Design of a continuous time model predictive controller for an F16 jet

C.H. Dai, H. Nijmeijer (Editor), Liuping Wang (Editor)

Research output: Book/ReportReportAcademic

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Abstract

Continuous time model predictive control (CMPC) is a control algorithm similar to discrete time model predictive control in that it uses a quadratic cost function to find the optimal control inputs within given constraints. Inputs which give the lowest cost function are the optimal control inputs. The benefit of CMPC over its discrete time counterpart is the use of a continuous time linear model to predict future system behaviour at each time sample. The control inputs are modelled with orthonormal basis functions. This simplifies the calculation of the optimal control inputs in continuous time. The cost function uses an exponentially data weighting strategy to improve the stability and tracking performance of the controller. Simulations with a non-linear F16 jet aircraft MIMO model show that CMPC can control the attitude of the aircraft with good performance under certain conditions.
Original languageEnglish
Place of PublicationEindhoven
PublisherEindhoven University of Technology
Publication statusPublished - 2013

Publication series

NameD&C
Volume2013.027

Bibliographical note

Traineeship report. - DC 2013.027

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