Extended complex Kalman filter for sensorless control of an induction motor
Abstract This paper deals with the design of an extended complex Kalman filter (ECKF) for estimating the state of an induction motor (IM) model, and for sensorless control of systems employing this type of motor as an actuator. A complex-valued model is adopted that simultaneously allows a simpler observability analysis of the system and a more effective state estimation. The observability analysis of this model is first performed by assuming that a third order ECKF has to be designed, by neglecting the mechanical equation of the IM model, which is a valid hypothesis when the motor is operated at constant rotor speed. It is shown that this analysis is more effective and easier than the one …
Nonlinear Robust Control of a Quadratic Boost Converter in a Wide Operation Range, Based on Extended Linearization Method
This paper proposes a control system for a quadratic boost DC/DC converter in a wide range of operations, based on an inner loop with a sliding mode controller, for reaching a desired equilibrium state, and an outer loop with integral-type controller, for assuring robustness against load and input voltage variations and converter parameter uncertainties. The sliding mode controller is designed with the extended linearization method and assures local asymptotic stability, whereas the integral controller is designed using classical frequency methods, and assures input–output stability. It is shown that the proposed controller also deals with the sudden changes in the nominal operating conditi…
Localization in Structured Environments with UWB Devices without Acceleration Measurements, and Velocity Estimation Using a Kalman–Bucy Filter
In this work, a novel scheme for velocity and position estimation in a UWB range-based localization system is proposed. The suggested estimation strategy allows to overcome two main problems typically encountered in the localization systems. The first one is that it can be suitable for use in environments where the GPS signal is not present or where it might fail. The second one is that no accelerometer measurements are needed for the localization task. Moreover, to deal with the velocity estimation problem, a suitable Kalman–Bucy filter is designed and it is compared, experimentally, with a particle filter by showing the features of the two algorithms in order to be used in a localization …
Adaptive Feedback Linearization Control of SynRM Drives With On-Line Inductance Estimation
This article proposes an adaptive input-output Feedback Linearization Control ( FLC ) techniques for Synchronous Reluctance Motor ( SynRM ) drives, taking into consideration the iron losses. As a main original content, this work proposes a control law based on a new dynamic model of the SynRM including iron losses as well as the on-line estimation of the static inductances. The on-line estimation of the SynRM static inductances permits to inherently take into consideration the magnetic saturation phenomena occuring on both axes. As a major result, it permits a null stator current steady state tracking error even with a proportional derivative controller. The estimation law is obtained thank…
Input-Output Feedback Linearization Control of a Linear Induction Motor Taking Into Consideration Its Dynamic End-Effects and Iron Losses
This article proposes a new input-output feedback linearization control (FLC) technique of linear induction motors (LIMs), taking into consideration both the dynamic end-effects and the iron losses. Starting from a previously conceived dynamic model, including the dynamic end-effects and the iron losses, all the theoretical framework of the FLC has been developed. The proposed FLC improves a previous version of FLC in accounting also the iron losses, which in LIMs with fixed-secondary sheet play a pivotal role more than in rotating induction motors (RIMs). The proposed FLC has been experimentally tested on a suitably developed test setup, and experimental comparisons between the proposed FL…