The Control Talk Blog provides guidance from a user's viewpoint on the design of automation systems, equipment, and piping for process control improvement. Details are offered on the selection and installation of PID controllers, control valves, variable speed drives, and measurements to maximize loop performance. The blogs are often more intensive and extensive and less vendor specific than a white paper. The goal is an advancement of the profession by sharing conceptual principle based knowledge.
Greg McMillan is a retired Senior Fellow from Solutia/Monsanto and an ISA Fellow. At present, he contracts with Emerson DeltaV R&D via CDI Process & Industrial in Austin and consults for MYNAH Simulation Technologies in Saint Louis. Greg received the ISA Kermit Fischer Environmental Award for pH control in 1991, received the Control magazine Engineer of the Year Award for the Process Industry in 1994, was inducted into the Control magazine Process Automation Hall of Fame in 2001, was honored by InTech magazine in 2003 as one of the most influential innovators in automation, and received the ISA Life Achievement Award in 2010.
For basic control, when do I use Fuzzy Logic Control (FLC) and Model Predictive Control (MPC) instead of PID control? The automation and integration of FLC and MPC into distributed control systems makes these a more viable choice. Surprisingly, there may be less decisions and expertise required than for PID control.
In part 5 we finish with a list of my foremost best practices. These practices build on the essential concepts given in Part 3. These practices offer simple fixes in the automation system design. Major improvements in the mechanical design are also introduced.
In part 4 we start a list of best practices. The guidance is the result of decades of experience in plants by industry experts Michel Ruel and Jacques Smuts. The practices are insightful and apply to almost every control loop. The series will conclude next week with my offering.
PID tuning and features determine process performance but the relationship is not well understood leading to a divergence of opinions and a multitude of rules. This seminar unifies major tuning rules to a simpler set that when used with key PID options can achieve a diverse spectrum of process objectives.
In part 3 we start a list of the essential concepts needed to understand what is most important and what to do to help make a loop meet process objectives. The concepts are presented in the broadest possible terms to provide a perspective that can be used in a wide spectrum...
In part 2 we evaluate a misleading statement about the amount of derivative to use and provide some better guidance. We take a look at how mechanical and process design and operating conditions affect the need for derivative action.
The mechanical, piping, and process design determines the steady state and integrating process gains and the process deadtimes and lags. The process engineer usually sets the project basis for the control system in the development of the Process Flow Diagram (PFD) and in the writing of the operating and process descriptions.
Noise in control loops can wear out valves and get amplified by proportional and derivative action. The filter should reduce noise to an acceptable level without appreciably slowing down the loop. I have enlisted the help of key industry experts to provide their guidance.
The PID structures with proportional on error cause a step change in the PID output for a large setpoint change. For structures with derivative on error there is also a sharp bump almost looking like a spike unless you zoom in.
What are the relative merits of different PID structures, a setpoint (SP) filter, and analog output (AO) setpoint rate (velocity) limits? Should I seek a general solution I can use all the time and each knob fits a particular purpose, or a controller with fewer knobs that does exactly what...