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Docente
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VENDITTELLI MARILENA
(programma)
Il corso è organizzato in 4 moduli da 3 crediti. Ciascun modulo ha il suo programma specifico disponibile all'inizio del ciclo di lezioni.
Una descrizione dettagliata e sempre aggiornata dei programmi è disponibile alla pagina: http://www.diag.uniroma1.it/vendittelli/EIR/
Riportiamo qui una sintesi:
Modulo 1: Modeling and control of multi-rotor UAVs (Marilena Vendittelli)
- Introduction to the course and aerial vehicles modeling
- Quadrotor modeling
- Control based on linear approximation
- Backstepping-based control
- Control based on dynamic feedback linearization
- Geometric control on SE(3)
- State estimation
- Motion planning
- Controllers comparison
- Fault-diagnosis and fault tolerant control - part I: introduction
- Fault-diagnosis and fault tolerant control - part II: application to quadrotors
Modulo 2: Underactuated Robots (Leonardo Lanari, Giuseppe Oriolo)
1. Introduction
Motivation. Definition of underactuated system (generalized coordinates vs degrees of freedom). Examples of underactuated robots.
2. Modeling and Properties
Eulero-Lagrange modeling (classic and alternate). State-space form. Control problems of interest. Controllabiity (STLA, STLC, natural controllability). Comparison with fully actuated robots. Integrability conditions for passive dynamics. Equilibrium points and linear controllability.
3. Case Studies: Acrobot and Pendubot
Modeling. Approximate linearization at equilibria. Linear controllability. Balancing. Partial feedback linearization. Swing-up (1) via analysis of the zero dynamics (2) via energy pumping.
4. Zero dynamics in underactuated systems
Normal form and zero dynamics. Importance of the zero dynamics in control. Zero-dynamics in linear and nonlinear underactuated systems. The homoclinic orbit.
5. Passivity
Definition and physical interpretation. Linear and nonlinear mechanical systems examples. Dissipativity in state space representations. Feedback equivalence to a passive system. Output stabilization of passive systems
6. Energy-based control of underactuated systems
The convey-crane and reaction-wheel cases.
7. Optimization methods for Planning and Control
Introduction to Dynamic Programming. Hamilton-Jacobi-Bellman equation. Derivation of the Linear Quadratic Regulator
Linear-Time-Varying LQR. Trajectory optimization with Iterative LQR. Constrained optimization. Model Predictive Control (Linear, LTV and Nonlinear). LQR-trees.
Modulo 3: Locomotion and haptic interfaces for VR exploration (Alessandro De Luca)
- General introduction to haptic and locomotion interfaces with several illustrative examples.
- Two specific hardware devices: the Geomatic Touch haptic interface; the Cyberith Virtualizer locomotion interface (with the Oculus Rift HMD). Possible applications of these interfaces.
- Design, construction, actuation, sensing, modelling, and system issues for two locomotion platforms for VR exploration, developed within the CyberWalk project: the CyberCarpet (ball-array) and the CyberWalk platform (2D, omni-directional).
- Control design and experimental validation for the CyberCarpet. Control design and experimental validation for a 1D treadmill.
- Control design, experimental validation, and perceptual evaluation for the 2D CyberWalk platform.
Modulo 4: Control of Multi-Robot Systems (Andrea Cristofaro)
- Examples of applications of multi-robot systems.
- Centralized vs. decentralized architectures.
- Elements of graph theory.
- Connectivity and Consensus; Passivity and Lyapunov stability; Interconnection of mechanical systems.
- Application to multi-UAV systems: Formation control with time-varying topology; Formation control with connectivity maintenance; Steady-state behaviors;
- Overview of other multi robot problems.
 Materiale didattico fornito dai docenti.
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