摘要
步进电机在电能存储和补偿过程中存在建模精确度低、输入采样量失真、模型结构多变和负荷输出失配等问题,从而导致电能存储和补偿无法达到预期设计标准。为此,将仿人MPC算法引入步进电机的数学建模过程中。首先,分析电能从输入采样到输出反馈的数学模型构建过程,以及步进电机存储与建模的工作原理;其次,针对模型失配和参数动态变化对步进电机产生的影响,利用仿人预测控制策略有效地解决了步进电机电能存储和补偿的精度问题。仿真实验结果表明,控制结果在模型匹配时性能良好,在模型失配时依然能满意运行,使储能与建模幅度和误差精度都能达到要求。
In the process of energy storage and compensation of stepper motor,there are some problems such as low modeling accuracy,distortion of input sampling,variable model structure and mismatch of load output,so that the energy storage and compensation can not reach the expected design standards.Therefore,humanoid MPC algorithm is introduced into the mathematical modeling process of stepper motor.Firstly,the mathematical model construction process from input sampling to output feedback as well as the working principle of stepper motor storage and model-ing are analyzed.Secondly,in response to model mismatch and dynamically changing parameters that can have im-pact on stepper motors,the use of a humanoid predictive control strategy effectively solves the accuracy problem of energy storage and compensation.The simulation results show that the control results have good performance when the model is matched,and can still run satisfactorily when the model is mismatched,so that the energy storage and modeling amplitude and error accuracy can meet the requirements.
作者
欧志新
李继侠
邓春兰
OU Zhixin;LI Jixia;DENG Chunlan(Department of Urban Rail Transit and Information Engineering,Anhui Communications Vocational and Technical College,Hefei 230051,China)
出处
《重庆科技大学学报(自然科学版)》
CAS
2024年第5期65-71,98,共8页
Journal of Chongqing University of Science and Technology(Natural Sciences Edition)
基金
2024年安徽省高校自然科学研究重大项目“高速铁路弓网系统机械振动和DMC策略抑制方法的研究”(2024AH040053)
2024年安徽省中青年教师培养行动项目:青年骨干教师境内访学项目“新型配电系统储能与DER智能调度平台”(JNFX2024143)。
关键词
MPC算法
仿人预测控制
步进电机储能
电能损耗与补偿
建模仿真
MPC algorithm
humanoid predictive control
stepper motor energy storage
power loss and compensa-tion
modeling and simulation