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In this article, a new scheme for range-based localization is proposed. The main goal is to estimate the position of a mobile point based on distance measurements from fixed devices, called anchors, and on inertial measurements. Due to the nonlinear nature of the problem, an analytic relation to compute the position starting from these measurements does not exist, and often trilateration methods are used, generally based on least-square algorithms. The proposed scheme is based on the modeling of the localization process as a parallel robot, thereby methodologies and control algorithms used in the robotic area can be exploited. In particular, a closed-loop control system is designed for tracking the position of a mobile point based on range measurements from fixed anchors, and it is shown a peculiar structure of the tracking error dynamics, whose allows an intuitive gain tuning and ensures global exponential stability. Moreover, it is also shown a nice connection between tuning parameters and rate of convergence of the estimation error. Experimental results confirm the validity of the proposed localization method. [ABSTRACT FROM AUTHOR]

This paper presents the analysis and design of a min-type strategy to control a synchronous boost converter in continuous conduction mode. The strategy uses a nonlinear switching surface to establish the change of topology in the converter and is analyzed by means of a sliding-mode control approach. Subsequently, the min-type strategy is modified by a hybrid control formulation, which introduces a hysteresis width and a dwell-time to obtain a finite switching frequency in the start-up and steady-state, respectively. The hybrid control formulation is implemented digitally by means of a microprocessor which processes the samples of inductor current and capacitor voltage to provide the control signal that activates the power switch. Experimental results in a prototype validate the proposed control strategy and show its potential in transient time and steady-state. [ABSTRACT FROM AUTHOR]

This paper deals with motion control systems with induction motor, subject to severe requirements on both dynamics and steady-state behavior. The proposed control methodology could be viewed as an advancement of the standard field oriented control. It consists of two control loops, i.e., the rotor flux and the speed control loops, designed using the active disturbance rejection control method, with the aim to cope with both exogenous and endogenous disturbances, which are estimated by means of two linear extended state observers and then compensated. Moreover, with the aim of achieving total robustness, a sliding-mode based component is designed, in order to take into account disturbance estimation errors and uncertainties in the knowledge of the control gains. The effectiveness of this approach is shown by means of numerical simulations, and experiments carried out on a suitably developed test set-up. Finally, experimental comparisons between the proposed robust active disturbance rejection control, and the basic active disturbance rejection control are given. [ABSTRACT FROM PUBLISHER]

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 FLC, the classic field-oriented control and a previously developed FLC, not accounting for the iron losses, have been shown in variable flux working conditions. [ABSTRACT FROM AUTHOR]

This article proposes a nonlinear controller based on feedback linearization (FL) for synchronous reluctance motor (SynRM) drives which takes into consideration the magnetic saturation. The proposed nonlinear FL control based control technique has been developed starting from the theoretical definition of an original dynamic model of the SynRM taking into consideration both the self- and the cross-saturation effects. Such a control technique permits the dynamics of both the speed and axis flux loops to be maintained constant independently from the load and the saturation of the iron core in both constant flux and variable direct axis flux operating conditions. Finally, sensitivity of the performance of the proposed FL control versus the variation of the main motor parameters has been verified. The proposed technique has been tested experimentally on a suitably developed test setup. The proposed FL control has been further compared with the classic field-oriented control (FOC) in both constant flux and variable flux working conditions. [ABSTRACT FROM AUTHOR]

This paper deals with robust estimation of rotor flux and speed for sensorless control of motion control systems with an induction motor. Instead of using sixth-order extended Kalman filters (EKFs), rotor flux is estimated by means of a fourth-order descriptor-type robust KF, which explicitly takes into account motor parameter uncertainties, whereas the speed is estimated using a recursive least squares algorithm starting from the knowledge of the rotor flux itself. It is shown that the descriptor-type structure allows for a direct translation of parameter uncertainties into variations of the coefficients appearing in the model, and this improves the degree of robustness of the estimates. Experimental findings, carried out on a closed-loop system consisting of a low-power induction-motor-load system, a proportional–integral-type controller, and the proposed estimator, are shown with the aim of verifying the goodness of the whole closed-loop control system. [ABSTRACT FROM PUBLISHER]

