Fault Diagnosis and Accommodation of Linear Stochastic Systems with Unknown Disturbances

نویسندگان

  • Jong-Hyo Lee
  • Joon Lyou
چکیده

An integrated robust fault diagnosis and fault accommodation strategy for a class of linear stochastic systems subjected to unknown disturbances is presented under the assumption that only a single fault may occur at a given time. The strategy is based on the fault isolation and estimation using a bank of robust two-stage Kalman filters and introduction of the additive compensation input for cancelling out the fault’s effect on the system. Each filter is set up such that the residual is decoupled from unknown disturbances and fault with the influence vector designed in the filter. Simulation results for the simplified longitudinal flight control system with parameter uncertainties, process and sensor noises demonstrate the effectiveness of the present approach.

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

Robust fuzzy observer-based fault detection for nonlinear systems with disturbances

With the increasing demand for higher performance, safety and reliability of dynamic systems, fault diagnosis has received more and more attention. The observer-based strategy is one of the active research fields, which is widely used to construct model-based fault detection systems for technical processes which can be well modelled as linear time invariant systems. Fault diagnosis for nonlinea...

متن کامل

Robust Filtering for State and Fault Estimation of Linear Stochastic Systems with Unknown Disturbances

This paper presents a new robust filter structure to solve the simultaneous state and fault estimation problem of linear stochastic discrete-time systems with unknown disturbances. The method is based on the assumption that the fault and the unknown disturbances affect both the system state and the output, and no prior knowledge about their dynamical evolution is available. By making use of an ...

متن کامل

An LPV Approach to Sensor Fault Diagnosis of Robotic Arm

One of the major challenges in robotic arms is to diagnosis sensor fault. To address this challenge, this paper presents an LPV approach. Initially, the dynamics of a two-link manipulator is modelled with a polytopic linear parameter varying structure and then by using a descriptor system approach and a robust design of a suitable unknown input observer by means of pole placement method along w...

متن کامل

Identification of Multiple Input-multiple Output Non-linear System Cement Rotary Kiln using Stochastic Gradient-based Rough-neural Network

Because of the existing interactions among the variables of a multiple input-multiple output (MIMO) nonlinear system, its identification is a difficult task, particularly in the presence of uncertainties. Cement rotary kiln (CRK) is a MIMO nonlinear system in the cement factory with a complicated mechanism and uncertain disturbances. The identification of CRK is very important for different pur...

متن کامل

Robust State and fault Estimation of Linear Discrete Time Systems with Unknown Disturbances

This paper presents a new robust fault and state estimation based on recursive least square filter for linear stochastic systems with unknown disturbances. The novel elements of the algorithm are : a simple, easily implementable, square root method which is shown to solve the numerical problems affecting the unknown input filter algorithm and related information filter and smoothing algorithms;...

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:

دوره   شماره 

صفحات  -

تاریخ انتشار 2003