Second Cycle (Laurea magistrale) Degree Programme in Robotics and Automation Engineering
Prof.: Mario Innocenti
Prof.: Andrea Caiti
Italian/English (Students Choice)
The student who successfully completes the course will be able:
- to possess the analytical tools for the estimation of uncertain parameters in dynamic systems;
- to compute appropriate models of dynamic systems based on parameter estimation and processing of deterministic and stochastic measurements;
- to analyze and model multivariable linear systems under a large class of structured and unstructured uncertainties;
- to design robust controllers in the framework of norm-based performance and stability specifications.
- to write software advanced code for the digital implementation of advanced identification and control techniques.
- Elements of Signals and Sampling theory;
- Estimation theory (Bayesian estimation and Kalman filtering);
- White/Grey/Black box modeling; Box-Jenkins models, prediction, parametric and non parametric identification; spectrum estimation; Linear Matrix Inequalities;
- Linear multivariable systems (MIMO) review. Optimization, linear quadratic regulator, linear Gaussian optimal control;
- MIMO tools: 2-Block representation, internal stability, small gain theorem. State space and frequency approaches, Singular values, signal and system norms. H2 analysis;
- MIMO shaping, weighting functions, scaling. Performance limitations. Uncertainty classification, robustness Theorems. Robust Loop shaping, MIMO stability margins, structured singular value;
- Robust Control design: Kalman Inequality, Nyquist Criterion. LQG/LTR controller. H2 e Hinf control, D-K iteration. MU analysis and synthesis.
For this course the prerequisite/s is/are
face to face
The recommended text for the "Identification of Uncertain Systems" module is:
L. Ljung: "System Identification: theory for the user", Prentice-Hall, 1987
The recommended texts for the "Control of Uncertain Systems" module are:
“Robust Control Systems: Theory and Case Studies”, Mackenroth, U. Springer, 2004
“Essentials of Robust Control”, Zhou, K., Doyle, J., Prentice Hall, 1998 (http://www.ee.lsu.edu/kemin/essentials.htm)
Additional material, and class notes for the same module can be downloaded at: http://www.dsea.unipi.it/Members/innocentiw/didattica-materiale/cisi/.
The final grade is determined as the average of the two modules (identification and control).
The student preparation will assessed during the oral exam. The primary elements of evaluation are: - The ability to communicate in a clear and formal language appropriate for the advanced understanding of science and engineering; - the capability to demonstrate the knowledge of the material with the answer to questions in all topics of the program; - The ability to describe results of advanced scientific findings in the open literature, and the presentation of a design project in a clear, scientific manner, describing the individual effort and understanding of the problem; - The capability of showing a clear conceptual understanding of the overall engineering implications of the material presented in the course.
Per informazioni scrivete a email@example.com.