摘要
针对线性时变多变量系统,在可能存在输入输出数据噪声的情况下,不需已知系统的先验结构信息,提出一种完全数据驱动的子空间辨识及控制器设计方法.在子空间在线辨识基础上,利用不确定性模型更好地建模被控系统,结合鲁棒控制策略进行预测控制器的设计;将系统建模与鲁棒控制器的设计包含在一个控制系统设计框架内,对模型不确定性具有更好的鲁棒性;最后给出仿真实例验证算法的有效性.
In the existence of system noise, a new data-driven controller is proposed without any prior knowledge for linear time-varying (LTV) multivariable system. Through online subspace identification, uncertainty model is used for better description of the controlled system. The new predictive controller is designed by combining the robust control strategy. The system modeling and design of robust controller are then included in a framework, which increases robustness of the control system. Finally, an example is given to demonstrate the usefulness and efficiency of the proposed method.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2007年第5期732-736,742,共6页
Control Theory & Applications
基金
国家自然科学基金资助项目(60474051
60534020)
国家863计划资助项目(2006AA04Z173)
国家教育部新世纪优秀人才计划资助项目
关键词
子空间辨识
鲁棒性
预测控制
subspace identification
robustness
predictive control