logo SBA

ETD

Archivio digitale delle tesi discusse presso l’Università di Pisa

Tesi etd-03192016-152856


Tipo di tesi
Tesi di laurea magistrale
Autore
BRANDIMARTI, ALESSANDRO
URN
etd-03192016-152856
Titolo
A Novel Nonlinear Model Predictive Control for coordinating a UAV Swarm
Dipartimento
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
INGEGNERIA ROBOTICA E DELL'AUTOMAZIONE
Relatori
relatore Prof. Innocenti, Mario
Parole chiave
  • coordinated control
  • nonlinear model predictive control
  • particle swarm optimization
  • uav swarm
Data inizio appello
28/04/2016
Consultabilità
Non consultabile
Data di rilascio
28/04/2086
Riassunto
This thesis project addresses the problem of coordinating the motion of a multiagents system for a real time application. The case study is a Unmanned Aerial Vehicles (UAV) swarm moving on a not completely known map with pop-up obstacles to be avoided. The main concept of coordination is discussed, providing a general procedure to describe the environment and mission goals through a proper optimization problem. Relative distances are used to describe the tasks, as in a standard formation control. The usage of a minimal task description permits the swarm to have more degree of freedom to achieve the optimal configuration. Dealing with not completely known environments, where the robot has to react to sensory data as quickly as possible, a real time algorithm is necessary. For this reason, the controller design needs to properly face the computational burden and environments variations issues. Furthermore, the algorithm should be distributed.
The report presents a novel approach that allows to easily deal with nonlinear models and very complex, time variant cost function. A distributed Non Linear Model Predictive Control is implemented and a Particle Swarm Optimization is used to solve the optimization problem.
File