Design and experimentation of a self-tuning PID control applied to the 3DOF helicopter

Open access

Abstract

The paper presents design and experimental validation of a stable self-tuning PID controller for three degrees of freedom (3-DOF) helicopter. At first, it is proposed a self-tuned proportional-integral-derivative (PID) controller for a class of uncertain second order multiinput multi-output nonlinear dynamic systems to which the 3-DOF helicopter dynamic model belongs. Within this scheme, the PID controller is employed to approximate unknown ideal controller that can achieve control objectives. PID controller gains are the adjustable parameters and they are updated online with a stable adaptation mechanism designed to minimize the error between the unknown ideal controller and the used by PID controller. The stability analysis of the closed-loop system is performed using Lyapunov approach. It is proven that all signals in the closed-loop system are uniformly ultimately bounded. The proposed approach can be regarded as a simple and effective model-free control since the mathematical model of the system is assumed unknown. Experimental results are presented to verify the effectiveness of the proposed controller.

References
  • [1] J. APKARIAN: 3D Helicopter experiment manual. Canada: Quanser Consulting, 1998.

  • [2] Z. LIU, Z. CHOUKRI EL HAJ and H. SHI: Control strategy design based on fuzzy logic and LQR for 3-DOF helicopter model. In: Proc. Int. Conf. on Intelligent Controland Information Processing, Dalian, China, (2010), 262-266.

  • [3] L. HAO, Y. YAO, L. GENG and Z. YISHENG: Robust LQR attitude control of 3DOF helicopter. In: Proc. of the 29th Chinese Control Conference, Beijing, China, (2010), 529-534.

  • [4] T. KIEFER, K. GRAICHEN and A. KUGI: Trajectory tracking of a 3DOF laboratory helicopter under input and state constraints. IEEE Trans. on Control SystemsTechnology, 18(4), (2010), 944-952.

  • [5] A.T. KUTAY, A.J. CALISE, M. IDAN and N. HOVAKIMYAN: Experimental results on adaptive output feedback control using a laboratory model helicopter. IEEETrans. on Control Systems Technology, 13(2), (2005), 196-202.

  • [6] F. ZHOU, D. LI and P. XIA: Research of fuzzy control for elevation attitude of 3-DOF helicopter. In Proc. 2009 Int. Conf. on Intelligent Human-Machine Systemsand Cybernetics, Hangzhou, Zhejiang, China, (2009), 367-370.

  • [7] Y. YU and Y. ZHONG: Robust attitude control of a 3dof helicopter with multioperation points. J. of Systems Science and Complexity, 22(2), (2009), 207-219.

  • [8] J. WITT, S. BOONTO and H. WERNER: Approximate model predictive control of a 3-DOF helicopter. In Proc. 46th IEEE Conf. on Decision and Control, New Orleans, LA, USA, (2007), 4501-4506.

  • [9] W. XIUYAN, Z. CHANGLI and L. ZONGSHUAI: Robust H-infinity tracing control of 3-DOF helicopter model. In Proc 2010 Int. Conf. on Measuring Technology andMechatronics Automation, Changsha City, China, (2010), 279-282.

  • [10] F.G. MARQUES DE CARVALHO and E.M. HEMERLY: Adaptive elevation control of a three degrees-of-freedom model helicopter using neural networks by state and output feedback. ABCM Symp. Series in Mechatronics, 3 (2008), 106-113.

  • [11] M. ISHITOBI, M. NISHI and K. NAKASAKI: Nonlinear adaptive model following control for a 3-DOF tandem-rotor model helicopter. Control Engineering Practice, 18(8), 2010, 936-943.

  • [12] H. ZHU, L. LI, Y. ZHAO, Y. GUO and Y. YANG: CAS algorithm-based optimum design of PID controller in AVR System. Chaos, Solitons and Fractals, 42(2), (2009), 792-800.

  • [13] V. BOBÁL: Technical note self-tuning Ziegler-Nichols PID controller. Int. J. ofAdaptive Control and Signal Processing, 9(2), (1995), 213-226.

  • [14] R. DITTMAR, S. GILL, H. SINGH and M. DARBY: Robust optimization-based multi-loop PID controller tuning: A new tool and its industrial application. ControlEngineering Practice, 20(4), (2012), 355-370.

  • [15] S. IPLIKCI: A comparative study on a novel model-based PID tuning and control mechanism for nonlinear systems. Int. J. of Robust and Nonlinear Control, 20(13), (2010), 1483-1501.

  • [16] B. ANDRIEVSKY, A. FRADKOV and D. PEAUCELLE: Adaptive control experiments for LAAS "Helicopter" benchmark. In Proc. Int. Conf. on Physics and Control, Saint Petersburg, Russia, (2005), 760-766.

  • [17] A.L. FRADKOV, B. ANDRIEVSKY and D. PEAUCELLE: Estimation and control under information constraints for LAAS helicopter benchmark. IEEE Trans. onControl Systems Technology, 18(5), (2010), 1180-1187.

  • [18] H. RIOS, A. ROSALES, A. FERREIRA and A. DAVILA: Robust regulation for a 3-DOF helicopter via sliding-modes control and observation techniques. In 2010 American Control Conference, Baltimore, Maryland, USA, (2010), 4427-4432.

  • [19] H. RIOS, A. ROSALES and A. DAVILA: Global non-homogeneous quasicontinuous controller for a 3-DOF Helicopter. In 2010 11th Int. Workshop on VariableStructure Systems, Mexico City, Mexico, (2010), 475-480.

  • [20] J. SHAN, H.T. LIU and S. NOWOTNY: Synchronised trajectory-tracking control of multiple 3-DOF experimental helicopters. IEE Proc. Control Theory Applications, 152(6), (2005), 683-692.

  • [21] J.E. SLOTINE and W. LI: Applied Nonlinear Control. Englewood Cliffs, NJ (USA), Prentice Hall, 1991.

  • [22] S. LABIOD and T.M. GUERRA: Direct adaptive fuzzy control for a class of MIMO nonlinear systems. Int. J. of Systems Science, 38(8), (2007), 665-675.

  • [23] P.A. IOANNOU and J. SUN: Robust Adaptive Control. Englewood Cliffs, NJ (USA), Prentice Hall, 1996.

Archives of Control Sciences

The Journal of Polish Academy of Sciences

Journal Information


IMPACT FACTOR 2016: 0.705

CiteScore 2016: 3.11

SCImago Journal Rank (SJR) 2016: 0.231
Source Normalized Impact per Paper (SNIP) 2016: 0.565

Metrics

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 46 46 29
PDF Downloads 8 8 5