Model predictive control with application to real-time hardware and guided parafoil

Model Predictive Control (MPC) is a control strategy that is suitable for optimizing the performance of constrained systems. Constraints are present in all control systems due to the physical and environmental limits on plant operation. Through a systematical handling of constraints, MPC can improve the performance of a system by allowing it to safely operate near constraint boundaries. This thesis describes the mathematical background of MPC and develops two controllers. One controller is based on a linear model of the plant and is successfully applied to a real-time 3 degrees-of-freedom helicopter system, used to simulate helicopter-like motions in a laboratory setting. This system has a number of significant state and control constraints. The second controller uses a nonlinear model and is applied to a guided parafoil to identify the advantage of using a Doppler wind sensor. A method for reducing the computational load is also introduced that is applicable to both controllers.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2004

Author dc:creator

• Alaniz, Abran, 1980-

Advisor dc:contributor.advisor

• David W. Carter.

• Aeronautics and Astronautics.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/17753

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/17753