Unit FEEDBACK CONTROL SYSTEMS
- Course
- Computer science and electronic engineering
- Study-unit Code
- 70A00093
- Curriculum
- Ingegneria informatica
- Teacher
- Paolo Valigi
- Teachers
-
- Paolo Valigi
- Hours
- 81 ore - Paolo Valigi
- CFU
- 9
- Course Regulation
- Coorte 2018
- Offered
- 2020/21
- Learning activities
- Caratterizzante
- Area
- Ingegneria informatica
- Academic discipline
- ING-INF/04
- Type of study-unit
- Obbligatorio (Required)
- Type of learning activities
- Attività formativa monodisciplinare
- Language of instruction
- Italian
- Contents
- Modelling with the state space, linear and nonlinear models, numerical simulation. Modal analysis. Structural properties. Lyapunopv stabilty. Pole placement, state observer, separation principle.
Basic on optimal control. Basic on Kalman filtering and LQG control.
PID regulators, tuning and autotuning. Receding Horizon Control.
Application to motion control problems, also with application to mobile robots and drones. - Reference texts
- Fondamenti di controlli automatici, by Paolo Bolzern, Riccardo Scattolini, Nicola Schiavoni, Mc Graw Hill Education, 2015.
Additional notes from the instructor. - Educational objectives
- Basic methods for modelling, simulation and analysis.
Knowledge to correctly understand and design pole placement control schemes based on pole placement and observer design, LQR and LQG regulators, PID regulators and auto-tuning.
Control schemes for general motion control problems. Realization of simple schemes on mobile robot platforms. - Prerequisites
- The comprehension of the classes and of the teaching assignments requires a complete comprehension of the contents of the course "Automatic Fundamentals". In addition, knowledge on the areas of matrix calculus, vector spaces, ordinary differential equations, and complex numbers are of major relevance.
Finally, an intermediate level of knowledge of at least a programming language is also required. - Teaching methods
- Lessons, exercises, programming examples.
- Other information
- During the course, some experimental activities will be carried out. Students will have the possibilty to carry out additional activities, upon request.
- Learning verification modality
- Written and oral test, both mandatory. A project can also be discussed, based on student choice.
In case of mandatory restriction due to the CODIV-19 emergence, rules could change, as discussed at the end of this field.
The written test is aimed at verifying that the student is able to solve simple modeling and control problems, related to the control schemes discussed during the lessons.
The oral test is based on three open questions, comprising discussion of the written test, with an overall duration of about 30 minutes. To be admitted to the oral test, the mark on the written assignment has to be larger then, or equal, to 15/30.
The oral test is finalized to check that the student has acquired a satisfactory level of comprehension and understanding of the theoretical concepts covered by the course, as well as the interaction with the general topics of computer and electronic engineering. Finally, basic algorithms be discussed, with the use of pseudo-code or any other programming language of student choice, aimed at the solution of common analysis, synthesis, or simulation problems.
In the case in which the COVID-19 crisis would impose some restrictions, the final test structure will be modified accordingly. The aim of the test will remain that of verifying both the student ability to solve analysis and control problems, and the student comprehension of the topics covered by the course. - Extended program
- Dynamic modelling and state space models: examples and real cases.
Analysis of causal, finite dimensional, linear, time-invariant systems.
State space transformations, modal analysis, convergence and eigenvalues role.
Structural properties
Reachability, observability, criteria, Kalman decomposition and transfer function structure.
Stability
Equilibrium, Lyapunov definitions, criteria per linear systems and for the general linear and nonlinear case.
Feedback and control design
Output regulation, internal model.
Pole placement, state observers, separation principle.
Basics on optima control, Kalman filtering, and LQG regulators.
PID regulators, structure and tuning. Improvements.
Minimal realizations.
Simulation
Basic approaches to the numerical simulation of dynamical systems.
Pseudo-code Octave and Python examples for the analysis, design and simulation