Industrial Control Systems

Aim

The course should give knowledge about the control methods that are common in industry with a particular focus on how practical control problems can be solved at different levels. After completing the course, each student is expected to know how to:

• Model and analyse discrete-time systems and implement controllers in software
• Design controllers and control structures and evaluate their performance during normal operation
• Design and analyse model predictive controllers (MPC)
• Use programmable logic controllers (PLCs) to analyse and solve sequential control problems with relay ladder diagrams and sequential function charts
• Design and evaluate a control system for a particular lab process with respect to its key characteristics

Content

Sequential control: Function charts, relay ladder diagrams, PLC languages.

Basic tools and methods: Discrete-time control theory, sampling of systems, process models.

Design and tuning of controllers: Internal model control, Smith predictor, reference feedforward control, PID tuning.

Implementation and operation of controllers: Digital implementation, anti-windup, mode transitions, performance measures, Harris index, oscillation index.

Nonlinear control strategies: Selector control, gain scheduling, fuzzy control.

Control system structures: Disturbance feedforward control, cascade control, ratio control, mid-range control, split-range control.

Model predictive control: Formulation of optimization problems for MPC, reference tracking, integral action, stability, explicit MPC.