Automation system structures: central, decentral and distributed. Examples from the industry, energetic and transportation sectors. Structures for ensuring redundancy in an automation system. Computation techniques for reliability, availability and safety of an automation system. Mathematical models of processes, equilibrium equations, examples. Process analogies. Multiple-input-multiple-output (MIMO) processes, their control and decoupling. Predictive control basics. Generalized predictive controller (GPC). Illustrative examples from the process industry.

This course qualifies students for design of automation systems for complex processes whereby advanced control methods and concepts are used.

1. recognize various structures of an automation system
2. summarize the principles of achieving hardware and software redundancy in an automation system
3. apply computation techniques of reliability, availability and safety in an automation system
4. apply basic physical laws and process analogies in mathematical modelling of processes of fluid storage, heat transfer and material moving/shaping
5. develop simplified (linearized) mathematical models of processes for control system design purposes
6. employ decoupling techniques for control system design of a MIMO process
7. explain the principles of predictive control of processes
8. compute parameters of a generalized predictive controller (GPC) for a linear process model

Lectures

26 hours of lectures

Consultations

After the lectures or scheduled through e-mail communication

Seminars

3 seminar assignments to be done in Matlab/Simulink environment

Internship visits

Field trip to a typical industrial plant.

1. Lecture 00 -- Course organization and administration; Lecture 01 -- Basic terms from process automation. (2 hours)
2. Lecture 02 -- Structures of automation systems; Lecture 03 -- Process perifery. (2 hours)
3. Lecture 03 -- Process perifery (continuation); Lecture 04 -- Reliability and safety of a process automation system. (2 hours)
4. Lecture 05 -- Conceptualization of a control system. Dynamic process models; Lecture 06 -- Processes of fluid moving and storage. (2 hours)
5. Lecture 06 -- Processes of fluid moving and storage (continuation). (2 hours)
6. Lecture 07 -- Dynamics of heat transfer processes. (2 hours)
7. Lecture 07 -- Dynamics of heat transfer processes (continuation). Solving typical numerical problems from the lectured course materials as a preparation for the midterm exam. (2 hours) Seminar 1 - Modelling and control of a fluid moving/storage process
8. Midterm exam
9. Lecture 08 -- Dynamics of processes for material shaping/moving. (2 hours)
10. Lecture 09 -- Control of multiple-input-multiple-output processes. (2 hours)
11. Lecture 09 -- Control of multiple-input-multiple-output processes (continuation) (2 hours) Seminar 2 -- Tension force control by aluminum tape rolling
12. Lecture 10 -- Model predictive control. (2 hours)
13. Lecture 10 -- Model predictive control (continuation). (2 hours)
14. Field trip to a typical industrial plant. Solving typical numerical problems from the course materials as a preparation for the final exam. (2 hours) Seminar 3 -- Synthesis of a generalized predictive controller for a typical industrial plant
15. Final exam