Autonomous Autorotation of Unmanned Rotorcraft using Nonlinear Model Predictive Control
| Autor: | Kimon P. Valavanis, Les A. Piegl, Konstantinos Dalamagkidis |
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| Rok vydání: | 2009 |
| Předmět: |
Engineering
business.industry Rotor (electric) Mechanical Engineering Hinge Control reconfiguration Control engineering Trajectory optimization Industrial and Manufacturing Engineering law.invention Power (physics) Model predictive control Recurrent neural network Autorotation Artificial Intelligence Control and Systems Engineering law Control theory Electrical and Electronic Engineering business Software |
| Zdroj: | Journal of Intelligent and Robotic Systems. 57:351-369 |
| ISSN: | 1573-0409 0921-0296 |
| DOI: | 10.1007/s10846-009-9366-2 |
| Popis: | Safe operations of unmanned rotorcraft hinge on successfully accommodating failures during flight, either via control reconfiguration or by terminating flight early in a controlled manner. This paper focuses on autorotation, a common maneuver used to bring helicopters safely to the ground even in the case of loss of power to the main rotor. A novel nonlinear model predictive controller augmented with a recurrent neural network is presented that is capable of performing an autonomous autorotation. Main advantages of the proposed approach are on-line, real-time trajectory optimization and reduced hardware requirements. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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