Sensor fault detection and isolation filter for polytopic LPV systems: a winding machine application
نویسندگان
چکیده
In this paper, a fault diagnosis method is developed for a particular class of nonlinear systems described by a polytopic Linear Parameter Varying (LPV) formulation. The main contribution consists in the synthesis of an accurate Fault Detection and Isolation (FDI) filter and also a sensor fault magnitude estimation with a quality factor. This quality factor of the filter underlines if the fault estimation can be used or not. Stability conditions of the polytopic LPV filter are studied by ensuring poly-quadratic stability with Linear Matrix Inequality (LMI) representation. The effectiveness of this global FDI scheme through LPV modelization, filter design and stability analysis, is illustrated on a real winding machine under multiple sensor faults.
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 کاملDesign of Sensor Fault Diagnosis Method for Nonlinear Systems described by Linear Polynomial Matrices Formulation: Application to a Winding Machine
In this paper, a sensor model-based fault diagnosis method for a particular class of nonlinear systems is developed. A polynomial matrices representation is considered for modeling the dynamic behavior of a class of nonlinear systems. According to nonlinear representation via a polytopic transformation, the nonlinear faulty system can be considered as a nonlinear system with the presence of add...
متن کاملStator Fault Detection in Induction Machines by Parameter Estimation Using Adaptive Kalman Filter
This paper presents a parametric low differential order model, suitable for mathematically analysis for Induction Machines with faulty stator. An adaptive Kalman filter is proposed for recursively estimating the states and parameters of continuous–time model with discrete measurements for fault detection ends. Typical motor faults as interturn short circuit and increased winding resistance ...
متن کاملRobust H∞ Sensor Fault Diagnosis with Neural Network
The paper deals with the problem of a robust fault diagnosis for Linear Parameter-Varying (LPV) systems with Recurrent NeuralNetwork (RNN). The preliminary part of the paper describes the derivation of a discrete-time polytopic LPV model with RNN. Subsequently, a robust fault detection, isolation and identification scheme is developed, which is based on the observer and H∞ framework for a class...
متن کاملFault detection for LPV systems: Loop shaping H– approach
This paper addresses a method for fault detection (FD) in linear parameters varying (LPV) systems by maximizing the fault to residual sensitivity. It uses the newly developed H− index properties and minimizing the well known H∞ norm for worst case uncertainties and disturbance attenuation. A loop shaping approach for the H− FD problem is proposed. The multi-objectives problem is formulated as L...
متن کامل