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大惯量随动系统解析模型预测控制
引用本文:汪正军,王军政,马立玲,赵江波.大惯量随动系统解析模型预测控制[J].北京理工大学学报,2011,31(11):1307-1312.
作者姓名:汪正军  王军政  马立玲  赵江波
作者单位:北京理工大学自动化学院,北京,100081
基金项目:北京市产学研科研基金资助项目
摘    要:为了提高时变负载大惯量随动系统的响应速度以及控制精度,将解析模型预测控制运用到负载系统的控制策略中.建立了大惯量随动系统负载的动力学模型,并考虑系统性能指标、能量输入功率和制动功率等约束条件,通过双无迹卡尔曼观测器对负载惯量扰动进行实时观测,实现了大惯量随动系统的解析模型预测控制.仿真试验结果表明,包含了约束条件的解析模型预测控制,减小了大惯量随动系统的响应时间,提高了控制精度,达到了预期的控制效果.

关 键 词:大惯量随动系统  解析模型预测控制  能量约束  扰动观测器  永磁同步电机
收稿时间:2010/12/31 0:00:00

Explicit Model Predictive Control for Large Inertia Servo System
WANG Zheng-jun,WANG Jun-zheng,MA Li-ling and ZHAO Jiang-bo.Explicit Model Predictive Control for Large Inertia Servo System[J].Journal of Beijing Institute of Technology(Natural Science Edition),2011,31(11):1307-1312.
Authors:WANG Zheng-jun  WANG Jun-zheng  MA Li-ling and ZHAO Jiang-bo
Institution:School of Automation, Beijing Institute of Technology, Beijing 100081, China;School of Automation, Beijing Institute of Technology, Beijing 100081, China;School of Automation, Beijing Institute of Technology, Beijing 100081, China;School of Automation, Beijing Institute of Technology, Beijing 100081, China
Abstract:This paper aims at improving the dynamic response and control precision of large inertia servo system with time-varying loading disturbance by using the scheme of explicit model prediction control (EMPC). The dynamic model of the large inertia servo system was directly established, the loading disturbance was observed by the dual unscented Kalman filter (DUKF) and the constraints such as system performance, input and braking power were considered. Thus, the EMPC control strategy was realized. The experimental results show that the response time is reduced with satisfactory control precision and the expected performance has been achieved.
Keywords:large inertia servo system  explicit model prediction control (EMPC)  power constraints  disturbance observer  permanent magnet synchronous motor (PMSM)
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