The lessons of Complex Systems analysis and Control will deal with the following topics:
• Dynamic systems control
Classical and modern approach.
• Regulator synthesis
Controllability and observability. Canonical forms. Feedback control. Feedback observers. Eigenvalue separation theorem.
• Optimal control
The basic optimal control problem. Problems with terminal constraints. Minimum time control (bang-bang). Linear systems with Quadratic cost (LQ). Dynamic programming.
• State observer with uncertainty
Kalman filter.
• Data mining
Analysis and classification of big amounts of data and multivariate systems. Multiple regression models, Neural Networks, Principal Component Analysis, Factor Analysis, Cluster Analysis, Granger causality analysis.
Examples of application to real data will be performed by the student in a computer lab with the support of MATLAB, SIMULINK and Applic ation Toolbox.