Researches on inverse simulation’s applications in teleoperation rendezvous and docking based on hyper-ellipsoidal restricted model predictive control for inverse simulation structure
Restricted accessResearch articleFirst published online July, 2015
Researches on inverse simulation’s applications in teleoperation rendezvous and docking based on hyper-ellipsoidal restricted model predictive control for inverse simulation structure
The inverse simulation is a technique used to calculate the control action based on the expected trajectory or experimental data and has been applied successfully in the aviation field. A novel inverse simulation technique is first introduced in the fields of rendezvous and docking. The least square estimation under the hyper-ellipsoidal restriction is presented to solve inverse simulation problems. The inverse simulation structure used in this paper is based on the model predictive control scheme. The predictive model is derived by Clohessy–Wiltshire dynamics equations, and the accurate one is obtained by two-body dynamics equations. When the designed trajectories or the data obtained by teleoperation console experiments are given to the predictive model, the inverse strategy is transformed into a generalized shrunken estimation problem. Then, the continuous control signals produced by the least square theory are dispersed by the pulse width modulation method and propagated into the high-order model. The inverse simulation results of the traditional control method and the inverse strategy mentioned in this paper show that the maneuvers can be better reproduced by inverse strategy, and the proper choices of sensitive factors and the receding horizon lead to better results.
LuoYZZhangJTangGJ. Survey of orbital dynamics and control of space rendezvous. Chin J Aeronuat2014; 27(1): 1–11.
2.
ZhangBLiHYTangGJ. Human control model in teleoperation rendezvous. Acta Phys Sin2013; 62(2): 029601.1–029601.10.
3.
ZhouJYJiangZCTangGJ. A new approach for teleoperation rendezvous and docking with time delay. Sci China Phys Mech Astron2012; 55(2): 339–346.
4.
Zhang B, Li HY and Tang GJ. Human control model in teleoperation rendezvous. Sci China Inf Sci 2014; 57(11): 1–11.
5.
JonesS. Orbital maneuvering vehicle teleoperation and video data compression. AIAA J1989; 28(9): 99–117.
6.
Cislaghi M. The ATV rendezvous pre-development program (ARP). In: The 22nd AAS guidance control conference, 1999, pp.43–58. Breckenridge: ESA.
7.
Mokuno M and Kawano I. Development of ETSVII RVD system-preliminary design and EM development phase. In: AIAA guidance, navigation, and control conference, Baltimore, MD, USA, 1995, pp.1656–1664.
8.
Mitsushige OD. Experiences and lessons learned from the ETS-VII robot satellite. In: IEEE international conference on robotics and automation, San Francisco, CA, USA, 2000, pp.914–919.
9.
CheathamDCHacklerCT. Handling qualities for pilot control of Apollo lunar-landing spacecraft. J Spacecraft Rockets1966; 3(5): 632–638.
10.
Nicholas S, Frances P, Mark K, et al. Human operator performance of remotely controlled task: a summary of teleoperator research conducted at NASA's Marshall Space Flight Center between 1971 and 1981. NASA TN D-5153, 1982.
11.
Anon. Lunar landing research vehicle: estimated handling qualities. NASA CR-127487, 1964.
12.
StengelRF. Manual attitude control of the lunar module. J Spacecraft Rockets1970; 7(8): 941–948.
13.
ZhouJYZhouJPJiangZC. Investigation into pilot handling qualities in teleoperation rendezvous and docking with time delay. Chin J Aeronaut2012; 23(2): 622–630.
14.
ThomsonDGBradleyR. Inverse simulation as a tool for flight dynamics research—principles and applications. Prog Aerospace Sci2006; 42(3): 174–210.
15.
OsamuKIchiroS. An interpretation of airplane general motion and control as inverse problem. J Guid Control Dyn1986; 9(2): 198–204.
16.
Meyer G and Cicolani L. Application of nonlinear systems inverses to automatic flight control systems design. System Concepts And Flight Evaluation. AGAR Do graph AG-251 on Theory and Applications of Optimal Control in Aerospace Systems, NATO 1980, 10-1–10-29.
17.
Thomson DG. An analytical method of quantifying helicopter agility. In: Proceedings of the 12th European rotorcraft forum, Garmisch-Partenkirchen, Germany, 1986, p.45.
