摘要
针对永磁同步电机调速系统,首先提出一种基于多维泰勒网的非线性观测器方案,该方案相对于神经网络观测器,具有结构简单、计算复杂度低的优势。然后,基于Lyapunov理论设计多维泰勒网权值的自适应学习规则,从理论上证明了非线性观测器的稳定性。最后,系统仿真结果验证了其有效性。
Aiming at the speed variable system of permanent magnet synchronous motor,a nonlinear observer is firstly designed based on the multi-dimensional Taylor network.Compared with the neural network observer,the advantages of the proposed scheme are both simple structure and low computational complexity.What’s more,the Lyapunov function is created,the adaptive learning rule is given for the weights of multi-dimensional Taylor network,and we prove the stability of nonlinear observer.Finally,the example simulation results verify the scheme’s significance.
作者
翟海庆
崔瑞超
王彦昊
张超
ZHAI Haiqing;CUI Ruichao;WANG Yanhao;ZHANG Chao(School of Computer Science and Technology,Henan Institute of Technology,Xinxiang 453003,China;School of Electrical Engineering and Automation,Henan Institute of Technology,Xinxiang 453003,China;Xi′an Thermal Power Research Institute Co.,Ltd,Xi′an 710054,China)
出处
《河南工学院学报》
CAS
2021年第3期20-25,共6页
Journal of Henan Institute of Technology
基金
河南省重点研发与推广专项(212102210015)
河南工学院高层次人才科研启动基金(KQ1863)
河南工学院教育教学改革研究与实践项目(DQXY-2019005)。
