The aim of the course is that the student should acquire basic knowledge of feedback systems, their design and how they are used in control applications.

For a passing grade, the student shall:

• be able to define basic control techniques and terminology.

• demonstrate basic knowledge about proven methods for design of feedback controllers.

• demonstrate the ability to model and simulate dynamic systems based on balance equations and constitutive relationships.

• be able to analyze the static, dynamic and frequency characteristics of dynamic systems using mathematical methods.

• be able to use common methods for dimensioning and analyzing feedback controllers.

• demonstrate the ability to design and implement controllers in teams, and evaluate their performance for a real process.

• demonstrate ability to teamwork and teamwork in group workings

• be able to Identify the usability of simple regulators and identify the need for more advanced methods

Automatic control is the theory of control of processes. A typical example is the cruise control in a car (the car is in this case the "process"), which by varying the throttle ("input" to the process) seeks to keep the speed ("output" of the process) constant despite uphill and counterwind (so-called "Disturbances"). Other common examples include, among other things, the process industry, where it can be used to control pressures and temperatures, and in communication technology where you want to control data transfer rates and transmitter effects.

Control theory, however, is not limited to technical processes but can also be applied in eg Economics and Medicine. One example is the human body's own, highly sophisticated control system, capable of keeping body temperature constant at 37 degrees Celsius despite variations in ambient temperature and keeping body weight constant despite persistently trying for better diet and exercise.

This course is our basic course in automatic control and covers the most common classical methods for analysis and synthesis of feedback control systems for a wide range of technical processes. The course provides thorough knowledge of the subject, sufficient for non-specialists in control engineering to develop simple control systems. The course is a necessary basis for further studies on the subject.

During the course, the following methods and concepts will be discussed:

Introduction: Introduction of common control concepts, such as static systems, dynamic systems, processes, reference signals (setpoint), control signal, output signal (value), interference, open system, measurement signal, feedback, regulator.

Dynamic Models: Mathematical Modeling of Physical Systems. Differential equations. Differential equations on state of the order. Linearization.

Simulation: Introduction to simulation of dynamic systems.

Mathematical Aid: The Laplace Transform and its properties. Transfer function. Static gain. Super-positions principle. Block schemes. Specifications. Rise time. Settling time. Overshoot. Poles. Zeros. Experimental model building. State space models.

Feedback system: PID controller. Feedforward control. Cascade control. Pole placement. Process disturbances. control error. Ziegler-Nichol's methods. Stability concept. State feedback. Reconstruction with observers. Control structures.

Frequency methods: Frequency function. Frequency analysis. Bode plot. Asymptotic Bode plot. Stability. Stability margins. Compensation. Sensitivity. Time delays.

Digital Control: Discretisation. Sampling.

The teaching consists of lectures, lessons, computer exercises and compulsory laboratory exercises. The lectures are devoted to the review of theory sections with problem solving. The lessons are devoted to problem solving and preparation of laboratory exercises.