PPT-Nonlinear Model Reduction for Flexible Aircraft Control Des

Author : sherrill-nordquist | Published Date : 2016-07-30

A Da Ronch K J Badcock University of L iverpool Liverpool UK Y Wang A Wynn and R Palacios Imperial College London UK AIAA Paper 2012 4404 Minneapolis 13 August

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Nonlinear Model Reduction for Flexible Aircraft Control Des: Transcript

A Da Ronch K J Badcock University of L iverpool Liverpool UK Y Wang A Wynn and R Palacios Imperial College London UK AIAA Paper 2012 4404 Minneapolis 13 August 2012. Nonlinear Model Problem Let us consider the nonlinear model problem 87228711 f in 8486 1a 0 on 8486 1b where is a given positive function depending on the unknown solution As usual is a given source function which we for simplicity assume not to Di64256erentiating 8706S 8706f Setting the partial derivatives to 0 produces estimating equations for the regression coe64259cients Because these equations are in general nonlinear they require solution by numerical optimization As in a linear model The o64260ine phase of the method builds the local red ucedorder bases using an unsupervised learning algorithm In the online phase of the method the choice of the local basis is based on the current state of the system Inexp ensive rankone updates . . . . N.D.Tantaroudas. . . K.J.Badcock,A.Da. . Ronch. University . Framework in . Py. . A. . Da. . Ronch. University of. L. iverpool. , . UK. Liverpool, . 16. March 2012. Target. . Nonlinear models . for flexible aircraft (hierarchy). Nonlinear . model reduction. for . Liquid-Rocket . Transverse Combustion Instability. by W. A. Sirignano and P. Popov. Mechanical and Aerospace Engineering. University of California, Irvine. Supported by Air Force Office of Scientific Research . Part 2. Pieter . Abbeel. UC Berkeley EECS. TexPoint fonts used in EMF. . Read the TexPoint manual before you delete this box.: . A. A. A. A. A. A. A. A. A. A. A. A. From linear to nonlinear. Model-predictive control (MPC). A. . Da . Ronch, N.D. . Tantaroudas. , . S.Timme. and K.J. Badcock. University of Liverpool, U.K.. AIAA Paper 2013-. 1942. Boston, MA, 08 April 2013. email:. K.J.Badcock@liverpool.ac.uk. Shape Optimisation. Final report. Ville-Pietari Louhiala . Status of the project . Main problem of the project is solved. The statistics of the stochastic nonlinear combustion engine model in question can be calculated with Extended . RMG Study Group Presentation. Kehang Han. Apr. 28, 2015. Outline. Why we need model reduction. Two levels of model reduction. Most recent methods. Personal opinion. High CPU time . in predictive . combustion. Nancy Leveson. MIT. Outline. Accident Causation in Complex Systems: STAMP. New Analysis Methods. Hazard Analysis. Accident Analysis. Security Analysis. Does it Work? Evaluations. Why We Need a New Approach to Safety. Haiqing. . Guo. 1. , Marcos Vanella. 2. , Sean Crowley. 1. , . Paul . Scrofani. 1. , . Richard E. . Lyon. 1. 1. . William J. Hughes Technical Center, FAA, Atlantic City, NJ. 2. NIST, Gaithersburg, NJ. BADA Model Overview BADA is based on a mass-varying, kinetic approach to aircraft performance modeling [3]. It is structured in three parts: Aircraft Performance Model (APM), Airline Procedure Model ( 2DEVELOPMENT OF SHIP MANEUVERING CONTROL SYSTEMWITH ONLINE NONLINEAR OPTIMAL CONTROLINTRODUCTIONMOTIVATIONREVIEW OF THE OPTIMAL CONTROL PROBLEMOPTIMAL THRUST ALLOCATIONEXPERIMENTAL RESULTSROUTE TRACKI

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