Zobrazeno 1 - 10
of 93
pro vyhledávání: '"Kayacan, Erkan"'
Autor:
Choo, Wonoo, Kayacan, Erkan
This paper develops a data-based moving horizon estimation (MHE) method for agile quadrotors. Accurate state estimation of the system is paramount for precise trajectory control for agile quadrotors; however, the high level of aerodynamic forces expe
Externí odkaz:
http://arxiv.org/abs/2307.16887
Autor:
Choo, Wonoo, Kayacan, Erkan
This paper develops computationally efficient data-driven model predictive control (MPC) for Agile quadrotor flight. Agile quadrotors in high-speed flights can experience high levels of aerodynamic effects. Modeling these turbulent aerodynamic effect
Externí odkaz:
http://arxiv.org/abs/2305.17254
Autor:
Bhandari, Vedant, Kayacan, Erkan
This paper demonstrates the applicability of the combination of concurrent learning as a tool for parameter estimation and non-parametric Gaussian Process for online disturbance learning. A control law is developed by using both techniques sequential
Externí odkaz:
http://arxiv.org/abs/2106.00910
Publikováno v:
Mechatronics, Volume 24, Issue 8, Pages 926-933, 2014
This paper addresses the trajectory tracking problem of an autonomous tractor-trailer system by using a fast distributed nonlinear model predictive control algorithm in combination with nonlinear moving horizon estimation for the state and parameter
Externí odkaz:
http://arxiv.org/abs/2104.09708
Publikováno v:
IEEE Transactions on Cybernetics, vol. 43, no. 1, pp. 170-179, Feb. 2013
As a model is only an abstraction of the real system, unmodeled dynamics, parameter variations, and disturbances can result in poor performance of a conventional controller based on this model. In such cases, a conventional controller cannot remain w
Externí odkaz:
http://arxiv.org/abs/2104.07160
Publikováno v:
Computers and Electronics in Agriculture, Volume 115, Pages 78-87, 2015
More efficient agricultural machinery is needed as agricultural areas become more limited and energy and labor costs increase. To increase their efficiency, trajectory tracking problem of an autonomous tractor, as an agricultural production machine,
Externí odkaz:
http://arxiv.org/abs/2104.06833
Publikováno v:
IEEE/ASME Transactions on Mechatronics, vol. 20, no. 1, pp. 287-298, Feb. 2015
Provision of some autonomous functions to an agricultural vehicle would lighten the job of the operator but in doing so, the accuracy should not be lost to still obtain an optimal yield. Autonomous navigation of an agricultural vehicle involves the c
Externí odkaz:
http://arxiv.org/abs/2104.04123
Publikováno v:
IEEE/ASME Transactions on Mechatronics, vol. 20, no. 1, pp. 447-456, Feb. 2015
This paper addresses the trajectory tracking problem of an autonomous tractor-trailer system by using a decentralized control approach. A fully decentralized model predictive controller is designed in which interactions between subsystems are neglect
Externí odkaz:
http://arxiv.org/abs/2104.02063
Publikováno v:
IEEE Transactions on Control Systems Technology, Volume: 23, Issue: 1, Jan. 2015
One of the most critical tasks in tractor operation is the accurate steering during field operations, e.g., accurate trajectory following during mechanical weeding or spraying, to avoid damaging the crop or planting when there is no crop yet. To auto
Externí odkaz:
http://arxiv.org/abs/2104.01728
Publikováno v:
IEEE Transactions on Industrial Electronics, vol. 62, no. 3, pp. 1716-1724, March 2015
In order to achieve faster and more robust convergence (especially under noisy working environments), a sliding mode theory-based learning algorithm has been proposed to tune both the premise and consequent parts of type-2 fuzzy neural networks in th
Externí odkaz:
http://arxiv.org/abs/2104.01713