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Nonlinear Control Strategies for an Autonomous Wing-In-Ground-Effect Vehicle.
Patria, Davide; Rossi, Claudio; Fernandez, Ramon A Suarez; Dominguez, Sergio.
Affiliation
  • Patria D; Politecnico Di Torino, 10129 Torino, Italy.
  • Rossi C; Centre for Automation and Robotics UPM-CSIC, Universidad Politécnica de Madrid, 28006 Madrid, Spain.
  • Fernandez RAS; Centre for Automation and Robotics UPM-CSIC, Universidad Politécnica de Madrid, 28006 Madrid, Spain.
  • Dominguez S; Centre for Automation and Robotics UPM-CSIC, Universidad Politécnica de Madrid, 28006 Madrid, Spain.
Sensors (Basel) ; 21(12)2021 Jun 18.
Article in En | MEDLINE | ID: mdl-34207282
ABSTRACT
Autonomous vehicles are nowadays one of the most important technologies that will be incorporated to every day life in the next few years. One of the most promising kind of vehicles in terms of efficiency and sustainability are those known as Wing-in-Ground crafts, or WIG crafts, a family of vehicles that seize the proximity of ground to achieve a flight with low drag and high lift. However, this kind of crafts lacks of a sound theory of flight that can lead to robust control solutions that guarantees safe autonomous operation in all the cruising phases.In this paper we address the problem of controlling a WIG craft in different scenarios and using different control strategies in order to compare their performance. The tested scenarios include obstacle avoidance by fly over and recovering from a random disturbance in vehicle attitude. MPC (Model Predictive Control) is tested on the complete nonlinear model, while PID, used as baseline controller, LQR (Linear Quadratic Regulator) and adaptive LQR are tested on top of a partial feedback linearization. Results show that LQR has got the best overall performance, although it is seen that different design specifications could lead to the selection of one controller or another.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Nonlinear Dynamics Type of study: Prognostic_studies Language: En Journal: Sensors (Basel) Year: 2021 Document type: Article Affiliation country: Italy

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Nonlinear Dynamics Type of study: Prognostic_studies Language: En Journal: Sensors (Basel) Year: 2021 Document type: Article Affiliation country: Italy