The linear switched reluctance motors (LSRMs) have many benefits such as simple structure, low cost, comparatively high force-to-mass ratio, and no need for mechanical rotary to linear motion converters. However, application of these motors is limited because of their force ripple. In this study, the LSRM is used in vertical motion and a new control strategy is proposed for reducing the force ripple. This method is based on instantaneous control of motor position, speed, phase current, and force. In order to realise the good motion quality of elevator, this study applies a speed profile based on minimum jerk model. Also, a new force distribution function is proposed that can properly distribute the total force among the phases. Using this function, phase currents can properly track the corresponding command currents and then, decrease undesirable ripples of output force considerably. The control system was implemented on a double sided four phase LSRM. Its performance is demonstrated by means of modelling and experimental results in elevator application.

In 2014–2016, >1,000 wild goats and sheep in 4 northern and central provinces of Iran died from peste des petits ruminants virus (PPRV) infection. Partial nucleoprotein sequencing of PPRV from 3 animals showed a close relationship to lineage 4 strains from China. Control measures are needed to preserve vulnerable ruminant populations.

A new direct adaptive fuzzy speed control method for a linear switched reluctance motor with unknown control gain sign is presented. The proposed control system consists of two parts: a fuzzy system and an adaptive law. Fuzzy system approximates an unknown ideal control law with unknown adjustable parameters. After determination of the control law, an appropriate adaptation law is designed to update the adjustable parameters to achieve control objectives. The adaptation law is designed using the error between the unknown ideal control law and fuzzy control law. Unlike previous works, in this study, the unknown control gain sign is taken as an unknown constant parameter and is determined online by an appropriate adaptation law. Proposed control method along with a fuzzy sliding mode speed control and a proportional integral speed control strategies are experimentally studied and the performance index is used to evaluate each strategy. The robustness of the proposed method to the parameters and external load force change has been verified via simulation and experiments. The results indicate that the proposed control method has an acceptable performance.

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