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机构地区:[1]西安科技大学电气与控制工程学院,西安710054
出 处:《科学技术与工程》2014年第36期61-66,共6页Science Technology and Engineering
基 金:国家自然科学基金(51307137);西安科技大学科研培育基金(201318)资助
摘 要:提出一种基于灰预测理论的抗扰动模型预测控制方法。首先推导出模型预测控制系统中干扰量与输出误差之间的解析关系;利用系统已知输出误差建立稳定灰预测模型,预测系统未来时刻的输出误差;根据干扰量与输出误差之间的关系,采用反馈输出误差预测值的方法,实现对系统干扰量的前馈补偿控制。对模型预测控制PMSM调速系统进行仿真实验,选择出干扰观测器抗扰动方法中的最优干扰模型结构;对两种抗扰动方法比较分析得出,基于灰预测理论的抗扰动模型预测控制不需要考虑干扰模型结构,简化了系统设计、提高了系统自适应性,同时能够获得与优化干扰观测器模型预测控制一样的性能。An anti-interference model predictive control (MPC) algorithm based on grey prediction theory was proposed.Analytic expression between interferences and output errors of MPC system are deduced; stabilized grey predictive model is established with known output errors of MPC system to predict the future output errors; based on the relation between interferences and output errors,the predicted output errors are fed back and interferences are restrained by feedforward control.Permanent magnet synchronous motor (PMSM) speed control system with MPC is simulated,and the optimal interference model utilized by disturbance observer is determined.Furthermore,the comparative results of two anti-interference MPC algorithms show that grey predictive method contributes to simplify system design and improve system adaptability because of neglecting the structure of interference model,and has the same anti-interference ability as the optimal disturbance observer method.
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