The main aim of the course is to help students acquire in-depth knowledge of digital control, the design of digital feedback control systems, and their use in various engineering applications, ranging from control to medicine and biology. After completing the course the student:
understands the principles of discrete-time modeling and computer control;
understands the common ideas and differences between analog and digital control;
can design, simulate and implement discrete-time controllers (for example discretized PID or state feedback controllers);
understands the Principle of Optimality;
understands the ideas behind optimal controllers, specifically LQ control;
can design and implement LQ controllers;
understands the basics of stochastic control theory and can implement the Kalman filter.
Project (Balancing a 2-wheel robot):
To consolidate the theoretical knowledge obtained during the course, laboratory work is performed on a small-scale balancing robot. The intended learning outcome is not just to make the balancing robot to stand. It is to learn how to design
control schemes in the real world through using a simple and fun object. In practice, you will go through some of the fundamental steps that control engineers usually do in their job.