Facoltà di Ingegneria - Guida degli insegnamenti (Syllabus)

The student is required to be familiar with the basic elements of Systems Theory, Control Theory, Probability theory, Linear Algebra; Math Analysis; Physics.

The course has the aim to increase the knowledge learnt in the base courses, related to the problems of automatic control of engineering interest, referred to more general operative situations. Students will learn theorical elements for the planning and optimization of advanced control systems with high performance in case of complex real operative situations.

The course, even it is more aimed at increasing theorical knowledge, will provide experiences in applying the elements learnt in analysis and planning of complex automatic control systems. The considered case studies will provide experience to introduce measure indexes and optimization in real situations with high presence of noise. At the end of the course, students will be able to autonomously model and design dynamic systems.

In the course are strengthened the competences that leads to identifying and solve in a better way, complex problems of engineering nature. Besides, it is increased the problem solving capacity and the identification of suitable optimization indexes.

essons (52 Ore) - Elements of probability theory and stochastic processes. - Minimum variance estimate. Orthogonal projection Lemma - Kalman filter. Optimal smoothers and predictors. - Dynamic programming equations. LQ and LQG control problems. - Optimal stabilization and tracking over finite and infinite time intervals. - Minimum variance control of industrial processes- - Adaptive control Laboratory (20 Ore) LabVIEW and Matlab use for advance control systems design.

The final examination consists of an oral test. Usually, the first question concerns the discussion of a case study

Knowledge assessment of a number of topics of the course.

Measurement of the mastery of at least two of the course topics.

Average between the two discussed arguments.

Lessons (52 Ore) - Elements of probability theory and stochastic processes. - Minimum variance estimate. Orthogonal projection Lemma - Kalman filter. Optimal smoothers and predictors. - Dynamic programming equations. LQ and LQG control problems. - Optimal stabilization and tracking over finite and infinite time intervals. - Minimum variance control of industrial processes- - Adaptive control Laboratory (20 Ore) LabVIEW and Matlab use for advance control systems design.

- Ingegneria Informatica e dell'Automazione (Corso di Laurea Magistrale (DM 270/04))

**Università Politecnica delle Marche**

P.zza Roma 22, 60121 Ancona

Tel (+39) 071.220.1, Fax (+39) 071.220.2324

P.I. 00382520427