Modeling and Control

Earlier this year I had the pleasure of putting together a class on process control for a group of new software engineers. In most cases, the individuals had no experience in the process industry and no formal training on process control. I used this opportunity to distill into a two day class the key information that I thought these engineers would need to understand the basics of process control. The class material covers only the basic concepts and terminology that a control engineer should be familiar with in performing his job. The class was taped and turned into a DVD that is distributed internally within Emerson for self-study. I thought it might be helpful to post some of the slides from this basic class on process control since it covers and explains most of the terminology and control concepts you will encounter on this blog

In many of our posts, we assume that the reader is an experienced process or control engineer and is familiar with the technical terms used in the post. However, this may no be true for all the readers. Also, some of the terms such as controller gain may be used in different ways within our industry e.g. proportional band vs proportional gain. If you come across a term that is unfamiliar, then there is a good chance that you will find an explanation of the term in this material.

The class material is organized into the following areas of study:

Introduction Historic Perspective
Field Devices and Wiring
Documentation of Plant Control and Instrumentation
Characterizing the Process, Terminology
Control System Objectives
Manual and Feedback Control
Feedforward Control
Cascade Control
Override Control
Split Range Valve Position and Ratio Control
Test Over Class Material

Most of the material is independent of the control system design or manufacturer. However, the workshops were based on the student having access to a DeltaV control system. The control examples in workshop are based on the Foundation fieldbus function block set and thus should be familiar if you have been working with fieldbus systems. You may find it fun to look over the tests that go with this short course. If you aren’t certain about the correct answer to some of the questions, then you may find it helpful to look deeper into the class material.

Recent blogs appearing on http://www.EmersonProcessXperts.com and http://www.controlguru.com discussing the practical value of process models and various controller rules motivated me to write the following for my “Control Talk” column scheduled for the November issue of Control magazine.

I think most astute control people can devise a case where the literal use of their favorite tuning method is better than another method. In the book titled Handbook of PI and PID Controller Tuning Rules 2nd ed by Aidan O’Dwyer there are over 400 pages of tables of tuning rules. My rules are cited 6 times (incorrectly for dead time dominant processes). Obviously the authors of these rules all thought they had something better to offer.

To help put it all in perspective, I offer the following Top Ten List.

Top Ten Reasons to Devise Your Own Tuning Rule and Simulation Test

10. Opportunity to present papers at your favorite conference (whoops - not possible this year at ISA since there are no sessions on traditional process control)
9. Material to start a blog site
8. Competitive edge to start a consulting business
7. Listing in a book on tuning rules
6. Method named after you (sorry Ignatius Michael Coolman, the IMC acronym is taken)
5. Simulations tailored to prove your point
4. Linear processes without control valves
3. Speed since the time to steady state is just a matter of seconds in your simulation
2. Simplicity by ignoring the prevalence, size, speed, and entry point of unmeasured disturbances in real processes and non-stationary behavior
1. Chance to discount industrial online software for controller tuning as just hearsay

What prompted this impromptu column was the realization that diverse tuning rules have a common basis. For example, the equation for controller gain from the Ziegler Nichols ultimate oscillation, Lambda self-regulating and integrating process, and Internal Model Control tuning rules when set for maximum disturbance rejection reduce to the Ziegler Nichols reaction curve rule. For this discussion, we are focusing on loops dominated by a single time constant so that the dead time to time constant ratio is less than 0.5. It is important to remember that maximum disturbance rejection corresponds to maximum transfer of variability from the process control variable to the controller output, which may not be the entire objective. The following files show the basis and importance of this unification and simplification of tuning rules.

Nov 2006 Control Talk Details

Process Responses to Change in Controller Output

Tuning Rule Equations and Relationships

Scan Time Effect on Integrated Absolute Error (IAE)