Search

This paper presents a model predictive thrust force control (MPTFC) method for a multiple-modular permanent magnet synchronous linear motor (PMSLM). It focuses on the thrust assignment and thrust ripple of the motor drive system with a multiple-branch inverter. A discrete time model of the PMSLM is established, and the driving system structure and operation principle of the motor are studied. A multi-mode cost function is designed according to the requirements of the different load conditions, and the optimal voltage vector action time is determined. The operation mode is analyzed to determine the distribution factor, so as to reduce the thrust pulsation during operation and improve the performance of the drive system. The results indicate that the proposed MPTFC method is effective in different operating modes, and the drive system has high efficiency and safer performance compared to a conventional drive system. [ABSTRACT FROM AUTHOR]

This paper presents a model predictive thrust force control (MPTFC) method for a multiple-modular permanent magnet synchronous linear motor (PMSLM). It focuses on the thrust assignment and thrust ripple of the motor drive system with a multiple-branch inverter. A discrete time model of the PMSLM is established, and the driving system structure and operation principle of the motor are studied. A multi-mode cost function is designed according to the requirements of the different load conditions, and the optimal voltage vector action time is determined. The operation mode is analyzed to determine the distribution factor, so as to reduce the thrust pulsation during operation and improve the performance of the drive system. The results indicate that the proposed MPTFC method is effective in different operating modes, and the drive system has high efficiency and safer performance compared to a conventional drive system.

The model predictive thrust control (MPTC) is emerging as a promising control technique for the linear induction machine (LIM) drive applications. However, the weighting factor is designed based on empirical procedures that are tedious and time consuming. In this work, a novel fuzzy weighting factor optimization method for LIM is developed to identify the suitable control action. Different from conventional fuzzy methods, the tuning process of weighting factors is regarded as a fuzzy chance constraint so as to constitute a new optimal problem without weighting factors. Hence, the optimal model can be solved by probability optimization algorithm and the corresponding equivalence class is also conducted. At last, simulation results are presented to validate the feasibility and effectiveness of this method. [ABSTRACT FROM AUTHOR]

In this paper, the model predictive thrust control (MPTC) method is applied in combination with the arbitrary two voltage vectors modulation strategy so as to acquire the more accurate modulation. Because of the huge number of possible voltage vector pairs that need to be evaluated, it may consume high calculation cost to find the best pair of voltage vectors (BPVV). So, one simplified method is proposed to avoid the tedious process of enumerating and comparing all possible cases, which can find directly the BPVV from large number of possible voltage vector pairs. Besides, the current limit is introduced into MPTC to avoid the overcurrent in dynamic transients, and the proposed search method is also effective to the case with current limit. This method has been numerically simulated and experimentally tested on a platform consisting of two coupled 3kW arc induction motors. Both simulation and experimental results show that the MPTC performance is improved by using the modulation of BPVV under different conditions, and its complexity is reduced obviously. [ABSTRACT FROM AUTHOR]

Compared with various commonly used control algorithms for linear induction machine, the model predictive thrust control can achieve multiple optimum control objectives, such as high dynamic performance, low power loss, and low flux and thrust ripples, but it is difficult to find suitable weighting factors to balance them. The most commonly used method to tune the weighting factors is by enumerating numerous cases, and then evaluating and comparing each case until the best set of weighting factors is achieved, which can be a very long and tedious procedure. This paper proposes two different methods to solve this problem for minimizing the flux and thrust ripples. One method is to use the variable weighting factor related to flux ripple so that the flux ripple can be seen as a hard constraint without complex tuning process. The other is to replace the flux control term by a variable defined with the same unit as the thrust so that the weighting factor can be equal to one without tuning. These two proposed methods have been successfully applied to a test platform consisting of two 3-kW arc induction motors. The experimental results have shown smaller flux and thrust ripples, as well as tracking errors in comparison with two existing common methods, i.e., the fuzzy decision based method and model predictive flux control. [ABSTRACT FROM AUTHOR]