Advanced Process Control

PARTNERSHIP WITH ESD SIMULATION TRAINING

Wild Geese International and ESD Simulation Training are working together to deliver engaging and highly practical skills to the oil and gas industry. Working together has allowed us to deliver courses at a more affordable price to students, to take advantage of this please contact ESD Simulation Training directly by email at perth@esd-simulation.com or phone at 08 6555 7077 quoting code 714 to receive a 5% discount on your selected course.

COURSE DESCRIPTION

Intensive, three-day, hands-on course using a mixture of exercises including computer simulation models, short lectures, practical exercises and videos. This course begins with a firm foundation in the important fundamentals of PID control, then moves on to explore some of the advanced classical methods and techniques that are popular in the current industrial practice. For all topics, you will gain hands-on experience in tuning controllers and testing algorithm performance.

PRE-REQUISITE

Professionals who are familiar with the general ideas of process control, or who have studied the subject but have never used it in practice.

PARTICIPANT PROFILE

Engineers, chemists, operations and management personnel who wish to formalise and extend their understanding of applied process control and to use this understanding to maximise yields, throughputs, efficiencies and troubleshooting.

LEARNING OUTCOMES

At the end of this course, delegates will:

  • Understand the fundamentals of dynamic process behaviour
  • Be able to collect and analyse process data
  • Be able to tune PI and PID controllers with and without filters
  • Understand non-linear behaviour and adaptive control techniques
  • Be able to optimise PID performance for industrial applications
  • Be able to design and tune cascade control systems
  • Understand feed forward and decoupling control
  • Be able to design and tune a model based control system
  • Appreciate how to control non-self regulating processes

COURSE CURRICULUM

This course will cover information about a series of advanced control systems within the
following sessions:

  1. Fundamental Principles of Process Control
  • Review session
  1.  Modelling Process Dynamics
  • Dynamic process modelling for controller tuning
  • Hands-on: participants will test data for process modelling
  1. Process Control Preliminaries
  • On/off control
  • Intermediate value and the PID algorithm
  1. Proportional Only Control
  • Design of controller
  • Set-point tracking
  • Bumpless transfer
  1. Automated Controller Design
  • Generating good process data
  • Different types of process testing
  1. Advanced Modelling of Dynamic Process Behaviour
  • Overdamped process models
  • Different process responses
  1. Integral Action and PI Control
  • Advantages and disadvantages of PI control
  • Tuning controllers
  • Interaction of PI tuning parameters
  • Reset windup
  • Continuous vs. discrete forms of PI algorithm
  1. Controller Performance Criteria
  • Defining “good” controller performance
  • Popular performance criteria
  1. Derivative Action, Derivative Filtering and PID Control
  • Ideal and non-interacting forms of the PID controller
  • Advantages and disadvantages of PID control
  • Tuning a PID controller
  • The effect of measurement noise on PID control
  1. Cascade Control
  • Tuning a cascade control system
  • Advantages and disadvantages of cascade control
  1. Feed Forward Control
  • Tuning feed forward control systems
  • Advantages and disadvantages of feed forward control
  • Hands-on: participants will engage in an activity involving the tuning process of a feed forward control system
  1. Multivariable Control Interaction and Loop Decoupling
  • Multivariable process control
  • Control loop interaction
  1. Modelling, Analysis and Control of Multivariable Processes
  • Relative gain as a measure of loop interaction
  • Effect of process parameters on loop interaction
  • Decoupling cross-loop effects
  1. Frequently Used Optimisation Techniques
  • Override control
  • Constraint control and optimisation
  • Sample-and-hold algorithm
  • Analyser validation
  • Closed-loop analyser control