Aim
The purpose of the course is to give an overview of the different components that constitute an industrial control system and how these work and interact with each other. Another purpose is to give basic knowledge on the tools and methods used for realisation, analysis and assessment of industrial control systems. Many complex computer control systems today are connected to a very large number of I/O-points. A large process industry may include more than 200 000 measurement points. This requires large computer control systems and the handling of huge amounts of information. How to systematically condense the information from a large number of units? The course will describe and analyze how to structure this kind of large systems. The primary goal is to coordinate many unit processes or machines so that such an “industrial orchestra” is properly conducted.

Knowledge and understanding
For a passing grade the student must

• describe the concepts of states in mathematical modelling of discrete as well as continuous systems

• explain the different components of an automation system for a simple process and understand how they are interacting.

Skills and abilities
For a passing grade the student must

• formulate a mathematical model of a simple process from the information on the constituting components and how they interact and by using this analysing characteristics of the process

• structure a control system for a industrial process consisting of several process units

• program a PLC using suitable tools and standard languages for a simple sequential control task.

Judgement and approach
For a passing grade the student must

assess the appropriateness of control, process monitoring and communication structures for small industrial processes.

Contents

• Complex systems:
  Definition of complexity. How complexity appears in industrial systems. A deeper description of complexities in the process, power and manufacturing industries.

• Description of complex systems: Continuous and discrete event systems. Simulators.

• Modelling large systems. Representation of dynamics in large systems. Stiff differential systems, sparse matrices. Differential-algebraic systems. Model libraries in simulators. Modelling tools and languages.

• Process monitoring: multivariable tools for analysis, estimation, regression, multivariate statistics.

• Structures of industrial computer control systems: The ISO 61131-3 standard. How structures of processes are met by the control systems. Process databases.

• Project: The use of a commercial software package 4Control..

Literature
Olsson G, Rosen C: Industrial Automation, IEA, LTH, 2005. (The same book as in MIE080 Automation)