This is the first part of the article, divided into two parts, dealing with the definition of a space-vector dynamic model of the linear induction motor (LIM) taking into consideration both the dynamic end-effects and the iron losses and its offline identification. This first part specifically treats the theoretical formulation of this model, which has been expressed in a state form, so to be, in perspective, suitably adopted for developing novel nonlinear control techniques, nonlinear observers as well as electrical losses minimization techniques. Besides the formulation of the dynamic model in space-vector state form, a steady-state analysis is proposed, highlighting the combined effects of the dynamic end-effects and the iron losses on the main electrical quantities of the LIM. [ABSTRACT FROM AUTHOR]

This is the second part of an article, divided into two parts, dealing with the definition of a space-vector dynamic model of the linear induction motor (LIM) taking into consideration both the dynamic end-effects and the iron losses as well as the offline identification of its parameters. This second part is devoted to the description of an identification technique that has been suitably developed for the estimation of the electrical parameters of the LIM dynamic model accounting for both the dynamic end-effects and iron losses. Such an identification technique is strictly related to the state formulation of the proposed model and exploits genetic algorithms for minimizing a suitable cost function based on the processing of both the primary current and speed estimation errors. The proposed parameters’ estimation technique has been validated experimentally on a suitably developed test set-up. It has been further validated by a finite element analysis model of the LIM. [ABSTRACT FROM AUTHOR]

This paper deals with a robust input–output feedback linearization control technique for induction motors. Indeed, classic feedback linearization presents two main disadvantages: 1) the accuracy of the dynamic model; and 2) the corresponding correct knowledge of the model parameters. To address this issue, the linear controller has been substituted with a suitably controller designed to be robust to the variations of the main parameters of the induction motor, like stator and rotor resistances, and the three-phase magnetizing inductance. The proposed controller has been tested both in numerical simulation and experimentally on a suitably designed test setup. Moreover, it has been compared with the classical feedback linearization based on linear controllers, highlighting the improvements in terms of dynamic performance, when parameter variations occur. Results confirm a significant increase of the robustness of the controller against parameter variations. [ABSTRACT FROM AUTHOR]

This paper proposes a nonlinear observer for induction machine drives based on space-vector dynamic model of induction machine, expressed in state form, which presents the peculiarity of taking into consideration the magnetic saturation of the iron core. This observer is particularly suitable in order to obtain high accuracy in rotor flux estimation, in both amplitude and phase position, during working conditions characterized by varying flux, among which the most important are those during electrical losses minimization. A Lyapunov-based convergence analysis is proposed in order to suitably compute the numerical observer gain guaranteeing the convergence of the estimation error. The proposed nonlinear observer has been tested by means of simulations and experiments carried out on a suitably developed test setup. Its behavior has been compared with that obtained with a standard full-order Luenberger observer that assumes the linearity of the magnetization characteristic. The paper shows the capability of the proposed nonlinear observer to correctly estimate amplitude and phase of the rotor flux under flux varying conditions. Moreover, the proposed observer exhibits a higher accuracy than that obtained with the standard observer, which does not consider the estimated magnetization characteristic. [ABSTRACT FROM PUBLISHER]

This paper proposes the theoretical framework and the experimental application of the active disturbance rejection control to linear induction motors. Such a nonlinear control (ADRC) technique can be viewed as a particular kind of input–output linearization control, where the nonlinear transformation of the state is not computed by means of the model, but it is estimated online. Such an approach permits to cope with unmodeling dynamics, as well as uncertainty in the knowledge of the model parameters and exogenous disturbances. The effectiveness of the proposed ADRC control law has been verified both by numerical simulations and experimentally on a suitably developed test setup. Moreover, the results have been compared with those achievable with the model-based feedback linearization control. [ABSTRACT FROM AUTHOR]

