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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 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]

Passenger car equivalents for heavy vehicles are required to carry out capacity calculations and perform operational analysis of any road entity (roadway segments or intersections). At single-lane roundabouts, the constraints to the vehicular trajectories imposed by the curvilinear geometric design and the driver's gap acceptance behaviour are expected to produce an impact of the heavy vehicles on the quality of traffic flow different from that produced on freeways and two-lane highways or other at-grade intersections. This is also because entering flow is opposed by the circulating flow which has priority and travels in an anticlockwise direction on a single-lane path around the central island. This paper addresses the question of how to estimate the passenger car equivalents for heavy vehicles on single-lane roundabouts. First, a comparison was performed between the empirical capacity functions based on a meta-analytic estimation of the critical and the follow up headways and the simulation outputs manually obtained for a single-lane roundabout built in Aimsun microscopic simulator. A genetic algorithm-based calibration procedure, therefore, was used to reach a better convergence between the simulation outputs and the empirical capacities. Based on the calibrated model, the passenger car equivalents were determined by comparing the capacity functions built for a fleet of passenger cars with the capacity functions calculated for different percentages of heavy vehicles. Differently from HCM 2010 which assumes a heavy vehicle to be equivalent to two passenger cars and sets as 2.0 the passenger car equivalents for heavy vehicles for roundabouts, a higher PCE effect would be expected on the quality of traffic conditions when the traffic stream contains a high number of heavy vehicles; this effect should be accounted for when calculating capacity and level-of-services. [ABSTRACT FROM AUTHOR]

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]

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 performed on the corresponding real-valued model, as it allows the observability conditions to be directly obtained in terms of stator current and rotor flux complex-valued vectors. Necessary observability conditions are also obtained along with the well-known sufficient ones. It is also shown that the complex-valued implementation allows a reduction of 35% in the computation time w.r.t. the standard real-valued one, which is obtained thanks to the lower dimensions of the matrices of the ECKF w.r.t. the ones of the real-valued implementation and the fact that no matrix inversion is required. The effectiveness of the proposed ECKF is shown by means of simulation in Matlab/Simulink environment and through experiments on a real low-power drive. [Copyright &y& Elsevier]