Control systems

Introduction to control systems: general, types, effects, building elements, holistic and systemic approach. 

Modelling: objectives, system, process, simulation, theoretical, experimental and combined modelling, cyclic approach in modelling and simulation, examples: car suspension, room heating, pray and predator system, SIR model of epidemics. Presentation of models in Dymola-Modelica environment. 

Model descriptions: differential equations, transfer functions, block diagrams. 

Simulation: basic methods (indirect approach, transfer functions), description of Matlab-Simulink environment. 

Computer-aided analysis, modelling and simulation. 

Analysis of systems in the time domain: influence of poles and zeros, proportional, integral and differential systems, stability. 

Control systems: open-loop, closed loop system, tracking and regulating performance, control quality indicators, working point treatment, steady state analysis, stability. 

Control algorithms: PID algorithm, the determination of the parameters with setting rules, optimization of parameters by using the Matlab environment, suitable functions, computer implementation of the PID algorithm. 

Analysis and design of control systems with root locus diagram. 

Analysis and design of control systems in the frequency domain. 

Analysis and design of control systems in state space, state observers. 

The basic objective is to present the control system’s area in an interesting way through a number of cases, the use of computer tools and practical work in a well-equipped laboratory. Acquired skills are as follows: modelling and simulation of systems that occur in automation, understanding the principles of feedback loop, PID control and more advanced control approaches: compensation methods, the state space control , …), presentation and usage of advanced software tools for system analysis, modelling, simulation and control design.

Lectures, laboratory exercises.