To improve flight performance of small rotary-wing unmanned aircraft under complex environment, a composite control method based on internal model control (IMC) and adaptive radial basis neural network (RBFNN) is proposed. With the analysis of the characteristics of system disturbance, an IMC system is constructed to eliminate system errors. Furthermore, an adaptive RBFNN without prior training is proposed to eliminate residual estimation errors to augment the control performance. The effectiveness of the composite control method is validated by a series of flight tests. Compared with the feedback control method, the composite control method can yield good tracking performance under wind disturbances.
AgusBSinggihS (2007) Optimal tracking controller design for a small scale helicopter. Journal of Bionic Engineering4(4): 271–280.
2.
AlexanderJVSjirUNickE (2009) Safety in high-risk helicopter operations: the role of additional crew in accident prevention. Safety Science5(47): 717–721.
3.
ApkarianPChampetierCMargniJF (1989) Design of a helicopter output feedback control law using modal and structured-robustness technique. internal journal of Control4(50): 84–96.
4.
BayraktarSFeronE (2009) Experiments with small unmanned helicopter nose up landings. Journal of Guidance, Control and Dynamics1(32): 332–337.
5.
BhandariSColgrenR (2008) 14-Dof parameter varying model of a UAV helicopter using analytical techniques. In Proceedings of the AIAA Modeling And Simulation Technologies Conference and Exhibition, Honolulu, HI, AIAA 2008–6523.
6.
CaiGWChenBMLeeTH. (2009) Design and implementation of a hardware-in-the-loop simulation system for small-scale UAV helicopters. Mechatronics7(19): 1057–1066.
7.
CaiGWChenBMPengKM. (2008) Modeling and control of the yaw channel of a UAV helicopter. IEEE Transaction on Industrial Electronics9(55): 3426–3434.
8.
CarloLBFabioLGiorgioM (2012) Efficient rotorcraft trajectory optimization using comprehensive models by improved shooting methods. Aerospace Science and Technology1(23): 34–42.
9.
ChienTLChenCCHuangYC. (2008) Stability and almost disturbance decoupling analysis of nonlinear system subject to feedback linearization and feedforward neural network controller. IEEE Transactions on Neural Networks19(7): 1220–1230.
10.
DavidLGerardoRAnandS. (2010) Robustness margin for attitude control of a four rotor mini-rotorcraft: Case of study. Mechatronics1(20): 143–152.
11.
DouikA (2008) Optimized eigenstructure assignment by ant system and LQR approaches. International Journal of Computer Science and Applications4(5): 45–56.
12.
FerruzJVegaVMOlleroA. (2011) Reconfigurable control architecture for distributed systems in the HERO autonomous helicopter. IEEE Transactions on Industrial Electronics12(58): 5311–5318.
13.
GadewadikarJLewisFLSubbaraoK. (2009) H∞ static output feedback control for rotorcraft. Journal of Intelligent Robot Systems4(54): 629–646.
14.
GeSSRenBBLeeTH (2009) Approximation based control of uncertain helicopter dynamic. IET Theory and Application7(3): 941–956.
15.
IsidoriAMarconiLSerraniA (2003) Robust nonlinear motion control of a helicopter. IEEE Transactions on Automatic Control3(48): 413–426.
16.
LeiXSDuYH (2010) A linear domain system identification for small unmanned aerial rotorcraft based on adaptive genetic algorithm. Journal of Bionic Engineering2(7): 142–149.
17.
LeiXSLiJJ (2012) An adaptive information fusion method for autonomous landing processes of small unmanned aerial rotorcraft. Sensors10(12): 13212–13224.
18.
LinFDongXXChenBM. (2012) A robust real time embedded vision system on an unmanned rotorcraft for ground target following. IEEE Transactions on Industrial Electronics2(59): 1038–1049.
19.
LiuCJChenWHAndrewsJ (2012) Tracking control of small scale helicopters using explicit nonlinear MPC augmented with disturbance observers. Control Engineering Practice3(20): 258–268.
20.
LuoCHLiuRFYangCD. (2003) Helicopter H∞ control design with robust flying quality. Aerospace Science and Technology2(7): 159–169.
21.
MartensD (1999) Neural networks as a tool for assessment of human pilot behavior in wind shear. Aerospace Science and Technology1(3): 39–48.
22.
MazaIKondakKBernardM. (2010) Multi-UAV cooperation and control for load transportation and deployment. Journal of Intelligent Robot Systems1–4(57): 417–449.
23.
RussellEJennieS (2003) Helicopter trimming and tracking control using direct neural dynamic programming. IEEE Transactions on Neural Networks4(14): 929–939.
24.
ŠpinkaOHolubOHanzálekZ (2011) Low-cost reconfigurable control system for small UAVs. IEEE Transactions on Industrial Electronics3(58): 880–897.
25.
StevensBLLewisFL (2004) Aircraft Control and Simulation. New York: Wiley-Interscience, pp. 23–68.
26.
ZhengBZhongYS (2011) Robust attitude regulation of a 3-DOF helicopter benchmark: theory and experiments. IEEE Transactions on Industrial Electronics2(58): 660–670.
