failed interconnection. Meanwhile, an arbitrary switching signal is introduced to denote which one subsystem is activated at the instant of disconnection of interconnection. The filter is designed to guarantee the finite-time boundedness and the achievement of the performance to the fault detection system. Sufficient conditions on the existence of desired filter are presented in term of feasible linear matrix inequalities by using the switched Lyapunov functional approach based on stochastic functional. Two examples are finally given to show the effectiveness of our method.

An Approach to Fault Detection for Multirate Sampled-Data Systems With Frequency Specifications

This paper is concerned with the design of fault detection for sampled-data systems, which are based on multirate sampling, with frequency specifications. A general multirate system is considered in this paper, where not only the inputs and outputs but also their different channels have different sampling rates. The purpose of this paper is to make this residual system with multirate sampling satisfy a given disturbance attenuation level over a restricted frequency range. With the use of the lifting technique, this paper reformulates a single-rate linear time-invariant system, which is equivalent to the multirate time-varying system. For a given restricted frequency range, convex conditions are obtained in designing a required fault detection filter. Then, the restricted frequency ranges problem are also solved specifically via the generalized Kalman–Yakubovic–Popov lemma. Finally, this paper uses a continuous-stirred tank reactor system to illustrate the effectiveness and advantages of the fault detection filter design method.

Robust Fault Detection Filter Design for Nonlinear Networked Control Systems with Time-Varying Delays and Packet Dropout

This paper deals with the problem of detecting faults in nonlinear networked control systems. The considered system is the state space models of time-varying systems in which the upper and lower bounds of delay are known. Sector-bounded condition is exploited to overcome the nonlinear term. It is assumed that data packet dropouts occur during data transmission, which here is modeled as Bernoulli-distributed white sequences. For fault detection, an $$H_{-} /H_{\infty }$$ performance index is utilized to design an observer such that the residual signal is much sensitive to faults and less sensitive to disturbance. The Lyapunov–Krasovskii approach is exploited to ensure the stability of the designed observer. The obtained results for observer design are modeled as linear matrix inequalities. Finally, a numerical example and a practical example of engineering systems are adopted to illustrate the effectiveness of the proposed approach.

Simultaneous Disturbance Compensation and H1/H∞ Optimization In Fault Detection Of UAVs

Abstract This paper deals with the problem of robust fault detection (FD) for an unmanned aerial vehicle (UAV) flight control system (FCS). A nonlinear model to describe the UAV longitudinal motions is introduced, in which multiple sources of disturbances include wind effects, modeling errors and sensor noises are classified into groups. Then the FD problem is formulated as fault detection filter (FDF) design for a kind of nonlinear discrete time varying systems subject to multiple disturbances. In order to achieve robust FD performance against multiple disturbances, simultaneous disturbance compensation and H1/H∞ optimization are carried out in designing the FDF. The optimality of the proposed FDF is shown in detail. Finally, both simulations and real flight data are applied to validate the proposed method. An improvement of FD performance is achieved compared with the conventional H1/H∞-FDF.

Fault detection for T–S fuzzy systems with past output measurements

This paper is concerned with the fault detection (FD) filter design problem for the discrete-time nonlinear systems with past output measurements and sensor saturation. The considered discrete-time nonlinear systems are described by T–S fuzzy models. A decomposition method is used to deal with the characteristics of sensor saturation. A new FD filter with past output measurements is firstly proposed by using the Lyapunov functional method. Subsequently, the design conditions are given in terms of convex problems constrained by linear matrix inequalities (LMI). Moreover, it is shown that the FD filter with past output measurements can achieve better FD performances than the existing ones with current output measurements. Finally, some simulation results are given to illustrate the advantages of the proposed design method.

Design of robust fuzzy fault detection filter for polynomial fuzzy systems with new finite frequency specifications

This paper investigates the problem of fault detection filter design for discrete-time polynomial fuzzy systems with faults and unknown disturbances. The frequency ranges of the faults and the disturbances are assumed to be known beforehand and to reside in low, middle or high frequency ranges. Thus, the proposed filter is designed in the finite frequency range to overcome the conservatism generated by those designed in the full frequency domain. Being of polynomial fuzzy structure, the proposed filter combines the H−/H∞ performances in order to ensure the best robustness to the disturbance and the best sensitivity to the fault. Design conditions are derived in Sum Of Squares formulations that can be easily solved via available software tools. Two illustrative examples are introduced to demonstrate the effectiveness of the proposed method and a comparative study with LMI method is also provided.