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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。
Aiming at the problems of increasing system dynamic complexity and modeling difficulties caused by network intervention, the idea of data-driven control was proposed and the controller was designed independently of the system model. The input and output data matrix and output data matrix of the system are constructed by inputting and outputting the current data and the historical data from the online acquisition system respectively. The linear relationship between them is established and the Markov parameters of the system at the current sampling time are obtained. The parameters are substituted into Markov The solution of the Riccati equation expressed in the form of parameters obtains the optimal control gain. At the same time, using the linear relationship between input and output, a controller state observer is constructed and the optimal control law is calculated by using the estimated controller state. Finally, the proposed controller is validated on Truetime1.5 and Matlab simulation platform.