This document presents a method of on-line fault diagnosis for iron core of induction motor stator based on adaptive observer. Due to the equivalent resistance is directly affected by the stator core fault, while the iron loss is considered in the series iron loss model of the induction motor, so we can determine the core fault state by identifying equivalent iron consumption resistance. In thi...

This correspondence describes a method for nonlinear filtering based on an adaptive observer, which guarantees the local stability of the linearised error system. Filter gain selection is by use of a fake algebraic Riccati equation. The design procedure attempts to produce a stable filter at the expense of optimality. This contrasts with the extended Kalman filter (EKF) which attempts to preser...

In recent years a growing interest was observed in the problem of synchronizing chaotic systems [Afraimovich et al., 1987; Pecora & Carroll, 1990; Cuomo et al., 1993; Blekhman et al., 1995; Nijmeijer & Mareels, 1997; Pogromsky & Nijmeijer, 1999]. It was motivated not only by scientific interest in the problem, but also by practical applications in different fields [Blekhman, 1988; Lindsey, 1972...

This paper presents an approach for data-driven design of fault diagnosis system. The proposed fault diagnosis scheme consists of an adaptive residual generator and a bank of isolation observers, whose parameters are directly identified from the process data without identification of complete process model. To deal with normal variations in the process, the parameters of residual generator are ...

It is well known that universal approximators can be used for adaptive control and estimation. In this paper, the problem of adaptive state observation of a large class of nonlinear uncertain systems is considered and it is shown that splines have some special properties, which can lead to simplified observer structure. In particular, the observer filter has fixed dynamical order, independent o...

A novel adaptive observer is proposed to perform on-line estimation of both state and parameters of the electrical part of induction motors. The rotor mechanical speed and the stator currents/voltages are assumed to be measured. A particular non–minimal state representation of the machine electrical model is derived and exploited to build the adaptive observer, based on a series–parallel archit...

In this study, a new adaptive sliding-mode observer is proposed to estimate the rotor position and speed for sensorless control of permanent-magnet synchronous motor (PMSM) in an electric vehicle drive system. This observer can effectively reduce the estimation errors caused by the inherent chattering phenomenon for a conventional sliding-mode observer and the stator resistance uncertainty due ...

A hybrid indirect and direct adaptive fuzzy output tracking control schemes are developed for a class of nonlinear multiple-input–multiple-output (MIMO) systems. This hybrid control system consists of observer and other different control components. Using the state observer, it does not require the system states to be available for measurement. Assisted by observer-based state feedback control ...

This paper considers the cooperative output regulation problem for linear multi-agent systems with a directed communication graph, heterogeneous linear subsystems, and an exosystem whose output is available to only a subset of subsystems. Both the cases with nominal and uncertain linear subsystems are studied. For the case with nominal linear subsystems, a distributed adaptive observer-based co...

A genetic algorithm (GA) uses the principles of evolution, natural selection, and genetics to offer a method for parallel search of complex spaces. In this paper we show how to utilize GA’s to perform online adaptive state estimation for nonlinear systems. First, we show how to construct a genetic adaptive observer (GAO) where a GA evolves the gains in a state observer in real time so that the ...