Achievable Performance Assessment and Design for Parallel Cascade Control Systems

The cascade control technology has been widely implemented through the industries. The focus of this paper is the assessment of a parallel cascade control system scheme against an achievable performance standard. Following the methodology of the univariate control loop performance, a procedure is derived based on the minimum variance and the Diophantine decomposition for the parallel cascade control system. The performance bound is computed using the minimum process variances which depend on the controllers. Besides, the achievable performance bound and the corresponding optimal parameters of the PID controller structure computed from the closed loop operating data are also proposed. It can assess the performance of the current given controller. If the cascade controllers are not operating at the achievable bound, the reduction of the output variability can be achieved based on the estimation of the controller parameters of the PID-achievable performance. The performance of the proposed method is illustrated through a simulation problem and a pilot scaled experiment.

[1]  T. Harris.  Assessment of Control Loop Performance , 1989 .

[2]  Sunwon Park,et al.  Enhanced Control with a General Cascade Control Structure , 2002 .

[3]  Paul M. J. Van den Hof,et al.  An indirect method for transfer function estimation from closed loop data , 1993, Autom..

[4]  K. Åström.  Introduction to Stochastic Control Theory , 1970 .

[5]  Thomas F. Edgar,et al.  Performance assessment of cascade control loops , 2000 .

[6]  Pradeep B. Deshpande,et al.  When to use cascade control , 1990 .

[7]  T. Harris,et al.  Performance assessment measures for univariate feedback control , 1992 .

[8]  Gaetano Scarano,et al.  Discrete time techniques for time delay estimation , 1993, IEEE Trans. Signal Process..

[9]  P.-G. Eriksson,et al.  Some aspects of control loop performance monitoring , 1994, 1994 Proceedings of IEEE International Conference on Control and Applications.

[10]  Nina F. Thornhill,et al.  Refinery-wide control loop performance assessment , 1999 .

[11]  S. Merhav,et al.  Identification of linear systems with time-delay operating in a closed loop in the presence of noise , 1976 .

[12]  Ai Poh Loh,et al.  Relay feedback auto-tuning of cascade controllers , 1994, IEEE Trans. Control. Syst. Technol..

[13]  Wei Xing Zheng,et al.  Identification problems in distributed parameter neuron models , 1990 .

[14]  Lennart Ljung,et al.  System Identification: Theory for the User , 1987 .

[15]  Thomas F. Edgar,et al.  Computer-aided process control system design using interactive graphics , 1981 .

[16]  Sirish L. Shah,et al.  Performance Assessment of Control Loops: Theory and Applications , 1999 .

[17]  Thomas E. Marlin,et al.  Process Control: Designing Processes and Control Systems for Dynamic Performance , 1995 .

[18]  Alessandro Brambilla,et al.  An Efficient Structure for Parallel Cascade Control , 1996 .

[19]  P. Atkinson,et al.  Process Control Systems , 1968 .

[20]  William L. Luyben,et al.  Parallel Cascade Control , 1973 .

[21]  Sunwon Park,et al.  PID controller tuning to obtain desired closed loop responses for cascade control systems , 1998 .

[22]  D. Etter,et al.  Adaptive estimation of time delays in sampled data systems , 1981 .