Hierarchy-Based Adaptive Generalized Predictive Control for Aerial Grasping of a Quadrotor Manipulator

Abstract

Abstract:In this paper, an adaptive generalized predictive control (GPC) based on hierarchical control strategy is designed for a quadrotor with a robotic arm. For this nonlinear and coupled system, a two-layer control structure is adopted to achieve more precise trajectory tracking and keep the tracking performance after aerial grasping. The inner-layer controller is a proportional-derivative (PD) controller. The outer-layer subsystem is linearized by input-output linearization first and an adaptive generalized predictive controller is applied. The effectiveness of this approach is verified through the simulation using MATLAB/Simulink. A PD controller with feedforward control input is applied on such a system for a comparative study. Simulation results show that a better tracking performance can be achieved by the proposed strategy.

Key words:unmanned aerial vehicle| robotic arm| predictive control| trajectory tracking

摘要：In this paper, an adaptive generalized predictive control (GPC) based on hierarchical control strategy is designed for a quadrotor with a robotic arm. For this nonlinear and coupled system, a two-layer control structure is adopted to achieve more precise trajectory tracking and keep the tracking performance after aerial grasping. The inner-layer controller is a proportional-derivative (PD) controller. The outer-layer subsystem is linearized by input-output linearization first and an adaptive generalized predictive controller is applied. The effectiveness of this approach is verified through the simulation using MATLAB/Simulink. A PD controller with feedforward control input is applied on such a system for a comparative study. Simulation results show that a better tracking performance can be achieved by the proposed strategy.

关键词:unmanned aerial vehicle| robotic arm| predictive control| trajectory tracking

CLC Number:

SONG Xueqian* (宋雪倩), HU Shiqiang (胡士强). Hierarchy-Based Adaptive Generalized Predictive Control for Aerial Grasping of a Quadrotor Manipulator[J]. Journal of Shanghai Jiao Tong University (Science), 2019, 24(4): 451-458.

References20

[1]	LIPPIELLO V, RUGGIERO F. Cartesian impedancecontrol of a UAV with a robotic arm [C]//10th IFACSymposium on Robot Control. Dubrovnik, Croatia: InternationalFederation of Automatic Control, 2012:704-709.
[2]	LOPES R V, SANTANA P H R Q A, BORGES GA, et al. Model predictive control applied to trackingand attitude stabilization of a VTOL quadrotor aircraft[C]//Proceedings of COBEM 2011. Natal, RN,Brazil: ABCM, 2011: 1-10.
[3]	ARLEO G, CACCAVALE F, MUSCIO G, et al.Control of quadrotor aerial vehicles equipped with arobotic arm [C]//21st Mediterranean Conference onControl and Automation (MED). Platanias-Chania,Crete, Greece: IEEE, 2013: 1-7.
[4]	BANGURA M, MAHONY R. Real-time model predictivecontrol for quadrotors [J]. IFAC Proceedings Volumes.Cape Town, South Africa, 2014: 11773-11780.
[5]	WANG Y, RAMIREZ-JAIME A, XU F, et al. Nonlinearmodel predictive control with constraint satisfactionsfor a quadcopter [J]. Journal of Physics: ConferenceSeries, 2017, 783: 012025.
[6]	GARIMELLA G, KOBILAROV M. Towards modelpredictivecontrol for aerial pick-and-place [C]//IEEEInternational Conference on Robotics and Automation.Washington, USA: IEEE 2015: 4692-4697.
[7]	ANTONELLI G, CATALDI E. Adaptive control ofarm-equipped quadrotors. Theory and simulations[C]// 22nd Mediterranean Conference on Control andAutomation (MED). Palermo, Italy: IEEE, 2014:1446-1456.
[8]	MELLINGER D, LINDSEY Q, SHOMIN M, et al.Design, modeling, estimation and control for aerialgrasping and manipulation [C]//IEEE/RSJ InternationalConference on Intelligent Robots and Systems.San Francisco, CA, USA: IEEE, 2011: 2668-2673.
[9]	MELLINGER D, KUMAR V. Minimum snap trajectorygeneration and control for quadrotors [C]//IEEEInternational Conference on Robotics and Automation.Shanghai, China: IEEE, 2011: 2520-2525.
[10]	MELLINGER D, MICHAEL N, KUMAR V. Trajectorygeneration and control for precise aggressive maneuverswith quadrotors [J]. International Journal ofRobotics Research, 2012, 31(5): 664-674.
[11]	LI X C. Dynamic analysis and control for multi-rotorsgrasping [D]. Harbin, China: Harbin Institute of Technology,2015 (in Chinese).
[12]	MING T, DENG W, ZHANG S, et al. MPC-basedtrajectory tracking control for intelligent vehicles[C]//SAE 2016 World Congress and Exhibition. Detroit,USA: SAE International, 2016: 1-7.
[13]	KIM H J, SHIM D H, SASTRY S. Nonlinear modelpredictive tracking control for rotorcraft-based unmannedaerial vehicles [C]//Proceedings of the AmericanControl Conference. Anchorage, AK, USA: IEEE,2002: 3576-3581.
[14]	SLEGERS N, KYLE J, COSTELLO M. Nonlinearmodel predictive control technique for unmanned airvehicles [J]. Journal of Guidance, Control, and Dynamics,2006, 29(5): 1179-1188.
[15]	MERABTI H, BOUCHACHI I, BELARBI K. Nonlinearmodel predictive control of quadcopter [C]//16thInternational Conference on Sciences and Techniquesof Automatic Control and Computer Engineering.Monastir, Tunisia: IEEE, 2015: 208-211.
[16]	ALEXIS K, NIKOLAKOPOULOS G, TZES A.Switching model predictive attitude control for aquadrotor helicopter subject to atmospheric disturbances[J]. Control Engineering Practice, 2011, 19(10):1195-1207.
[17]	LEE D, KIM H J, SASTRY S. Feedback linearizationvs. adaptive sliding mode control for a quadrotor helicopter[J]. International Journal of Control, Automation,and Systems, 2009, 7(3): 419-428.
[18]	CLARKE D W, MOHTADI C, TUFFS P S. Generalizedpredictive control — Part I. The basic algorithm[J]. Automatica, 1987, 23(2): 137-148.
[19]	CAO Y, HE D B, YU F, et al. Generalized predictivecontrol based on vehicle path following strategy by usingactive steering system [J]. Journal of Shanghai JiaoTong University, 2016, 50(3): 401-406 (in Chinese)
[20]	WANG W. The Basic Method of GPC [M]. Beijing,China: Science Press, 1998: 10-25 (in Chinese).