Performance assessment of single loop control systems with LQG benchmark

In the industrial process, not only is the output of the system expected to achieve the minimum variance, but also the variance of process input fluctuates in a certain range. However, minimum variance benchmark can meet the former but not the requirements of latter because of strong control effect. Therefore, subspace identification with combined input and output is utilized in this paper to identify single loop control systems, which obtains the process and the noise model, firstly. Then, the performance of the control system is assessed with LQG benchmark combining the control input and output synthetically, and the specific implementation steps are concluded systematically. Finally, the proposed method is verified effective through simulations.