18.
HessRAGaoC. A generalized algorithm for inverse simulation applied to helicopter maneuvering flight. J Am Helicopter Soc1993; 38(4): 3–15.
19.
HessRAZeyadaYHeffleyRK. Modeling and simulation for helicopter task analysis. J Am Helicopter Soc2002; 47(2): 243–252.
20.
RutherfordSThomsonDG. Improved methodologies for inverse simulation. Aeronaut J1996; 100(993): 79–86.
DoyleSThomsonDG. Modification of a helicopter inverse simulation to include an enhanced rotor model. AIAA J Aircraft2000; 37(3): 536–538.
23.
AvanziniGDe MatteisG. Two-timescale inverse simulation of a helicopter model. J Guid Control Dyn2001; 24(2): 330–339.
24.
HessRAGaoCWangSH. Generalized technique for inverse simulation applied to aircraft maneuvers. J Guid Control Dyn1991; 14(5): 920–926.
25.
GaoCHessRA. Inverse simulation of large-amplitude aircraft maneuvers. J Guid Control Dyn1993; 16(4): 733–737.
26.
De MatteisGDe SocioLMLeonessaA. Solution of aircraft inverse problems by local optimization. J Guid Control Dyn1995; 18(3): 567–571.
27.
BorriMBottassoCLMontelaghiF. Numerical approach to inverse flight dynamics. J Guid Control Dyn1997; 20(4): 742–747.
28.
AvanziniGDouglasT. Model predictive control architecture for rotorcraft inverse simulation. J Guid Control Dyn2013; 36(1): 207–217.
29.
MayneDQRawlingsJBRaoCV. Constrained model predictive control: stability and optimality. Automatica2000; 36(6): 789–814.
30.
DraperNR. Ridge regression and James-Stein estimation: review and comments. Technometrics1979; 21(4): 451–466.
31.
AnLHNkurnnzizaSFungKY. Shrinkage estimation in general linear models. Comput Stat Data Anal2009; 53(7): 2537–2549.
32.
WatermanMS. A restricted least squares problem. Technometrics1974; 16: 135–136.
33.
RaoCRToutenburgH. Linear Model: Least Squares and Alternatives, Berlin: Springer, 2005.
34.
ClohessyWHWiltshireRS. Terminal guidance system for satellite rendezvous. J Aerospace Sci1960; 27(9): 653–658.
35.
GiorgioGFrancoMPasqualeP. Design and development of guidance navigation and control algorithms for spacecraft rendezvous and docking experimentation. Acta Astronaut2014; 94: 395–408.
36.
LuoYZLiangLBWangH. Quantitative performance for spacecraft rendezvous trajectory safety. J Guid Control Dyn2011; 34(4): 1264–1269.
37.
Nicholas M, Josue DM and Gloria JW. A new method of guidance control for autonomous rendezvous in a cluttered space environment. In: AIAA guidance, navigation and control conference and exhibit, Hilton Head, South Carolina, 2007.
38.
Yamanake K and Yokota K. Guidance and navigation system design of R-bar approach for rendezvous and docking. In: 17th AIAA International communications satellite systems conference and exhibit, Yokohama, Japan, 1998.
39.
Eckstein MC. Safe rendezvous approach to a space station by impulsive transfers and continuous thrust arcs. In: First European in-orbit operations technology symposium, ESA, SP-272, Darmstadt, Germany, November 1987, pp.3–12.
40.
Matsumoto S, Jacobsen S, Dubowsky S, et al. Approach planning and guidance for uncontrolled rotating satellite capture considering collision avoidance. In: 7th international symposium on artificial intelligence, robotics and automation in space, Nara, Japan, May 2003.
41.
BregerLHowJP. Safe trajectories for autonomous rendezvous of spacecraft. J Guid Control Dyn2008; 31(5): 1478–1489.
42.
Wang H. Control and trajectory safety of rendezvous and docking. PhD Thesis, National University of Defense Technology, Changsha, PRC, 2007.
43.
WangCHYuTChenSG. Predicting performance in manually controlled rendezvous and docking through spatial abilities. Adv Space Res2014; 53: 362–369.
