Open AccessAutonomous Control Agents for Adaptive MAV Mission Profiles
Author(s) -
Chimpalthradi R. Ashokkumar
Publication year - 2013
Publication title -
international journal of micro air vehicles
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 21
eISSN - 1756-8307
pISSN - 1756-8293
DOI - 10.1260/1756-8293.5.1.1
Subject(s) - trajectory , controller (irrigation) , a priori and a posteriori , kalman filter , control theory (sociology) , computer science , adaptive control , extended kalman filter , control engineering , track (disk drive) , robot , feature (linguistics) , engineering , control (management) , artificial intelligence , philosophy , linguistics , physics , epistemology , astronomy , agronomy , biology , operating system
When a mission profile of an unmanned micro air vehicle is known a priori, one of the strategies adopted in autonomous control is to first generate a compatible trajectory in off-line and then implement a controller to track the trajectory. However, in decision rich intelligent aerial robots and in 6DOF operations of unmanned aerial vehicles, the mission profiles are usually known during an operation. Hence the trajectories are instantaneously inferred. Here an adaptive controller with capabilities to track these trajectories is required. In this paper, it is shown that an extended Kalman filter is an excellent tool to design such a controller which accepts the trajectory generation module as an input and then reconstructs its trajectories. To illustrate this feature, a 3DOF micro air vehicle in pitch plane is considered and an adaptive controller (referred as autonomous control agent) using an extended Kalman filter is applied to infer typical adaptive mission profiles.