Qualitative Event-Based Expert Supervision for Transient Condition Monitoring

This paper addresses the following supervisory problem: a continuous plant (P) is to be supervised via symbolic (or quantised) actions. These symbolic actions suggest the set points for the lower level control loops. The system dynamic is analysed on the supervisory level (K) by a qualitative approach. The relationships between variables and the steady-state references are known. These problems are especially common in chemical process control. The supervisor handles start-up and shut-down procedures and takes appropriate action to solve the sequential or parallel tasks of a basic procedure. The object of this paper is to introduce an approach to solving the problem of how to derive a set of rules from a physical process.The solutions for supervising start-up and shut-down operations in close loop are suitable for large industrial systems, as are as the batch and semi-continuous processes used in order to maintain operations in a dynamic mode. This paper considers the qualitative event-based expert supervision approach to distillation column problems. The development of a general supervision in this work is based on an events generator and a corrective actions generator. The qualitative symbols are based on fuzzy sets. In particular, there are mechanisms for processing the changes in the system variables from qualitative symbols.

[1]  Jan Lunze,et al.  On qualitative identification of linear dynamical systems , 1994 .

[2]  J. Lunze,et al.  A Petri-net representation of the qualitative behaviour of a dynamical continuous-time system , 1994 .

[3]  Benjamin Kuipers,et al.  The composition and validation of heterogeneous control laws , 1994, Autom..

[4]  Flávio Neves,et al.  Qualitative Event-Based Expert Supervision Part 2: Distillation Start-up Condition Monitoring , 1998, IEA/AIE.

[5]  Louise Travé-Massuyès Le raisonnement qualitatif, pour les sciences de l'ingénieur , 1997 .

[6]  Jörg Raisch,et al.  Control of Continuous Plants by Symbolic Output Feedback , 1994, Hybrid Systems.

[7]  Bertrand Zavidovique,et al.  Towards symbolic process control , 1994, Autom..

[8]  Nezha Maamri-Trigeassou Identification et commande des systèmes à représentation continue par la méthode des moments , 1991 .

[9]  Sten Bay Jørgensen,et al.  Knowledge-based control structuring of a distillation plant start-up , 1995 .

[10]  R. Gani,et al.  A generalized model for distillation columns—II: Numerical and computational aspects , 1986 .

[11]  Saibal Ganguly,et al.  Startup of a distillation column using nonlinear analytical model predictive control , 1993 .

[12]  Flávio Neves,et al.  Qualitative Event-Based Expert Supervision Part 1: Methodology , 1998, IEA/AIE.

[13]  Jan Lunze,et al.  Qualitative modelling of linear dynamical systems with quantized state measurements , 1994, Autom..

[14]  Qiang Shen,et al.  Fuzzy qualitative simulation , 1993, IEEE Trans. Syst. Man Cybern..

[15]  M. T. Tham,et al.  An application of qualitative modelling in an intelligent process supervisory system , 1993, Proceedings of IEEE International Conference on Control and Applications.

[16]  Rafiqul Gani,et al.  A generalized dynamic model for distillation columns—III. Study of startup operations , 1988 .

[17]  R. F. Luo,et al.  Fuzzy-neural-net-based inferential control for a high-purity distillation column , 1995 .

[18]  J. Raisch Qualitative control with quantitative models , 1994 .

[19]  G. Fieg,et al.  A new time-optimal strategy for column startup and product changeover , 1996 .