This paper presents an input–output feedback linearization (FL) control technique for rotating induction motors, which takes into consideration the magnetic saturation of the iron core. Starting from a new formulation of the dynamic model taking into consideration the magnetic saturation expressed in a space-state form in the rotor-flux-oriented reference frame, the corresponding FL technique has been developed. To this aim, a particular care has been given to the choice of nonlinear functions interpolating the magnetic parameters versus the rotor magnetizing current and the corresponding magnetic characteristic. The proposed FL technique has been tested experimentally on a suitably developed test setup and compared, under the same bandwidths of the speed and flux closed loops, with both the FL technique not taking into consideration the magnetic saturation and with the industrial standard in terms of high performance control of the induction motor: field-oriented control. A further comparison with the unique example present in the scientific literature of the FL control technique including the magnetic saturation has been shown, highlighting consistent improvements achievable by the proposed FL in terms of reduced computational demand and better dynamic performance. [ABSTRACT FROM AUTHOR]

This paper proposes the theoretical framework and the consequent application of the input–output feedback linearization (FL) control technique to linear induction motors (LIMs). LIM, additionally to rotating induction motor, presents other strong nonlinearities caused by the dynamic end effects, leading to a space-vector dynamic model with time-varying inductance and resistance terms and a braking force term. This paper, starting from a recently developed dynamic model of the LIM taking into consideration its end effects, defines a FL technique suited for LIMs, since it inherently considers its dynamic end effects. Additionally, it proposes a technique for the on-line estimation of the inductor resistance, based on model reference adaptive system (MRAS) on-line estimator; it has been exploited for adapting on-line the FL control action versus inductor resistance variations leading to undesirable steady-state tracking errors. The stability of the proposed MRAS on-line estimator has been proven theoretically, adopting the Popov's criterion for hyperstability. The proposed approach has been validated experimentally on a suitably developed test setup, under both no load and loaded conditions. It has been compared firstly with the simplest control structure, which is the scalar $V/f$ control, secondly under the same closed-loop bandwidths of the flux and speed systems, with the industrial standard in terms of high-performance control technique, i.e., field-oriented control. [ABSTRACT FROM AUTHOR]

This paper deals with convergence analysis of the extended Kalman filters (EKFs) for sensorless motion control systems with induction motor (IM). An EKF is tuned according to a six-order discrete-time model of the IM, affected by system and measurement noises, obtained by applying a first-order Euler discretization to a six-order continuous-time model. Some properties of the discrete-time model have been explored. Among these properties, the observability property is relevant, which leads to conditions that can be directly linked with the working conditions of the machine. Starting from these properties, the convergence of the stochastic state estimation process, in mean square sense, has been shown. The convergence is also explored with reference to the difference between the samples of the state of the continuous-time model and that estimated by the EKF. The results theoretically achieved have been also validated by means of experimental tests carried out on an IM prototype. [ABSTRACT FROM PUBLISHER]

This paper proposes a speed observer for linear induction motors (LIMs), which is composed of two parts: 1) a linear Kalman filter (KF) for the online estimation of the inductor currents and induced part flux linkage components; and 2) a speed estimator based on the total least squares (TLS) EXIN neuron. The TLS estimator receives as inputs the state variables, estimated by the KF, and provides as output the LIM linear speed, which is fed back to the KF and the control system. The KF is based on the classic space-vector model of the rotating induction machine. The end effects of the LIMs have been considered an uncertainty treated by the KF. The TLS EXIN neuron has been used to compute, in recursive form, the machine linear speed online since it is the only neural network able to solve online, in a recursive form, a TLS problem. The proposed KF TLS speed estimator has been tested experimentally on a suitably developed test setup, and it has been compared with the classic extended KF. [ABSTRACT FROM AUTHOR]

This paper proposes a technique for the off-line estimation of the electrical parameters of the equivalent circuit of linear induction machines (LIM), taking into consideration the end effects, and focuses on the application of an algorithm based on the minimization of a suitable cost function involving the differences of measured and computed by simulation inductor current components. This method exploits an entire start-up transient of the LIM to estimate all the 4 electrical parameters of the machine (Rs, Ls, \sigma Ls, Tr). It proposes also a set of tests to be made to estimate the variation of the magnetic parameters of the LIM versus the magnetizing current as well as the magnetizing curve of the machine. Moreover, a methodology for the estimation of the mechanical parameters of the model is proposed as well. The proposed methodology has been verified experimentally on suitably developed test set-up. [ABSTRACT FROM PUBLISHER]