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.
We conclude this series with a look at how to tune a controller when the objective is to maximize the absorption of variability rather than tight control of the process variable. The details for the most common case of surge tank level control are provided.
We are aware that too high of a PID gain can cause excessive oscillations and even instability. The ultimate gain for processes with no steady state on PID horizon is usually much higher than our comfort level.
Many of the most important process variables, such as vessel and column composition, pressure and temperature, do not reach a steady state in the time frame of PID action. Batch composition, pH and temperature and, of course, level have no steady state.
The PID is by far the most prevalent controller in the process industry. Here we step back for a view of the basics of the proportional, integral, and derivative modes. These PID controller modes have distinct advantages and disadvantages and consequences if one mode dominates.
Older Distributed Control Systems (DCS) and analog controllers tended to have different tuning setting units and methods of implementing integral and derivative action. A lack of understanding of the difference between the old and new PID features and tuning settings can lead to poor and even unstable control when migrating...
For advanced regulatory control, when do I use Model Predictive Control (MPC) instead of PID control? There are many PID techniques for dealing with batch operations, abnormal operation, startups, and transitions. Feedforward, ratio control, and override control are a main stay for PID control. If desired, PID dead time compensators...
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.