27,933 research outputs found
A New Hybrid Approach for Fault Detection and Diagnosis
Fault detection and isolation based on hybrid approaches have been an active eld of research over the last few years. From a practical point of view, the development of generic and uni ed approaches for industrial supervision systems design is a key challenge. The main methodological contribution of the present work is to develop a hybrid approach properly tailored for such challenge. The proposed approach uses the Bond Graph formalism to systematically develop computational models and algorithms for robust fault detection and isolation. The resulting outcomes are extended to a proposed data-driven approach which consists of transforming historical process data into a meaningful alphabetical model incorporated within a Bayesian network. This new hybrid methodology bene ts from all the knowledge available on the system and provides a more comprehensive solution in order to increase the overall con dence in the diagnosis and the performances. The e ectiveness of the developed hybrid approach is validated by the well-known Tennessee Eastman Benchmark process
On design of quantized fault detection filters with randomly occurring nonlinearities and mixed time-delays
This paper is concerned with the fault detection problem for a class of discrete-time systems with randomly occurring nonlinearities, mixed stochastic time-delays as well as measurement quantizations. The nonlinearities are assumed to occur in a random way. The mixed time-delays comprise both the multiple discrete time-delays and the infinite distributed delays that occur in a random way as well. A sequence of stochastic variables is introduced to govern the random occurrences of the nonlinearities, discrete time-delays and distributed time-delays, where all the stochastic variables are mutually independent but obey the Bernoulli distribution. The main purpose of this paper is to design a fault detection filter such that, in the presence of measurement quantization, the overall fault detection dynamics is exponentially stable in the mean square and, at the same time, the error between the residual signal and the fault signal is made as small as possible. Sufficient conditions are first established via intensive stochastic analysis for the existence of the desired fault detection filters, and then the explicit expression of the desired filter gains is derived by means of the feasibility of certain matrix inequalities. Also, the optimal performance index for the addressed fault detection problem can be obtained by solving an auxiliary convex optimization problem. A practical example is provided to show the usefulness and effectiveness of the proposed design method
Robust Fault Detection of Switched Linear Systems with State Delays
This correspondence deals with the problem of robust fault detection for discrete-time switched systems with state delays under an arbitrary switching signal. The fault detection filter is used as the residual generator, in which the filter parameters are dependent on the system mode. Attention is focused on designing the robust fault detection filter such that, for unknown inputs, control inputs, and model uncertainties, the estimation error between the residuals and faults is minimized. The problem of robust fault detection is converted into an H infin-filtering problem. By a switched Lyapunov functional approach, a sufficient condition for the solvability of this problem is established in terms of linear matrix inequalities. A numerical example is provided to demonstrate the effectiveness of the proposed method
Active actuator fault-tolerant control of a wind turbine benchmark model
This paper describes the design of an active fault-tolerant control scheme that is applied to the actuator of a
wind turbine benchmark. The methodology is based on adaptive filters obtained via the nonlinear geometric
approach, which allows to obtain interesting decoupling property with respect to uncertainty affecting the
wind turbine system. The controller accommodation scheme exploits the on-line estimate of the actuator
fault signal generated by the adaptive filters. The nonlinearity of the wind turbine model is described by the
mapping to the power conversion ratio from tip-speed ratio and blade pitch angles. This mapping represents
the aerodynamic uncertainty, and usually is not known in analytical form, but in general represented by
approximated two-dimensional maps (i.e. look-up tables). Therefore, this paper suggests a scheme to
estimate this power conversion ratio in an analytical form by means of a two-dimensional polynomial, which
is subsequently used for designing the active fault-tolerant control scheme. The wind turbine power generating
unit of a grid is considered as a benchmark to show the design procedure, including the aspects of
the nonlinear disturbance decoupling method, as well as the viability of the proposed approach. Extensive
simulations of the benchmark process are practical tools for assessing experimentally the features of the
developed actuator fault-tolerant control scheme, in the presence of modelling and measurement errors.
Comparisons with different fault-tolerant schemes serve to highlight the advantages and drawbacks of the
proposed methodology
Integrated fault estimation and accommodation design for discrete-time Takagi-Sugeno fuzzy systems with actuator faults
This paper addresses the problem of integrated robust
fault estimation (FE) and accommodation for discrete-time
Takagi–Sugeno (T–S) fuzzy systems. First, a multiconstrained
reduced-order FE observer (RFEO) is proposed to achieve FE for
discrete-time T–S fuzzy models with actuator faults. Based on the
RFEO, a new fault estimator is constructed. Then, using the information
of online FE, a new approach for fault accommodation
based on fuzzy-dynamic output feedback is designed to compensate
for the effect of faults by stabilizing the closed-loop systems. Moreover,
the RFEO and the dynamic output feedback fault-tolerant
controller are designed separately, such that their design parameters
can be calculated readily. Simulation results are presented to
illustrate our contributions
Fuzzy-logic-based control, filtering, and fault detection for networked systems: A Survey
This paper is concerned with the overview of the recent progress in fuzzy-logic-based filtering, control, and fault detection problems. First, the network technologies are introduced, the networked control systems are categorized from the aspects of fieldbuses and industrial Ethernets, the necessity of utilizing the fuzzy logic is justified, and the network-induced phenomena are discussed. Then, the fuzzy logic control strategies are reviewed in great detail. Special attention is given to the thorough examination on the latest results for fuzzy PID control, fuzzy adaptive control, and fuzzy tracking control problems. Furthermore, recent advances
on the fuzzy-logic-based filtering and fault detection problems are reviewed. Finally, conclusions are given and some possible future research directions are pointed out, for example, topics on two-dimensional networked systems, wireless networked control systems, Quality-of-Service (QoS) of networked systems, and fuzzy access control in open networked systems.This work was supported in part by the National Natural Science Foundation of China under Grants 61329301,
61374039, 61473163, and 61374127, the Hujiang Foundation of China under Grants C14002 andD15009, the Engineering and Physical Sciences Research Council (EPSRC) of the UK, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany
A review of convex approaches for control, observation and safety of linear parameter varying and Takagi-Sugeno systems
This paper provides a review about the concept of convex systems based on Takagi-Sugeno, linear parameter varying (LPV) and quasi-LPV modeling. These paradigms are capable of hiding the nonlinearities by means of an equivalent description which uses a set of linear models interpolated by appropriately defined weighing functions. Convex systems have become very popular since they allow applying extended linear techniques based on linear matrix inequalities (LMIs) to complex nonlinear systems. This survey aims at providing the reader with a significant overview of the existing LMI-based techniques for convex systems in the fields of control, observation and safety. Firstly, a detailed review of stability, feedback, tracking and model predictive control (MPC) convex controllers is considered. Secondly, the problem of state estimation is addressed through the design of proportional, proportional-integral, unknown input and descriptor observers. Finally, safety of convex systems is discussed by describing popular techniques for fault diagnosis and fault tolerant control (FTC).Peer ReviewedPostprint (published version
Leak localization in water distribution networks using a mixed model-based/data-driven approach
“The final publication is available at Springer via http://dx.doi.org/10.1016/j.conengprac.2016.07.006”This paper proposes a new method for leak localization in water distribution networks (WDNs). In a first stage, residuals are obtained by comparing pressure measurements with the estimations provided by a WDN model. In a second stage, a classifier is applied to the residuals with the aim of determining the leak location. The classifier is trained with data generated by simulation of the WDN under different leak scenarios and uncertainty conditions. The proposed method is tested both by using synthetic and experimental data with real WDNs of different sizes. The comparison with the current existing approaches shows a performance improvement.Peer ReviewedPostprint (author's final draft
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