Robust fault detection of non-linear systems using set-membership state estimation based on constraint satisfaction

نویسندگان

  • Sebastian Tornil-Sin
  • Carlos Ocampo-Martinez
  • Vicenç Puig
  • Teresa Escobet
چکیده

In this paper, the robust fault detection problem for non-linear systems considering both bounded parametric modelling errors and measurement noises is addressed. The non-linear system is monitored by using a state estimator with bounded modelling uncertainty and bounded process and measurement noises. Additionally, time-variant and time-invariant system models are taken into account. Fault detection is formulated as a set-membership state estimation problem, which is implemented by means of constraint satisfaction techniques. Two solutions are presented: the first one solves the general case while the second solves the time-variant case, being this latter a relaxed solution of the first one. The performance of the time-variant approach is tested in two applications: the well-known quadruple-tank benchmark and the dynamic model of a representative portion of the Barcelona’s sewer network. In both applications, different scenarios are presented: a faultless situation and some faulty situations. All considered scenarios are intended to show the effectiveness of the presented approach. & 2011 Elsevier Ltd. All rights reserved.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Actuator fault diagnosis for flat systems: A constraint satisfaction approach

This paper describes a robust set-membership-based Fault Detection and Isolation (FDI) technique for a particular class of nonlinear systems, the so-called flat systems. The proposed strategy consists in checking if the expected input value belongs to an estimated feasible set computed using the system model and the derivatives of the measured output vector. The output derivatives are computed ...

متن کامل

A Robust Adaptive Observer-Based Time Varying Fault Estimation

This paper presents a new observer design methodology for a time varying actuator fault estimation. A new linear matrix inequality (LMI) design algorithm is developed to tackle the limitations (e.g. equality constraint and robustness problems) of the well known so called fast adaptive fault estimation observer (FAFE). The FAFE is capable of estimating a wide range of time-varying actuator fault...

متن کامل

A GMDH neural network-based approach to passive robust fault detection using a constraint satisfaction backward test

This paper proposes a new passive robust fault detection scheme using non-linear models that include parameter uncertainty. The nonlinear model considered here is described by a group method of data handling (GMDH) neural network. The problem of passive robust fault detection using models including parameter uncertainty has been mainly addressed by checking if the measured behaviour is inside t...

متن کامل

A Gmdh Neural Network Based Approach to Passive Robust Fault Detection Using a Constraints Satisfaction Backward Test

This paper focus on the problem of passive robust fault detection using nonlinear models that include parameter uncertainty. The non-linear model considered here is described by a Group Method of Data Handling Neural Network (GMDHNN). The problem of passive robust fault detection using models including parameter uncertainty has been mainly addressed checking if the measured behaviour is inside ...

متن کامل

Robust Identification of Smart Foam Using Set Mem-bership Estimation in A Model Error Modeling Frame-work

The aim of this paper is robust identification of smart foam, as an electroacoustic transducer, considering unmodeled dynamics due to nonlinearities in behaviour at low frequencies and measurement noise at high frequencies as existent uncertainties. Set membership estimation combined with model error modelling technique is used where the approach is based on worst case scenario with unknown but...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Eng. Appl. of AI

دوره 25  شماره 

صفحات  -

تاریخ انتشار 2012