Research Of Performance Evaluation For Control Systems

Now the researches of control engineering domain mainly focus on model identification, design of controller and robustness of control systems, etc. Little has been done to the performance assessment of the running control systems. In fact, many control systems can't achieve the design index. So, it is a concerned problem for local technicians and control engineers that how to obtain the performance information of the control systems from the operating data so that the performance problem can be recognized and diagnosed early. Recently, the demand of high control system performance from industry promotes the development of the research of control system performance assessment and diagnosis rapidly.First, the minimum variance benchmark which is the most extensive useful performance evaluation method is introduced in this paper. The minimum variance benchmark can provide a practical reference to the performance of control systems, and this method only need the routine data and the time delay of the process. In order to evaluate the control systems, we use the method that compare, the output variance with the minimum variance. And the evaluate methods for single loop and multivariate control systems are introduced in this paper. The results of the simulation show that these methods are available in performance evaluation.The evaluation of a specific structure of the PID control system and the feedforward PID control system is considered in this paper. Instead of the minimum variance control, PID controller achievable minimum variance is used in this method. The simulation show that the PID control system using the new method in performance evaluation system is superior to the minimum variance approach.Finally, in this paper, a new method based on principal component analysis for multivariable process control system performance evaluation is introduced. A number of variables can be reduced-order and decoupled by using the PCA approach, and then the independent and low-dimensional variables can be evaluated. Simulation shows that the PCA is a viable method of performance evaluation, and compared with the original multi-variable control system performance evaluate method the new method is a simple one. And at last the method is used in the continuous industrial processes and in batch process, it shows that the method based on principal component analysis is a practical evaluate approach in multivariate process control system.