摘要
针对网络介入导致的系统动态复杂性增加及建模困难等问题,提出了基于数据驱动控制的思想,独立于系统模型设计控制器。利用在线获取的系统输入/输出当前数据和历史数据,分别构造系统的输入数据矩阵和输出数据矩阵,建立两者之间的线性关系,获得当前采样时刻系统的Markov参数,将该参数代入到Markov参数形式表示的Riccati方程解中,获取最优控制增益。同时利用输入与输出之间的线性关系,构造一个控制器状态观测器,利用估计的控制器状态参与计算最优控制律。最后,在Truetime1.5和Matlab仿真平台上验证了提出的控制器是有效的。
System dynamics characteristic will become complicated when the network is introduced into the system, it will be difficult to model the plant. Data-driven control theory is proposed to design the controller instead of the conventional model based controller in this paper. First construct the input data matrix based on the current and historical input data, output data matrix based on the current and historical output data. Then get the current system Markov parameters by establishing a linear relationship between the two. The optimal control gain is obtained after substituting the Markov parameters into the solution of the Riccati equation in the form of Markov parameters. Simultaneously, construct a controller state observer by using the linear relationship between the input and output data. The estimated controller state is used to calculate the optimal control law. At last, the simulation example with truetimel. 5 and Matlab verifies the methods and conclusions proposed.
出处
《控制工程》
CSCD
北大核心
2012年第1期165-168,共4页
Control Engineering of China
基金
教育部新教师基金(60774030)
国家博士后特别资助(0801001B)
关键词
网络
最优控制
基于数据
网络控制系统
network
optimal control
data-based
network control system