Title:
Model predictive control (MPC) algorithm for tip-jet reaction drive systems

dc.contributor.advisor Mavris, Dimitri N.
dc.contributor.author Kestner, Brian en_US
dc.contributor.committeeMember German, Brian J.
dc.contributor.committeeMember Healy, Tim
dc.contributor.committeeMember Rosson, Randy
dc.contributor.committeeMember Tai, Jimmy C. M.
dc.contributor.department Aerospace Engineering en_US
dc.date.accessioned 2010-01-29T19:54:18Z
dc.date.available 2010-01-29T19:54:18Z
dc.date.issued 2009-11-16 en_US
dc.description.abstract Modern technologies coupled with advanced research have allowed model predictive control (MPC) to be applied to new and often experimental systems. The purpose of this research is to develop a model predictive control algorithm for tip-jet reaction drive system. This system's faster dynamics require an extremely short sampling rate, on the order of 20ms, and its slower dynamics require a longer prediction horizon. This coupled with the fact that the tip-jet reaction drive system has multiple control inputs makes the integration of an online MPC algorithm challenging. In order to apply a model predictive control to the system in question, an algorithm is proposed that combines multiplexed inputs and a feasible cooperative MPC algorithm. In the proposed algorithm, it is hypothesized that the computational burden will be reduced from approximately Hp(Nu + Nx)3 to pHp(Nx+1)3 while maintaining control performance similar to that of a centralized MPC algorithm. To capture the performance capability of the proposed controller, a comparison its performance to that of a multivariable proportional-integral (PI) controller and a centralized MPC is executed. The sensitivity of the proposed MPC to various design variables is also explored. In terms of bandwidth, interactions, and disturbance rejection, the proposed MPC was very similar to that of a centralized MPC or PI controller. Additionally in regards to sensitivity to modeling error, there is not a noticeable difference between the two MPC controllers. Although the constraints are handled adequately for the proposed controller, adjustments can be made in the design and sizing process to improve the constraint handling, so that it is more comparable to that of the centralized MPC. Given these observations, the hypothesis of the dissertation has been confirmed. The proposed MPC does in fact reduce computational burden while maintaining close to centralized MPC performance. en_US
dc.description.degree Ph.D. en_US
dc.identifier.uri http://hdl.handle.net/1853/31802
dc.publisher Georgia Institute of Technology en_US
dc.subject Model predictive control reaction drive en_US
dc.subject.lcsh Predictive control
dc.subject.lcsh Automatic control
dc.subject.lcsh Algorithms
dc.title Model predictive control (MPC) algorithm for tip-jet reaction drive systems en_US
dc.type Text
dc.type.genre Dissertation
dspace.entity.type Publication
local.contributor.advisor Mavris, Dimitri N.
local.contributor.corporatename Daniel Guggenheim School of Aerospace Engineering
local.contributor.corporatename Aerospace Systems Design Laboratory (ASDL)
local.contributor.corporatename College of Engineering
local.relation.ispartofseries Doctor of Philosophy with a Major in Aerospace Engineering
relation.isAdvisorOfPublication d355c865-c3df-4bfe-8328-24541ea04f62
relation.isOrgUnitOfPublication a348b767-ea7e-4789-af1f-1f1d5925fb65
relation.isOrgUnitOfPublication a8736075-ffb0-4c28-aa40-2160181ead8c
relation.isOrgUnitOfPublication 7c022d60-21d5-497c-b552-95e489a06569
relation.isSeriesOfPublication f6a932db-1cde-43b5-bcab-bf573da55ed6
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
kestner_brian_k_200912_phd.pdf
Size:
3.7 MB
Format:
Adobe Portable Document Format
Description: