Accession Number : ADA572108


Title :   On-board Model Predictive Control of a Quadrotor Helicopter: Design, Implementation, and Experiments


Corporate Author : CALIFORNIA UNIV BERKELEY DEPT OF COMPUTER SCIENCES


Personal Author(s) : Bouffard, Patrick


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a572108.pdf


Report Date : 13 Dec 2012


Pagination or Media Count : 82


Abstract : This report describes work in applying model predictive control (MPC) techniques to the control of quadrotor helicopters, a type of micro aerial vehicle (MAV) platform that has gained great popularity in recent years both in research and commercial/military settings. MPC is a form of optimal control which is attractive in part because it allows engineering requirements to be addressed directly in the design of the controller in terms of costs to be minimized and constraints to be satisfied in an optimization problem. Furthermore, for many engineering problems of interest, the optimization to be performed is convex, meaning that a global optimum can be efficiently computed. MPC first found broad early application in the process industry, where the typically longer time scales were compatible with the time necessary to solve the optimization problem. More recently with both the exponential increase in available computing power and the development of more efficient solution techniques, MPC has become an option for control of systems with faster dynamics, such as quadrotors.


Descriptors :   *ENGINEERING , *HELICOPTERS , AIRCRAFT , COMMERCE , CONTROL , DYNAMICS , EFFICIENCY , GLOBAL , MODELS , ONBOARD , OPTIMIZATION , PLATFORMS , POWER , PREDICTIONS , REQUIREMENTS , SCALE , SOLUTIONS(GENERAL) , TIME


Subject Categories : Helicopters


Distribution Statement : APPROVED FOR PUBLIC RELEASE