AUV Low-Speed Following Based on Model Predictive Current Control of Data Fusion

• Published in: 2023 IEEE 7th Information Technology and Mechatronics Engineering Conference (ITOEC) Vol. 7; pp. 1830 - 1834
• Main Authors: Wei, Shumeng, Xu, Xiaoting, Li, Yanshuo
• Format: Conference Proceeding
• Language: English
• Published: IEEE 15.09.2023
• Subjects: Data integration; low-speed following; Measurement uncertainty; MPCC; Phase measurement; Prediction algorithms; Predictive models; Propulsion; propulsion system; Temperature measurement
• ISSN: 2693-289X
• DOI: 10.1109/ITOEC57671.2023.10291349

Low-speed following is one of the goals of AUV. The Permanent Magnet Synchronous Motor (PMSM) is used as the main propulsion motor of AUV. Since the PMSM drive system is a complex coupling and multivariable system, Model Predictive Current Control (MPCC) is used to simplify the equation and improve the system performance. Applied to AUV speed tracking, MPCC is compared with the SVPWM-based method, which has faster response time and smaller overshoot. Due to the algorithm uses current to build cost function to select the optimal switch combination. Therefore, the sampling accuracy of the current has a big influence on the control of AUV. However, in practical system, the current sensor is affected by ambient temperature and system noise. When the current of one phase is affected, the phase is reconstructed by other phases, which is integrated with the measured data with errors. The model based on data integration algorithm is proposed to reduce the accuracy degradation caused by current errors. MPCC based data fusion can ensure that the actual rotate speed of the propulsion system better follows the expected speed and achieves the purpose of low speed monitoring in the Simulink.