Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301) 2002
DOI: 10.1109/acc.2002.1024508
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Applied receding horizon control of the Caltech Ducted Fan

Abstract: This paper details the application of a constrained receding horizon control strategy t o an indoor vectoredthrust flight experiment known as the Caltech Ducted Fan. The strategy is used to stabilize the experiment about one operating point, and step response and disturbance rejection are examined with different configurations and in comparison t o a gain-scheduled LQR controller. Issues related to non-zero computation times, choice of horizon length and terminal cost are discussed. IntroductionIn receding hor… Show more

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Cited by 45 publications
(26 citation statements)
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References 7 publications
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“…By our implementation, at initial time the internal clock of each agent has to be synchronized using clock synchronization. Furthermore, the sampling time is calculated based on the average past results [17]. Thus sampling time is varying.…”
Section: Nonlinear Model Predictive Controlmentioning
confidence: 99%
“…By our implementation, at initial time the internal clock of each agent has to be synchronized using clock synchronization. Furthermore, the sampling time is calculated based on the average past results [17]. Thus sampling time is varying.…”
Section: Nonlinear Model Predictive Controlmentioning
confidence: 99%
“…The matrix A p propagates the state forward by a short time period to account for the computation delays between the measurement of x and the execution of the first plan step [11]. The requirement for y to start at 1 and end at 0 requires that the states pass through the target region at some step of the plan, thereby completing the mission.…”
Section: Controller Formulationmentioning
confidence: 99%
“…However, application to systems with faster dynamics, such as those found in the field of aerospace, has been impractical until recently, with the on-going improvements in computation speed. Recent hardware work in this field includes the online use of NTG nonlinear optimization for control of an aerodynamic system [11,12] and of a formation of highly-nonlinear vehicles [13,14].…”
Section: Introductionmentioning
confidence: 99%
“…The real-time trajectory generation framework, and the corresponding software, was developed by Milam and co-workers and has appeared in [21,23,25]. The implementation of model predictive control given in this chapter is based on the work of Dunbar, Milam, and Franz [8,10].…”
Section: Introductionmentioning
confidence: 99%