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A low-cost hardware-in-the-loop-simulation testbed of quadrotor UAV and implementation of nonlinear control schemes

Published online by Cambridge University Press:  17 August 2015

Bin Xian*
Affiliation:
Institute of Robotics and Autonomous System, the Tianjin Key Laboratory of Process Measurement and Control, Schoool of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, P. R. China. E-mail: [email protected], [email protected], [email protected]
Bo Zhao
Affiliation:
Institute of Robotics and Autonomous System, the Tianjin Key Laboratory of Process Measurement and Control, Schoool of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, P. R. China. E-mail: [email protected], [email protected], [email protected]
Yao Zhang
Affiliation:
Institute of Robotics and Autonomous System, the Tianjin Key Laboratory of Process Measurement and Control, Schoool of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, P. R. China. E-mail: [email protected], [email protected], [email protected]
Xu Zhang
Affiliation:
Institute of Robotics and Autonomous System, the Tianjin Key Laboratory of Process Measurement and Control, Schoool of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, P. R. China. E-mail: [email protected], [email protected], [email protected]
*
*Corresponding author. E-mail: [email protected]

Summary

Designing and testing flight control algorithms for quadrotor UAVs (unmanned aerial vehicles) is not an easy task due to the risk of possible danger and damage during the practical flight. In order to improve the safety and efficiency of the flight control implementation, a low-cost real-time HILS (hardware-in-the-loop simulation) testbed for quadrotor UAVs is developed in this paper. To realize the HILS testbed, a miniature quadrotor is used as the main body, equipped with a micro AHRS (attitude heading reference system) unit and a self-build DSP (digital signal processor) board. The HILS is implemented by using xPC target. A compact PC/104 computer is utilized as the target computer, and a laptop PC is employed as the host computer. A desktop PC is used as flight visualization computer which runs FlightGear and Google Earth to show visual data, such as orientation and flight path of the quadrotor UAV. This testbed can be utilized for simulating various flight control algorithms, without losing safeness and reliableness. To demonstrate the effectiveness of the proposed testbed, a new nonlinear adaptive sliding mode based stabilization control algorithm is developed and verified on the HILS testbed.

