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Finite Control Set Model Predictive Control (FCS-MPC) has the ability to achieve multi-objective optimization, but there are still many challenges. The key to realizing multi-objective optimization in FCS-MPC lies in the design of the cost function. However, the different dimensions of penalty terms in the cost function often lead to difficulties in designing weighting coefficients. Incorrect weighting coefficients may result in truncation errors in calculations of DSPs and FPGAs, thereby affecting the algorithm's control performance. Therefore, this article focuses on a system driving an induction motor with a three-level Neutral Point Clamped (NPC) inverter, and selects stator current and switching frequency as penalty terms in the cost function. An improved method is proposed to unify the dimensions of both penalty terms in the cost function. By unifying the dimensions of the penalty terms, a simple design of weighting coefficients can be achieved. Subsequently, to balance the inverter's switching frequency and the dynamic response performance of the motor, a composite cost function is further proposed. Finally, the rationality of the proposed method is validated through simulation and experimental platforms. [ABSTRACT FROM AUTHOR]

In order to accurately characterize and evaluate dust particle diffusion in the dynamic tunneling process of a boring machine, this study considers the 31,116 main transport chute heaving face of the Lijiahao coal mine as a case study. A dynamic tunneling model is developed considering the real dynamic tunneling state of the header, to carry out an in-depth analysis of the spatial and temporal evolution of wind flow and dust dispersion in the tunnel under dynamic excavation. In addition, the results were compared against the calculations of a static standard excavation model of a conventional header. Employing CFD analysis accompanied by field measurements, it was highlighted that the dynamic tunneling of the header leads to an increase in the pressure difference and the turbulent kinetic energy at the working face. Moreover, an increase in the number of vortices was reported, and a higher concentration of dust spreads more quickly along the return wind side wall to the return flow area. On the other hand, the high concentration of dust under the standard tunneling model was found to accumulate a lot on the return wind side. Simultaneously, as the distance between the pressurized air outlet and the working face increases, the average wind speed in the vortex-type wind flow area at the front of the tunnel decreases. When t = 60 s, the return flow area expands to a space of 8 m~24 m from the head, and the dust accumulated above the header spreads to the back of the header to form a high concentration dust region of more than 500 mg/m³. It was shown that the range of high-concentration dust clouds in the breathing zone decreases compared to the results of the standard tunneling model. Moreover, the dust concentration in the breathing zone of the driver is significantly lower than that reported by the standard tunneling model. Based on the results of the field test, the average error between the simulated and measured data of the dynamic tunneling model was calculated to be around 6.46%, thus demonstrating the model's capability in describing the real working conditions of the heave tunnel. [ABSTRACT FROM AUTHOR]