The object of this paper is a permanent magnet synchronous linear motor (PMLSM), whose control method is based on a model-referenced adaptive system (MRAS), and it analyses the speed identification of a permanent magnet synchronous linear motor without position sensors. The article proposes a new model-referenced adaptive method, which utilises a sliding-mode variable structure control method (SMC), to replace the PI control algorithm utilised in conventional model-referenced adaptive algorithm. The control system of the PMLSM is therefore designed and studied based on the change of the adaptive law in model-referenced adaption. The mathematical model of the PMLSM itself is chosen as the reference model, and the feedback magnetic chain model of the motor output is chosen as the adjustable model, replacing the conventional current model and simplifying the control algorithm. The sliding mode surface of the sliding mode variable structure control algorithm is constructed using the reference model and the output error of the adjustable model. Through theoretical analysis and simulation models built by MATLAB/Simulink simulation software, the simulation results show that the designed PMLSM speed induction-free control system MRAS speed observer based on the sliding mode variable structure has strong robustness and excellent dynamic static performance. The advantages verified by the new algorithm achieve the experimental purpose of the expected assumptions.
In recent years, permanent magnet synchronous linear motor (PMSLM) has gained tremendous momentum in industry, especially in the high-precision field. This is mainly because it has the advantages of small size, high control precision, and reliable operation. However, due to the special structure of linear motor, the control strategy of rotating motor cannot be directly applied to PMSLM. Three control strategies for reducing loss and improving efficiency of PMSLM are proposed in this paper. Firstly, the mathematical model of PMSLM is established, and the loss model and efficiency equation are established. Secondly, we adopt the loss model control strategies of i d = 0, and maximum thrust current ratio and direct thrust are used to optimize the efficiency of the motor. Finally, simulation experiments are carried out for the three proposed optimization strategies, and the effects of initial speed and load on motor efficiency are analyzed. The effectiveness of the three loss model control strategies proposed in this paper is fully verified by the simulation results, and it is found that the loss model control strategy of i d = 0 has the most obvious efficiency improvement.
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