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Evaluation of a statistically based controller override on a pilot-scale flow loop.

Nagappan Muthiah¹, R Russell Rhinehart

¹School of Chemical Engineering, 423 EN, Oklahoma State University, Stillwater, OK 74078-5021, United States. muthu@contechnet.com

ISA Transactions

|November 10, 2009

Summary

A new statistical override for automatic controllers improves performance by balancing variance reduction in controlled and manipulated variables. Experimental and simulation results confirm the benefits of this enhanced control strategy.

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Area of Science:

Process Control
Statistical Modeling
Automation Engineering

Background:

Conventional automatic controllers often struggle to balance variance reduction between controlled and manipulated variables.
Existing filtering techniques may not provide optimal performance in all scenarios.

Purpose of the Study:

To investigate a statistically based override for automatic controllers.
To temper controller action for improved variance reduction.
To achieve a better balance in variance reduction for both controlled and manipulated variables.

Main Methods:

Implementation of a statistically based override on an automatic controller.
Experimental validation on a pilot-scale flow loop.
Supporting analysis through simulation and theoretical examination.

Main Results:

Demonstrated benefits of the statistical override in experimental results.
Improved balance of variance reduction in controlled and manipulated variables.
Validation of the approach through simulation and theoretical analysis.

Conclusions:

The statistically based override offers a superior method for tempering controller action.
This approach enhances the balance of variance reduction compared to conventional filtering.
The findings are robust, supported by experimental, simulation, and theoretical evidence.