Rotorcraft aerial manipulator (RAM) system is an aerial robot with manipulators. When performing precise operation in hovering mode, there exists relative disturbance between the rotorcraft aerial vehicle and the manipulator, which cannot be eliminated through establishing dynamic models of the manipulator and the rotorcraft separately. In this research, the overall dynamics model is firstly developed based on dynamic disturbance of the both components, which is simplified as a linear control reference model in hovering mode. The dynamics disturbance caused by rotor system's control delay is compensated, and a predictive controller is designed to eliminate the errors of position and attitude of the end-effector. At last, control strategies are compared in simulative peg-in-hole tasks in cases of external and internal disturbances. The effectiveness of the proposed model and control method is verified by the simulation results of end-effector pose error.
 Behnke D, Bok P-B,Wietfeld C. UAV-based connectivity maintenance for borderline detection[C]//IEEE Vehicular Technology Conference. Piscataway, USA: IEEE, 2013: 1-6. Nigam N, Bieniawski S, Kroo I, et al. Control of multiple UAVs for persistent surveillance: Algorithm and flight test results[J]. IEEE Transactions on Control Systems Technology, 2012, 20(5): 1236-1251.  Skoglar P, Orguner U, Ornqvist D T, et al. Road target search and tracking with gimballed vision sensor on an unmanned aerial vehicle[J]. Remote Sensing, 2012, 4(7): 2076-2111. Kobilarov M. Nonlinear trajectory control of multi-body aerial manipulators[J]. Journal of Intelligent and Robotic Systems, 2014, 73(1-4): 679-692.  Kondak K, Krieger K, Albu-Schaeffer A, et al. Closed-loop behavior of an autonomous helicopter equipped with a robotic arm for aerial manipulation tasks[J]. International Journal of Advanced Robotic Systems, 2013, 10: No.145. Huber F, Kondak K, Krieger K, et al. First analysis and experiments in aerial manipulation using fully actuated redundant robot arm[C]//IEEE/RSJ International Conference on Intelligent Robots and Systems. Piscataway, USA: IEEE, 2013: 3452- 3457. Mellinger D, Lindsey Q, Shomin M, et al. Design, modeling, estimation and control for aerial grasping and manipulation[C]//IEEE/RSJ International Conference on Intelligent Robots and Systems. Piscataway, USA: IEEE, 2011: 2668- 2673. Korpela C M, Danko T W, Oh P Y. MM-UAV: Mobile manipulating unmanned aerial vehicle[J]. Journal of Intelligent and Robotic Systems, 2012, 65(1-4): 93-101.  Scholten J L J, Fumagalli M, Stramigioli S, et al. Interaction control of an UAV endowed with a manipulator[C]//IEEE/RSJ International Conference on Robotics and Automation. Piscataway, USA: IEEE, 2013: 4910-4915. Kim S, Choi S, Kim H J. Aerial manipulation using a quadrotor with a two DoF robotic arm[C]//IEEE/RSJ International Conference on Intelligent Robots and Systems. Piscataway, USA: IEEE, 2013: 4990-4995. Ding X L, Yu Y S. Dynamic analysis, optimal planning and composite control for aerial arm-operating with a multipropeller multifunction aerial robot[C]//IEEE International Conference on Mechatronics and Automation. Piscataway, USA: IEEE, 2012: 420-427. Song D L, Qi J T, Dai L, et al. Modelling a small-size unmanned helicopter using optimal estimation in the frequency domain[J]. International Journal of Intelligent Systems Technologies and Applications, 2010, 8(1-4): 70-85. Song D L, Wu C, Qi J T, et al. Aggressive maneuvering of unmanned helicopters: Learning from human based on neural networks[C]//Advances in Intelligent Systems and Computing. Berlin, Germany: Springer-Verlag, 2012: 693-703. Pounds P E I, Bersak D R, Dollar A M. Grasping from the air: Hovering capture and load stability[C]//IEEE International Conference on Robotics and Automation. Piscataway, USA: IEEE, 2011: 2491-2498. Song D L, Han J D, Liu G J. Active model-based predictive control and experimental investigation on unmanned helicopters in full flight envelope[J]. IEEE Transactions on Control Systems Technology, 2013, 21(4): 1502-1509.  Orsag M, Korpela C M, Bogdan S, et al. Hybrid adaptive control for aerial manipulation[J]. Journal of Intelligent and Robotic Systems, 2014, 73(1-4): 693-707.  Korpela C, Brahmbhatt P, Orsag M, et al. Towards the realization of mobile manipulating unmanned aerial vehicles (MMUAV): Peg-in-hole insertion tasks[C]//IEEE International Conference on Technologies for Practical Robot Applications. Piscataway, USA: IEEE, 2013: 54-59. Bramwell A R S, Done G, Balmford D. Bramwell's helicopter dynamics[M]. 2ed ed. Reston, USA: AIAA, 2001. He Y Q, Han J D. Acceleration-feedback-enhanced robust control of an unmanned helicopter[J]. Journal of Guidance, Control, and Dynamics, 2010, 33(4): 1236-1250.  Klancar G, Skrjanc I. Tracking-error model-based predictive control for mobile robots in real time[J]. Robotics and Autonomous Systems, 2007, 55(6): 460-469.  Ahmed B, Pota H R. Dynamic compensation for control of a rotary wing UAV using positive position feedback[J]. Journal of Intelligent and Robotic Systems, 2011, 61(1-4): 43-56.  Wang Z, Song D L, Qi J T, et al. A full-functional simulation and test platform for rotorcraft unmanned aerial vehicle autonomous control[C]//Advances in Intelligent Systems and Computing. Berlin, Germany: Springer-Verlag, 2012: 537-547. Kim H-C, Dharmayanda H R, Kang T, et al. Parameter identification and design of a robust attitude controller using H∞ methodology for the raptor E620 small-scale helicopter[J]. International Journal of Control, Automation and Systems, 2012, 10(1): 88-101.  Kutz B M, Kowarsch U, Keβler M, et al. Numerical investigation of helicopter rotors in ground effect[C]//30th AIAA Applied Aerodynamics Conference. Reston, USA: AIAA, 2012: 1137-1150.