Abstract-Finite-state predictive torque control (FS-PTC) is computationally expensive, since it uses all voltage vectors available from a power converter for prediction and actuation. The computational burden is rapidly increased with the number of voltage vectors and objectives to be controlled. Moreover, designing a cost function with more than two control objectives is a complex task. This paper proposes a simplified algorithm based on a new direct torque control (DTC) switching table to reduce the numbers of voltage vectors to be predicted and objectives to be controlled. The new switching table also assists to reduce average switching frequency and its variation range. As a result, the cost function is simplified by not requiring to include the frequency term. Experimental results show that the average execution time and the average switching frequency for the proposed algorithm are greatly reduced without affecting the torque and flux performances achieved in the conventional FS-PTC.Index Terms-Predictive torque control, simplified algorithm, execution time, average switching frequency, Torque and flux ripple, induction motor (IM).

Abstract. The extent of internal energy deposition upon ion formation by low temperature plasma and atmospheric pressure chemical ionization was investigated using novel benzylammonium thermometer ions. C-N heterolytic bond dissociation enthalpies of nine 4-substituted benzylammoniums were calculated using CAM-B3LYP/6-311++G(d,p), which was significantly more accurate than B3LYP/6-311++G(d,p), MP2/ 6-311++G(d,p), and CBS-QB3 for calculating the enthalpies of 20 heterolytic dissociation reactions that were used to benchmark theory. All 4-substituted benzylammonium thermometer ions fragmented by a single pathway with comparable dissociation entropies, except 4-nitrobenzylammonium. Overall, the extent of energy deposition into ions formed by low temperature plasma was significantly lower than those formed by atmospheric pressure chemical ionization under these conditions. Because benzylamines are volatile, this new suite of thermometer ions should be useful for investigating the extent of internal energy deposition during ion formation for a wide range of ionization methods, including plasma, spray and laser desorption-based techniques.

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In silico modelling and analysis of small molecules substantially accelerates the process of drug development. Representing and understanding molecules is the fundamental step for various in silico molecular analysis tasks. Traditionally, these molecular analysis tasks have been investigated individually and separately. In this study, we presented X-MOL, which applies large-scale pre-training technology on 1.1 billion molecules for molecular understanding and representation, and then, carefully designed fine-tuning was performed to accommodate diverse downstream molecular analysis tasks, including molecular property prediction, chemical reaction analysis, drug-drug interaction prediction, de novo generation of molecules and molecule optimization. As a result, X-MOL was proven to achieve state-of-the-art results on all these molecular analysis tasks with good model interpretation ability. Collectively, taking advantage of super large-scale pre-training data and super-computing power, our study practically demonstrated the utility of the idea of “mass makes miracles” in molecular representation learning and downstream in silico molecular analysis, indicating the great potential of using large-scale unlabelled data with carefully designed pre-training and fine-tuning strategies to unify existing molecular analysis tasks and substantially enhance the performance of each task.

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Linear permanent magnet machines are often characterized by low inductance and short pole pitch which leads to a small operational range of load angles. The resultant control performance using conventional direct thrust force control techniques is poor with high force ripple. This research improves this aspect of direct thrust force control. A novel multiple-inputmultiple-output (MIMO) state space model, independent of the mover's speed, having stator flux and thrust force as states, is formulated for the linear PMSM. An optimal linear state feedback control scheme is then designed using the optimal linear quadratic regulator technique. Integral action is added to the designed control scheme by state augmentation to minimize the steady-state error and reduce the force ripple. Experimental results clearly prove that the proposed optimal control scheme results in a faster transient response of speed and force with improved steady-state regulation of force and flux when compared to the state of the art. Index Terms-Direct Thrust Force Control (DTFC), Linear Quadratic Regulator (LQR) and Linear Permanent MagnetMotor (Linear PMSM).

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