%0 Journal Article
%T Hamiltonian Servo: Control and Estimation of a Large Team of Autonomous Robotic Vehicles
%A Vladimir Ivancevic
%A Peyam Pourbeik
%J Intelligent Control and Automation
%P 175-197
%@ 2153-0661
%D 2017
%I Scientific Research Publishing
%R 10.4236/ica.2017.84014
%X <div style=\"text-align:justify;\">
	This paper proposes a novel <i>Hamiltonian servo system</i>, a combined modeling framework for control and estimation of a large team/fleet of autonomous robotic vehicles. The Hamiltonian servo framework represents high-dimensional, nonlinear and non-Gaussian generalization of the classical <i>Kalman servo system</i>. After defining the Kalman servo as a motivation, we define the affine Hamiltonian neural network for adaptive nonlinear control of a team of UGVs in continuous time. We then define a high-dimensional Bayesian particle filter for estimation of a team of UGVs in discrete time. Finally, we formulate a hybrid Hamiltonian servo system by combining the continuous-time control and the discrete-time estimation into a coherent framework that works like a predictor-corrector system.
</div>
%K Team of UGVs
%K Kalman Servo
%K Hamiltonian Control
%K Bayesian Estimation
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=81090