Advanced process control

In control theory Advanced process control (APC) is a broad term composed of different kinds of process control tools, often used for solving multivariable control problems or discrete control problem.

Overview

Advanced process control is composed of different kinds of process control tools, for example:
* Model predictive control (MPC),
* Statistical process control (SPC),
* Run2Run (R2R),
* Fault detection and classification (FDC),
* Sensor control and
* Feedback systems. APC are often used for solving multivariable control problems or discrete control problem.

Normally an APC system is connected to a distributed control system (DCS). The APC application will calculate moves that are send to regulatory controllers. Historically the interfaces between DCS and APC systems were dedicated software interfaces. Nowadays the communication protocol between these system is managed via the industry standard OLE for process control (OPC) protocol.

Advanced process control: Topics

APC industries

*APC can be found in the (petro)chemical industries where it makes it possible to control multivariable control problems. Since these controllers contain the dynamic relationships between variables it can predict in the future how variables will behave. Based on these predictions, actions can be taken now to maintain variables within their limits. APC is used when the models can be estimated and do not vary too much.

*In the complex semiconductor industry where several hundred steps with multiple re-entrant possibilities occurs, APC plays an important role for control the overall production.

APC is more and more used in other industries. In the mining industry for example, successful applications of APC (often combine to Fuzzy Logic) have been successfully implemented. In the mining industry, the models change and APC implementation is more complex.

Terminology

Manipulated Variables (MVs) are variables where advanced controllers send setpoints to. Controlled variables (CVs) are variables that normally need to be controlled between limits. Disturbance variables (DVs) are only used as an input to the controller, they cannot be influenced, but when measured contribute to the predictability of the CV.

Commercial product examples

*DMCplus from [http://www.aspentech.com/ Aspen Technologies]
*SSE DNP server from [http://www.imperioustech.com/ Imperious Technology]
*RMPCT from Honeywell
*P&C from ABB (Asea Brown Boveri)
*Process Perfecter from [http://www.pavtech.com Pavilion Technologies]
*Connoisseur from Invensys
*INCA from [http://www.ipcos.com IPCOS] (also for batch application)
*ProfitNLC from Honeywell
*GMAXC from [http://www.intellopt.com/ "Intelligent" Optimization]
*Expert System ES III from [http://www.gsl.cz Glass Service]
*eMPC from [http://www.eposC.com/ "eposC" Process Optimization]
*ControlPerformanceOptimizer from [http://matrikon.com/apc-design.aspx/ Matrikon ] and [http://www.controlsoftinc.com/ ControlSoft Inc.]

References

External links

* [http://lorien.ncl.ac.uk/ming/advcontrl/apc.htm Article] about Advanced Process Control.
* [http://hpsweb.honeywell.com/Cultures/en-US/NewsEvents/NewsRoom/PressReleases/PasAcquisition_PR_013007.htm Press Release] . Honeywell Acquires PAS Advanced Process Controls Business
* [http://www.apmonitor.com APMonitor] . Advanced process modeling and estimation.


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