The Process Control Optimization (PCO) training course provided by Lambda Controls is a four-day course offered on a registration basis at a meeting facility convenient to several Pulp/Paper mills in an area (where feasible). The PCO course can also be held on-site at a mill. This course is designed to improve the ability of course participants to identify and correct process control problems and in particular, control loop problems. The PCO course is intended for a general technical audience consisting of mill instrumentation engineers, process engineers, control system engineers and operations personnel. It will also be useful to electrical/instrument technicians involved in control loop trouble-shooting and/or control loop tuning.
The PCO course is a combination of classroom based lectures and computer based lab work. The lab work consists of controller tuning and process control trouble-shooting exercises using a PC based process and control system dynamic simulator of a typical stock preparation process. If the course is held on-site at a mill, process data collected on site during the course can be used for classroom discussion. The computer based lab work and discussions of mill data and/or case studies make up about 50 percent of the course.
The goal of the PCO course is to heighten the awareness of process variability and the role of the control system and controller tuning, process equipment and process design, in reducing process variability and optimizing process performance.
Understanding how variability propagates from one place in the process to another and the capabilities of the process and the control system to reduce variability requires a basic understanding of process dynamics and control system dynamics. For this reason roughly half of the course is dedicated to presenting process dynamic models, controller dynamics, controller tuning and control loop performance concepts. The major topics include:
With this background covered the course focus moves to optimizing the control system to improve process performance and tools for analyzing and troubleshooting process variability. The major topics include:
Evaluating variability, sources of variability, control loop components, control system performance
Self-regulating and non-self-regulating processes, performing bump tests and interpreting the results, first order with deadtime process model for a self-regulating process, integrator with deadtime process model for a non self-regulating process, effect of control loop filtering on bump test results
Control valve backlash and stiction, control valve dynamic performance evaluation, process inherent non-linearities, impact of non-linearities on control performance
Description of PID control action, different forms of PID controller, tuning parameter description
Survey of controller tuning methods, Lambda Tuning method for a self-regulating process, guidelines for selecting Lambda, advantages of Lambda tuning over other tuning methods, control loop tuning robustness, guidelines for employing control loop filtering
Regulatory control, setpoint tracking, control loop cut-off period of a Lambda tuned loop, performance limitations of a PID controller
Lambda tuning rule for a non self-regulating process, tank level control loops, tuning strategy for level control
Tuning interacting control loops, tuning cascade control loops, defining process objectives, developing a tuning strategy for several interacting control loops
Controller tuning, loop health, loop design issues
Auto/manual tests, coupling tests, introduction to time series analysis tools, introduction to process and control system performance evaluation