Type
Articles
Copyright
Copyright © Cambridge University Press 2015 

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References

1. Sun, X. Y., Fang, Y. C. and Sun, N., “Backstepping-based adaptive attitude and height control of a small-scale unmanned helicopter,” Control Theory Appl. 29 (2), 381388 (2012).Google Scholar
2. Sun, N., Fang, Y. and Zhang, X., “Energy coupling output feedback control of 4-DOF underactuated cranes with saturated inputs,” Automatica 49 (2), 13181325 (2013).CrossRefGoogle Scholar
3. Diao, C., Xian, B., Zhao, B., Zhang, X. and Liu, S., “Nonlinear robust output feedback tracking control of a quadrotor UAV using quaternion representation,” Nonlinear Dyn. 79 (2), 27352752 (2015).Google Scholar
4. Palmintier, B., Lundstrom, B., Chakraborty, S., Williams, T., Schneider, K. and Chassin, D., “A power hardware-in-the-loop platform with remote distribution circuit cosimulation,” IEEE Trans. Ind. Electron. 62 (2), 22362245 (Apr. 2015).CrossRefGoogle Scholar
5. Gans, N., Dixon, W., Lind, R. and Kurdila, A., “A hardware in the loop simulation platform for vision-based control of unmanned air vehicles,” Mechatronics 19 (2), 10431056 (2009).CrossRefGoogle Scholar
6. Bittar, A. and de Oliveira, N. M., “Central processing unit for an autopilot: Description and hardware-in-the-loop simulation,” J. Intell. Robot. Syst. 70 (1–4), 557574 (2013).CrossRefGoogle Scholar
7. Jung, D., Ratti, J. and Tsiotras, P., “Real-Time Implementation and Validation of a New Hierarchical Path Planning Scheme of UAVs Via Hardware-in-the-Loop Simulation,” In: Unmanned Aircraft Systems (Springer, 2009) pp. 163181.CrossRefGoogle Scholar
8. Cai, G., Chen, B. M., Lee, T. H. and Dong, M., “Design and implementation of a hardware-in-the-loop simulation system for small-scale UAV helicopters,” Mechatronics 19 (2), 10571066 (2009).CrossRefGoogle Scholar
9. Ates, S., Bayezit, I. and Inalhan, G., “Design and Hardware-in-the-Loop Integration of a UAV Microavionics System in a Manned–Unmanned Joint Airspace Flight Network Simulator,” In: Unmanned Aircraft Systems (Springer, 2009) pp. 359386.CrossRefGoogle Scholar
10. Lee, T., “Robust adaptive attitude tracking on so(3) with an application to a quadrotor uav,” IEEE Trans. Control Syst. Technol. 21 (2), 19241930 (2013).Google Scholar
11. Oh, H., Won, D.-Y., Huh, S.-S., Shim, D. H. and Tahk, M.-J., “Experimental framework for controller design of a rotorcraft unmanned aerial vehicle using multi-camera system,” Int. J. Aeronaut. Space Sci. 11 (2), 6979 (2010).CrossRefGoogle Scholar
12. Bayrakceken, M. and Arisoy, A., “An educational setup for nonlinear control systems: Enhancing the motivation and learning in a targeted curriculum by experimental practices,” IEEE Control Syst. Mag. 33 (2), 6481 (2013).Google Scholar
13. Tayebi, A. and McGilvray, S., “Attitude stabilization of a VTOL quadrotor aircraft,” IEEE Trans. Control Syst. Technol. 14 (2), 562571 (2006).CrossRefGoogle Scholar
14. Czyba, R., “Design of Attitude Control System for an UAV Type-Quadrotor Based on Dynamic Contraction Method,” IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Singapore (Jul. 14–17, 2009) pp. 644–649.CrossRefGoogle Scholar
15. Bouabdallah, S., Murrieri, P. and Siegwart, R., “Towards autonomous indoor micro VTOL,” Auton. Robots 18 (2), 171183 (2005).CrossRefGoogle Scholar
18. XAircraft Inc. Available at: http://www.xaircraft.com/aircraft/.Google Scholar
19. Liu, H., Li, D., Kim, J. and Zhong, Y., “Real-time implementation of decoupled controllers for multirotor aircrafts,” J. Intell. Robot. Syst. 73 (1–4), 197207 (2014).CrossRefGoogle Scholar
20. Craig, J. J., Introduction to Robotics (Prentice Hall, 2005).Google Scholar
21. Zeng, W., Xian, B., Diao, C., Yin, Q., Li, H. and Yang, Y., “Nonlinear Adaptive Regulation Control of a Quadrotor Unmanned Aerial Vehicle,” Proceedings of the 2011 IEEE International Conference on Control Applications (CCA), Denver, CO (Sept. 28–30, 2011) pp. 133–138.CrossRefGoogle Scholar
22. Li, H.T., Xian, B., Diao, C., Yang, K. Y. and Yin, Q., 2011 Youth Academic Conference of Chinese Association of Automation, Nanjin, China (May 20–22, 2011) pp. 273–280.Google Scholar
23. Madani, T. and Benallegue, A., “Backstepping Sliding Mode Control Applied to a Miniature Quadrotor Flying Robot,” Proceedings of the 2006 32nd Annual Conference on IEEE Industrial Electronics, Paris, France (Nov. 6–10, 2006) pp. 700–705.CrossRefGoogle Scholar
24. Xu, R. and Özgüner, Ü., “Sliding mode control of a class of underactuated systems,” Automatica 44 (1), 233241 (2008).CrossRefGoogle Scholar
25. Zhang, X., Dawson, D., De, M. Queiroz and Xian, B., “Adaptive Control for a Class of MIMO Nonlinear Systems with Non-Symmetric Input Matrix,” Proceedings of the 2004 IEEE International Conference on Control Applications, vol. 2 (Sept. 2–4, 2004) pp. 1324–1329.Google Scholar
26. Khalil, H. K. and Grizzle, J., Nonlinear Systems (Prentice hall Upper Saddle River, 2002).Google Scholar
27. Slotine, J.-J. E. and Li, W. P., Applied Nonlinear Control (Prentice Hall, New Jersey, 1991).Google Scholar
28. Dixon, W. E., Behal, A., Dawson, D. M. and Nagarkatti, S. P., Nonlinear Control of Engineering Systems (Birkhauser Boston, 2002).Google Scholar
29. Zhao, B., Xian, B., Zhang, Y. and Zhang, X., “Nonlinear robust adaptive tracking control of a quadrotor UAV via immersion and invariance methodology,” IEEE Trans. Ind. Electron. 62 (2), 28912902 (2015).CrossRefGoogle Scholar