控制理论(社会学)
加权
模型预测控制
电压基准
稳健性(进化)
电压
扭矩
直接转矩控制
病媒控制
计算机科学
支持向量机
工程类
感应电动机
人工智能
控制(管理)
物理
化学
电气工程
基因
热力学
生物化学
声学
作者
Xiaoguang Zhang,Yikang He
标识
DOI:10.1109/tpel.2018.2880906
摘要
To reduce the computation burden and eliminate the weighting factor in conventional speed prediction control, a direct voltage-vector selection-based model-predictive direct-speed control (MP-DSC) method is proposed in this paper. An extended sliding-mode load-torque observer is designed to observe the motor speed and the load torque, which improves the robustness of the system and reduces the influence of measurement noise. Then, the reference voltage vector that includes the system speed and current information is predicted based on the deadbeat control principle. This reference voltage vector is used to construct a cost function, which only includes the error between the reference voltage vector and the candidate voltage vector. Thus, the weighting factor in conventional MP-DSC method is avoided in the proposed method. In addition, a voltage-vector selection method is developed to quickly determine candidate voltage vectors and to ensure the current does not exceed current limit. Finally, the proposed MP-DSC method is experimentally compared with a model-predictive torque and speed control.
科研通智能强力驱动
Strongly Powered by AbleSci AI