The study of the subdivision driving technology of a stepper motor and two types of typical acceleration and deceleration curves aims at optimizing the open-loop control performance of the stepper motor. The simulation model of a two-phase hybrid stepper motor open-loop control system is set up based on the mathematical model of the stepper motor, in order to let the stepper motor have the smaller stepper angle, two types of typical acceleration and a deceleration curve algorithm are designed for the real- time online calculation based on the subdivision driving technology. It respectively carries out the simulation analysis for their control effects. The simulation results show that the parabolic acceleration and deceleration curves have a larger maximum in-step rotation angle and the faster dynamic response ability in the same control period, and at the same time, the position tracking error of an intermediate process is smaller.
The recently proposed q-rung orthopair fuzzy set (q-ROFS) characterized by a membership degree and a non-membership degree is powerful tool for handling uncertainty and vagueness. This paper proposes the concept of q-rung orthopair linguistic set (q-ROLS) by combining the linguistic term sets with q-ROFSs. Thereafter, we investigate multi-attribute group decision making (MAGDM) with q-rung orthopair linguistic information. To aggregate q-rung orthopair linguistic numbers ( q-ROLNs), we extend the Heronian mean (HM) to q-ROLSs and propose a family of q-rung orthopair linguistic Heronian mean operators, such as the q-rung orthopair linguistic Heronian mean (q-ROLHM) operator, the q-rung orthopair linguistic weighted Heronian mean (q-ROLWHM) operator, the q-rung orthopair linguistic geometric Heronian mean (q-ROLGHM) operator and the q-rung orthopair linguistic weighted geometric Heronian mean (q-ROLWGHM) operator. Some desirable properties and special cases of the proposed operators are discussed. Further, we develop a novel approach to MAGDM within q-rung orthopair linguistic context based on the proposed operators. A numerical instance is provided to demonstrate the effectiveness and superiorities of the proposed method.
The shipping noise near channels and ports is an important contribution to the ambient noise level, and the depth of these sites is often less than 100 m. However less attention has been paid to the measurement in shallow water environments (Brooker, Humphrey, 2016). This paper presents extensive measurements made on the URN (underwater radiated noise) of a small fishing boat in the South China Sea with 87 m depth. The URN data showed that the noise below 30 Hz was dominated by the background noise. The transmission loss (TL) was modelled with FEM (finite element method) and ray tracing according to the realistic environmental parameters in situ. The discrepancy between the modelled results and the results using simple law demonstrates both sea surface and bottom have significant effect on TL for the shallow water, especially at low frequencies. Inspired by the modelling methodology in AQUO (Achieve QUieter Oceans) project (Audoly et al., 2015), a predicted model applied to a typical fishing boat was built, which showed that the URN at frequencies below and above 100 Hz was dominated by non-cavitation propeller noise and mechanical noise, respectively. The agreement between predicted results and measured results also demonstrates that this modelling methodology is effective to some extent.