CODE 111107 ACADEMIC YEAR 2026/2027 CREDITS 5 cfu anno 1 ELECTRONIC ENGINEERING 11970 (LM-29) - GENOVA 6 cfu anno 1 COMPUTER ENGINEERING 11965 (LM-32) - GENOVA SCIENTIFIC DISCIPLINARY SECTOR IINF-04/A LANGUAGE English TEACHING LOCATION GENOVA SEMESTER 2° Semester MODULES Questo insegnamento è un modulo di: SYSTEM IDENTIFICATION AND OPTIMAL CONTROL TEACHING MATERIALS AULAWEB AIMS AND CONTENT LEARNING OUTCOMES The purpose of the module is to introduce the development of control techniques based on the minimization of cost functionals such as LQR, LQT, and LQG, also relying on identification and estimation theory. AIMS AND LEARNING OUTCOMES Students will learn the basis of optimal control in different application contexts. They will be able to implement a quadratic controller to stabilize a linear system and to track a state trajectory both in the deterministic case and in the stochastic one. They will also learn suitable optimal control methods for nonlinear systems and uncertain ones. TEACHING METHODS The course consists of classroom lectures and PC-assisted demonstrations Students who hold valid certificates relating to Specific Learning Difficulties (SLD), disabilities or other educational needs are invited to contact the lecturer and the school’s disability liaison officer at the start of the course to agree on any teaching arrangements which, whilst respecting the course objectives, take into account individual learning styles. The contact details for the university’s disability liaison officer are available at the following link: https://unige.it/commissioni/comitatoperlinclusionedeglistudenticondisabilita. SYLLABUS/CONTENT -Introduction to cotimal control -the principle of optimality -linear quadratic optimal control: regulation and tracking -presence of disturbances: LQG contol -receding horizon control -optimal control for nonlinear systems -uncertain systems, state augmentation, connections with identification -introduction to “maximum information gain” control -introduction to machine learning methods for optimal control RECOMMENDED READING/BIBLIOGRAPHY A. Bryson and Y-C Ho. Applied Optimal Control: Optimization, Estimation, and Control. Abingdon, UK: Taylor & Francis. Y. Bar-Shalom, X. R. Li, T. Kirubarajan, “Estimation with Applications to Tracking and Navigation”, John Wiley & Sons Further readings will be given by lecturer. TEACHERS AND EXAM BOARD MARCO BAGLIETTO Ricevimento: Appointments can be fixed at the beginning or ending of any lecture or by email with a few working days of advance. Exam Board MARCO BAGLIETTO (President) GIOVANNI INDIVERI GIORGIO CANNATA (President Substitute) LESSONS LESSONS START https://easyacademy.unige.it/portalestudenti/index.php?view=easycourse&_lang=it&include=corso Class schedule The timetable for this course is available here: Portale EasyAcademy EXAMS EXAM DESCRIPTION Oral exam with discussion of optimal controlmethods and possible applications. Students with learning disorders ("disturbi specifici di apprendimento", DSA) will be allowed to use specific modalities and supports that will be determined on a case-by-case basis in agreement with the delegate of the Engineering courses in the Committee for the Inclusion of Students with Disabilities. ASSESSMENT METHODS The students will be evaluated on the basis of their capability to describe optimal control algorithms, to choose suitable methods depending on the application context and to discuss the computational complexity of the methods and their implementation. FURTHER INFORMATION Students with valid certifications for Specific Learning Disorders (SLD) may request accommodations for exams at least 7 days prior to the exam date by filling out the “accommodation request form” (available via online services at https://modulionline.unige.it/richiesta-adattamenti# no-back), which will be automatically forwarded by the system to the instructor in charge of the course and to the faculty liaison for students with disabilities and SLDs in their School/Department. The student will receive a copy of their request.
