Comparison of Controllers for a UAV Type Quadrotor: Feedback Control by Bessel´s Polynomials and LQR with Kalman Filter

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This paper presents the development of two different control techniques as an approach having to remove steady-state error present in the response of attitude of a mini unmanned aerial vehicle of four rotor model. The Bessel approximation allows the selection of the eigenvalues in function to a specified response time for a feedback pole placement controller and state estimator. On the other hand presents an optimal control technique combined with Kalman filter to estimate the state affected by perturbations in the system, both cases using the integral effect to eliminate the steady state error.

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40-48

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June 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] D. Lara, G. Romero, Robustness Margin for Attitude of a Four Rotor Mini- Rotorcraft: Case of Study, Mechatronics, Vol. 20, No. 1, February (2010).

DOI: 10.1016/j.mechatronics.2009.11.002

Google Scholar

[2] D. Lara, Modelization and Control of Mini Drones: Design of the Architecture Informatics, Université de Technologie de Compiègne, March (2007).

Google Scholar

[3] W. Colmenares. Control óptimo: El regulador linear cuadrático LQR. Universidad Simón Bolivar. (2006).

Google Scholar

[4] F. Szidarovszky, Linear Systems Theory. 2nd ed. CRC Press. (1997).

Google Scholar

[5] W. Rodríguez, R. Ibarra, G. Romero, D. Lara, C. Pegard and R. Abdelhamid, Robust Control Analysis Techinques Applied to a Mini Aircraft. Applied Mechanics and Materials. Vol. 394. pp.427-434, (2013).

DOI: 10.4028/www.scientific.net/amm.394.427

Google Scholar

[6] R.M. Murray. LQR Control. California Institute of Technology. (2006).

Google Scholar

[7] P. Zarchan. Fundamentals of Kalman Filtering: A practical Approach. 3rd ed. Progress in Astronomic and aeronautics volume 232. (2009).

Google Scholar

[8] G. Welch, G. Bishop, An introduction to the Kalman Filter, Department of computer science. University of North Carolina at Chapel Hill, (2006).

Google Scholar

[9] Karl J. Astrom. Computed Controlled Systems: Theory ad design. 3rd ed. Prentice Hall. (1997).

Google Scholar

[10] W. Rodríguez, R. Ibarra, G. Romero, D. Lara, Comparison of controllers for a UAV with integral effect and Kalman estimator: By Bessel polynomials and LQR. Applied Mechanics and Materials. Vol. 436. pp.54-60, (2013).

DOI: 10.4028/www.scientific.net/amm.436.54

Google Scholar

[11] Stevens BL., Lewis FL. Aircraft control and simulation. New Jersey, USA. John Wiley and sons, (2003).

Google Scholar