Artificial Neural Networks based SPWM technique for speed control of Permanent Magnet Synchronous Motor

• Main Authors: Tummala, Suresh Kumar, G, Dhasharatha
• Format: Conference Proceeding
• Language: English
• Subjects: Actuators; Artificial neural networks; Closed loops; Learning theory; Neural networks; Permanent magnets; Speed control; Synchronous motors; Torque
• ISSN: 2267-1242; 2555-0403; 2267-1242
• DOI: 10.1051/e3sconf/20198701030

The advancement of industry apparatuses for some methods with specific tasks to control the working of a few actuators on the field. Among these actuators, Permanent magnet synchronous motor drives are a mainly all-inclusive machine. Proficient utilization of hesitance torque, generally effectiveness, minor misfortunes and smaller size of the motor are the principle attractions of PMSM when contrasted and different drivers. Precise and rapid torque reaction is one of the parameters to determine differentiating arrangements in the ongoing past. The field-situated power perceived the likely and vigorous answer to accomplish these prerequisites to empower the figuring of streams and voltages in different parts of the inverter and motor under transient and consistent conditions. The primary objective of this paper is to investigate Artificial Neural Network based control of speed for PMSM in both open and closed loop under no-load and loaded condition. A shut circle control framework with ANN procedure in the speed circle intended to work in steady torque and transition debilitating districts. MATLAB reproduction performed in the wake of preparing the neural system (directed learning), results for reference control applications are adequate and appropriate in the process business. Speed control in shut circle at different stacking conditions talked about in detail.