Dynamical Systems

The course contains a selection of the following topics, with an emphasis on practical use of digital tools and lab work:

• Modelling and simulation of dynamical systems in the time domain
• State space models and state space analysis
• Conversion between state space and transfer functions
• Similarity transforms of state space models
• Controllability and design of control systems with the use of PID, feedforward, and state feedback (pole placement)
• Integral action and design in state space for error reduction
• Observability and state estimation
• Introduction to discrete-time dynamical systems and digital control systems
• Simulation and visualisation of dynamical systems for analysis, design and verification of control systems
• Possibly other topics

More details on the curriculum will provided during the start of semester.

The course emphasises use of theory and methods in the time domain. There may be minor overlap with topics in the course AIS2002 Control Systems Engineering but the latter emphasises theory and methods in the frequency (Laplace) domain.

Knowledge

• The candidate can explain the use of state space models for modelling, analysis, and control of dynamical systems.
• The candidate can explain principles and methods for state feedback control.
• The candidate can explain controllability and observability.
• The candidate can explain how control systems can be designed using state observers.

Skills

• The candidate can do mathematical modelling of dynamical processes in state space.
• The candidate can manipulate and analyse state space models.
• The candidate can design control systems based on state feedback control. and verify the design using simulation.
• The candidate can design state estimators (observers) for use in control systems and verify the design using simulation.
• The candidate can mathematically analyse stability of control systems modelled in state space.
• The candidate can use modern digital tools as an aid for all the above.

General competence

• The candidate can use digital tools for modelling, analysis, and control of system dynamics.
• The candidate can reflect on the value of cybernetics in technology.
• The candidate can present cybernetics problems, solution methods, and results both written and orally to a technical audience.
• The candidate can evaluate societal and ethical consequences of control engineering.

Learning activities generally include a mix of lectures, tutorials and practical lab/project work. A constructivist approach for learning is endorsed, with focus on problem solving and practical application of theory.