ELE302 Control Systems Engineering 2
Course description for academic year 2024/2025
Contents and structure
The course covers basic principles of modeling, simulation, analysis and design of modern Multiple Input- Multiple Output (MIMO) control systems by using techniques base on state-space (SS) and discrete, sampled systems. MIMO concepts and definitions can however be explained and illustrated by using Single Input-Single Output (SISO) systems to ease understanding. Both Linear-Time-Invariant (LTI)- and nonlinear systems will be studied.
The course addresses themes in electro technology, mechanics, fluid mechanics, and electromagnetism from classical physics together with calculus, linear systems and stability from mathematics so that to form a scientific foundation for working with advanced, dynamical, sampled/discrete automatic systems in technological courses.
The course includes teaching sessions, problem solving seminars, and practical laboratory exercises.
PC together with technical based and simulation software like Matlab for both control, processing, storing and presentation of data, are important tools in the course.
Control Systems Engineering 2 provides an introduction in the following concepts and themes:
- Dynamical modeling of physical MIMO basic systems like electrical, mechanical and electromechanical, from physical principles.
- Mathematical modeling of LTI systems through differential equations in SS, based on linear and vector algebra.
- Block diagrams or signal-flow graphs-based modeling in SS of more complex systems by using canonical SS-models.
- Frequency analysis by using Nyquist diagram in addition to Bode diagram.
- Stability analysis in SS.
- Steady-state error in SS.
- Controller design techniques in SS through pol placement for controller and observer design, diagonalization.
- Sampled systems using z-transform control techniques for sampled systems in SS and optimization by using Model Predictive Control (MPC).
Learning Outcome
Knowledge
After completing the course, the student has knowledge of
- modeling, analysis and design of Multi-Input-Multi-Output (MIMO) dynamic processes based on state Space modeling both in continuous and discrete time domain and frequency domain.
- modern techniques for evaluation of system performance and optimization of control systems. Further, an introduction to some of more Advanced control techniques that have gain success such as Model Predictive Control (MPC) is made.
- how the process model and requirements such as error, frequency and time properties, and the performance of the system are Applied in the design and simulation of modern control systems.
Skills
After completing the course, the student can
- apply modern modelling in state-space to MIMO processes and to analysis and design of MIMO control systems.
- estimate process parameters and performance both from theory, simulations and experiment and apply these to the design of MIMO Control systems.
- implement, take measurements, evaluate experimental data in standard laboratory environment and compare these data with data from design and simulations.
Competence
- The student can solve specific problems in automation by using methods from modern MIMO control systems.
- The student understands the automation engineer's role in the interaction between the technological development and the actual needs in society.
Entry requirements
None
Recommended previous knowledge
ELE204 Control Systems Engineering 1 (or similar)
Teaching methods
Lectures, laboratory work, exercises by using PC and technical-based software.
Compulsory learning activities
3 compulsory assignments, three laboratory exercises with mandatory attendance.
Assessment
4 hours written exam. The grading scale used is A to F. Grade A is the highest passing grade in the grading scale, grade F is a fail.
Examination support material
All support material is permitted
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