KNODE-MPC: A Knowledge-Based Data-Driven Predictive Control Framework for Aerial Robots

In this letter, we consider the problem of deriving and incorporating accurate dynamic models for model predictive control (MPC) with an application to quadrotor control. MPC relies on precise dynamic models to achieve the desired closed-loop performance. However, the presence of uncertainties in co...

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Veröffentlicht in:	IEEE robotics and automation letters Jg. 7; H. 2; S. 2819 - 2826
Hauptverfasser:	Chee, Kong Yao, Jiahao, Tom Z., Hsieh, M. Ani
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.04.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Aerodynamics Complex systems Computational modeling Data models Differential equations Dynamic models First principles Gaussian process Machine learning for robot control Mathematical models model learning for control model predictive control Neural networks Ordinary differential equations Predictive control Predictive models Robot control System dynamics Uncertainty
ISSN:	2377-3766, 2377-3766
Online-Zugang:	Volltext
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