Observer-based Sensor Fault Detectability: About Robust Positive Invariance Approach and Residual Sensitivity ⋆

نویسندگان

  • Abid Rahman Kodakkadan
  • Masoud Pourasghar
  • Vicenç Puig
  • Sorin Olaru
  • Carlos Ocampo-Martinez
  • Vasso Reppa
چکیده

This paper considers detectability of deviation of sensors from their nominal behavior for a class of linear time-invariant discrete-time systems in the presence of bounded additive uncertainties. Detectable sensor faults using interval observers are analyzed considering two distinct approaches: invariant-sets and classical fault-sensitivity method. It can be inferred from this analysis that both approaches derive distinct formulations for minimum detectable fault magnitude, though qualitatively similar. The core difference lies in the method of construction of the invariant set offline in the former method and the reachable approximation of the convergence set using forward iterative techniques in the latter. This paper also contributes in giving a formulation for minimum fault magnitudes with invariant sets using an observer-based approach. Finally, an illustrative example is used to compare both approaches.

برای دانلود 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

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

Design of nonlinear parity approach to fault detection and identification based on Takagi-Sugeno fuzzy model and unknown input observer in nonlinear systems

In this study, a novel fault detection scheme is developed for a class of nonlinear system in the presence of sensor noise. A nonlinear Takagi-Sugeno fuzzy model is implemented to create multiple models. While the T-S fuzzy model is used for only the nonlinear distribution matrix of the fault and measurement signals, a larger category of nonlinear systems is considered. Next, a mapping to decou...

متن کامل

Robust Model- Based Fault Detection and Isolation for V47/660kW Wind Turbine

In this paper, in order to increase the efficiency, to reduce the cost and to prevent the failures of wind turbines, which lead to an extensive break down, a robust fault diagnosis system is proposed for V47/660kW wind turbine operated in Manjil wind farm, Gilan province, Iran. According to the acquired data from Iran wind turbine industry, common faults of the wind turbine such as sensor fault...

متن کامل

Sensor Fault Detection and Diagnosis of a Process Using Unknown Input Observer

AbstractIn this paper, a robust sensor fault detection and isolation (FDI) method based on the unknown input observer (UIO) approach is presented. The basic principle of unknown input observers is to decouple disturbances from the state estimation error. A single full-order observer is designed to detect sensor faults in the presence of unknown inputs (disturbances). By doing so, we generate a ...

متن کامل

Variable Speed Wind Turbine DFIG Back to Back Converters Open-Circuit Fault Diagnosis by Using of Combiniation Signal-Based and Model-Based Methodes

Condition monitoring (CM) and Fault Detection (FD) of wind turbine lead to increase in reliability and availability of turbine. IGBT open circuit of wind turbine converter will bring about depletion in output current of converter and as a result, reduction in production of wind turbine power. In this research, back to back converter IGBT open - gate fault for wind turbine based on DFIG is detec...

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

برای دانلود 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

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2017