2026-10-06T07:28:33Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34002057 2026-10-01T01:52:29Z category_26431 item_type_3 month_year_10_2026

Clustering-Enhanced MCNN-LSTM-Based Control Method for PMSM Under Multi-Operating Conditions Tingting Wang (25113643) Wenjing Liu (22944343) Huangshui Hu (25113650) Lijie Han (25113651) Cong Zhang (25113654) Control engineering PMSM (permanent magnet synchronous motor), SVPWM (space vector pulse width modulation), VSI (voltage source inverter) K-means clustering method Long Short-Term Memory Network (LSTM) <p dir="ltr">To address the issues of deteriorating dynamic response, disturbance rejection performance, and steady-state accuracy of permanent magnet synchronous motors (PMSMs) under multi-operating conditions, as well as the difficulty of accurately characterizing operating-condition differences using a unified data-driven compensation model, this paper proposes a clustering-enhanced multi-scale convolutional neural network-long short-term memory (CE-MCNN-LSTM) control method. The method constructs operational state features and incorporates K-means clustering to embed operating-condition distance information into the control compensation model, thereby enhancing the model's ability to perceive and characterize different operating conditions. Based on this, a multi-scale convolutional neural network (MCNN) is used to extract local dynamic features, which are combined with a long short-term memory network (LSTM) to establish a temporal mapping relationship for control compensation. This is then integrated with a PI controller to form a composite control strategy. Using the PMSM hardware-in-the-loop simulation platform, comparative validation is conducted under typical operating conditions, including no-load, sudden load changes, and steady-state load. The results indicate that the proposed method outperforms the comparison methods in terms of speed tracking, disturbance recovery, and torque fluctuation suppression, effectively improving the control performance and operational stability of PMSMs under complex operating conditions.</p> 2026-10-01T01:52:29Z Dataset Dataset 10.6084/m9.figshare.34002057.v2 https://figshare.com/articles/dataset/Clustering-Enhanced_MCNN-LSTM-Based_Control_Method_for_PMSM_Under_Multi-Operating_Conditions/34002057 CC BY 4.0