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Phase currents corrupted by measurement disturbances mainly arising from sensor noise, PWM switching noise, DC-link ripple, and measurement offset, increase torque or force ripple, acoustic noise and EMI. This paper presents a novel current controller for a linear switched reluctance motor (Lobo et al., 2006) to suppress measurement disturbances without extra hardware. The controller is based on an extended state observer (ESO) and a nonlinear proportional controller (NLP). The proposed method does not require an accurate mathematical model of the system and lends itself for implementation with a low-cost DSP controller. The proposed ESO is exploited to estimate measurement disturbances on measured phase currents and the proposed NLP compensates for measurement disturbances estimated by the ESO. The performance of the proposed current control is validated through dynamic simulations and experiments on linear switched reluctance motor drive. Analytical and experimental results prove that measurement disturbances contained in phase currents are mitigated by the proposed control method. Moreover, the rejection of measurement disturbances results in a reduction of force ripple and acoustic noise. From this study, it is inferred that the proposed current control technique is a strong candidate to suppress measurement disturbances with the same promising results without extra hardware in other motor drives as well.

This paper presents the comparison of four linear switched reluctance machines (LSRMs) as possible candidates for application in vertical elevators. Linear induction and linear synchronous machines have been presented and experimentally tested in vertical elevators. In this paper, four longitudinal LSRM configurations are presented and designed to operate as propulsion actuators in a vertical elevator prototype. Two of the four configurations have been presented earlier in horizontal propulsion experiments, and a third one has been proposed for application in vertical elevators. All four LSRMs are designed for similar static force profiles to allow for their comparison. The designed LSRM configurations are compared by using finite-element analysis and dynamic control simulations. The stator, translator, and copper winding weight and dimensions, footprint area, active material weight, normal forces and payload capabilities for all four configurations are contrasted. The configuration with the highest payload capability is chosen for implementation in an experimental prototype. The prototype vertical elevator is 1.27 m tall with a 1-ft-tall elevator vehicle with no counterweights and uses two LSRM setups on each side. The experimental correlation of propulsion force and inductance is presented to validate the theoretical design method used in this research.

From the perspective of control of switched reluctance motor (SRM) drives, current control is typically used as an inner loop control method. In this paper, observer and artificial neural network (ANN)-based novel flux linkage control of SRM drives is presented and examined as an alternate approach to current control. The main advantage of flux linkage control is computational simplicity due to the insensitivity of controller gains to machine operation conditions, while current control depends on controller gains which are very sensitive to self-inductance of SRMs. Flux linkage control needs a reliable flux linkage estimator for desirable control of SRMs. Integration method to estimate flux linkage from measured phase voltages, currents and resistances is commonly used, but it is sensitive to measurement error and white noise. Another way to measure the flux linkage is to use a look-up table which is very sensitive to input currents because it is current- and position-based data. In this paper, a simple observer-based voltage and ANN-based current correction method is proposed to overcome the measurement error. Furthermore, ANNs with two layers and five neurons are applied to produce an acceptable flux linkage estimate at each corrected current and measured position, instead of a look-up table. Finally, simulation results are presented to validate its performance.

Linear switched reluctance motors (LSRMs) for the primary propulsion of a ship elevator is proposed and investigated for the first time in this paper. To achieve the stated objective, a new type of LSRM is proposed with twin stators and a translator between them with no back iron in the translator. The proposed configuration of the LSRM is designed, simulated, analyzed, compared with traditional LSRMs, and verified by experimental measurements. The number of LSRM propulsion subsystems required is studied with a view to minimize their weights and an optimization study for that purpose is developed. Unique placement of the LSRM propulsion systems on the elevator is presented. The propulsion force is generated using one phase or multiphase excitation. To reduce propulsion force pulsations, a major requirement in elevators, controlled multiphase excitation using one of the known force distribution functions (FDF) is an acceptable solution. In this paper, it is proved that the currently available FDFs are able to reduce the force pulsations but are not able to meet the peak force command for the system. Consequently, the velocity and position control do not meet even the elementary performance requirements any more. A new FDF is proposed in this paper and presented to overcome the problem caused by a conventional FDF. The control system with the proposed FDF is derived and integrated into velocity and position controllers. Extensive dynamic simulation and experimental verification of the proposed LSRM with the novel FDF is proved to give superior performance in this paper. Such high performance capable of meeting vertical elevator applications is demonstrated.