COURSES

Goals

Control is a "hidden" technology which ensures efficient and safe operation of systems in accordance with the requirements. The aim of the course is to acquiaint students with basic concepts and to present a number of state-of- the-art procedures for solving complex control problems. The course will provide a framework for understanding control technology in the form of a life cycle model which interconnects practical requirements, design and implementation in a concise manner. Procedures for planning self-adjusting and adaptive systems, non-linear control systems and supervision systems will be presented in greater detail. Practical examples highlighting the basic concepts will be provided as well. The student will be able to analyze the dynamics of the system, plan a system of optimal management, and plan virtual sensors.

Curriculum

1) Introduction Life-cycle basics: technical implementation phases, the analysis of functional requirements (what the system should do), specification, design, implementation and maintenance; non-technical aspects (man-machine interface, technoeconomics, social aspects). 2) Basic building blocks of state-of-the-art control technologies Review of sensors, actuators, signal conditioning and transmission; sampling. 3) Modern concepts of control design in time space Basic concepts: controllability; identifiability; optimal state regulator; self-adjusting and adaptive regulators; examples from industry. 4) Intelligent supervisory systems Reliability, efficiency and quality requirements; early error detection procedures based on models; application of signal processing methods; fault isolation by using approximate reasoning; examples of industrial applications. 5) Model based control Practical relevance of state estimation of dynamic systems; Kalman filter; extended Kalman filter; "bootstrap" procedures for state estimation of nonlinear dynamic systems; examples of application in forecasting and navigation; predictive control. 6) Predictive control Basic concepts; solution of the quadratic cost function; tuning; robustness; application.