漂浮基空间机器人捕获卫星过程动力学模拟及捕获后混合体运动的RBF神经网络控制

doi:10.7527/S1000-6893.2013.0157

Abstract

Abstract:

This paper discusses the collision dynamics modeling of a free-floating space-based robot in the process of on-orbit satellite capturing, and it also analyzes the stability control for the compounded body of the space-based robot and target after the capturing operation is completed. First the method of multibody system dynamics modeling is employed in combination with the characteristics of collision dynamics of the space-based robot while it captures the target satellite to set up a dynamics model for the free-floating space-based robot during its on-orbit capture of the floating satellite. Based on it, the movement speed for the compounded body of the space-based robot and target is calculated. In view of the fact that for the inertia parameters of both the satellite and the space-based robot system are unknown, the model and the theory of neural network control and Lyapunov stability theory are used to design a Gaussian radial basis function neural network control scheme for the compounded body to move stably under the influence of collision and impact during the capturing process. Thus, the effective control is realized for capturing a target satellite. The Gaussian radial basis function neural network control scheme has the obvious advantages of requiring no feedback and measurement of the position,velocity,acceleration,attitude angle velocity and attitude angle acceleration of the floating base. Finally, the validity and applicability of the control scheme are manifested by system numerical simulation.

Key words: free-floating space-based robot, on-orbit capture satellite, collision dynamics modeling, stable movement, Gaussian radial basis function, neural networks

CLC Number:

V447
TP242

LIANG Jie, CHEN Li. Dynamics Modeling for Free-floating Space-based Robot During Satellite Capture and RBF Neural Network Control for Compound Body Stable Movement[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, doi: 10.7527/S1000-6893.2013.0157.

References

[1] Isenberg D R, Kakad Y P. Quaternion based computed-torque and feed-forward tracking controllers for a space robot. Proceedings of the Annual South Eastern Symposium on System Theory, 2010: 232-236.

[2] Abiko S, Hirzinger G. An adaptive control for a free-floating space robot by using inverted chain approach. Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2007: 2236-2241.

[3] Gu Y L, Xu Y S. A normal form augmentation approach to adaptive control of space robot systems. Journal of the Dynamics and Control, 1995, 5(3): 275-294.

[4] Guo Y S, Chen L. Adaptive robust control for free-floating space robot system with dual-arms to track desired trajectory in joint space. Journal of System Simulation, 2009, 21(3): 625-633. (in Chinese) 郭益深, 陈力. 双臂空间机器人的自适应鲁棒性联合控制. 系统仿真学报, 2009, 21(3): 625-633.

[5] Nanos K. On the use of free-floating space robots in the presence of angular momentum. Intelligent Service Robotics, 2011, 4(1): 3-15.

[6] Ding X L, Yu Y S. A multi-propeller and multi-function aero-robot and its motion planning of leg-wall-climbing. Acta Aeronautica et Astronautica Sinica, 2010, 31(10): 2075-2086. (in Chinese) 丁希仑, 俞玉树.一种多旋翼多功能空中机器人及其腿式壁面行走运动规划. 航空学报, 2010, 31(10): 2075-2086.

[7] Ge X S, Chen L Q, Lv J. Nonholonomic motion planning of a space manipulator system using genetic algorithm. Journal of Astronautics, 2005, 26(3): 262-266.(in Chinese) 戈新生, 陈立群, 吕杰. 空间机械臂非完整运动规划的遗传算法研究. 宇航学报, 2005, 26(3): 262-266.

[8] Wang C Q, Zhang C L. Dynamic control of a free-floating flexible dual-arm space robotic system. Chinese Journal of Mechanical Engineering, 2007, 43(10): 196-200. (in Chinese) 王从庆, 张承龙.自由浮动柔性双臂空间机器人系统的动力学控制. 机械工程学报, 2007, 43(10): 196-200.

[9] Hong Z D, Yun C, Chen L. Modeling and trajectory tracking control of a free-floating space robot with flexible manipulators. Robot, 2007, 29(1): 92-96. (in Chinese) 洪在地, 贠超, 陈力. 柔性臂漂浮基空间机器人建模与轨迹跟踪控制. 机器人, 2007, 29(1): 92-96.

[10] Li Q, Wang T S. Adaptive mode method in inverse dynamics of a rotating flexible manipulator with high-frequency excitation. Chinese Journal of Space Science, 2008, 28(4): 345-349. (in Chinese) 李青, 王天舒.高频激励下旋转柔性臂逆动力学模态自适应方法研究. 空间科学学报, 2008, 28(4): 345-349.

[11] Liang J, Chen L. Improved nonlinear feedback control for free-floating space-based robot with time-delay based on predictive and approximation of taylor series. Acta Aeronautica et Astronautica Sinica, 2012, 33(1): 163-169. (in Chinese) 梁捷, 陈力.具有时延的漂浮基空间机器人基于泰勒级数预测、逼近的改进非线性反馈控制. 航空学报, 2012, 33(1): 163-169.

[12] Liang J, Chen L. Fuzzy logic adaptive compensation control for dual-arm space robot based on computed torque controller to track desired trajectory in inertia space. Engineering Mechanics, 2010, 27(11): 221-228. (in Chinese) 梁捷, 陈力. 基于标称计算力矩控制器的双臂空间机器人惯性空间轨迹跟踪的模糊自适应补偿控制.工程力学, 2010, 27(11): 221-228.

[13] Pan J, Cai G P. Particle swarm optimizer for optimal locations of actuators of a trussed structure. Engineering Mechanics, 2009, 26(12): 35-39. (in Chinese) 潘继, 蔡国平. 桁架结构作动器优化配置的粒子群算法. 工程力学, 2009, 26(12): 35-39.

[14] Oda M, Kibe K, Yamagata F. ETS-VII, space robot in-orbit experiment satellite. Proceedings of the IEEE International Conference on Robotics and Automation, 1996: 739-744.

[15] Whelan D A. DARPA orbital express program: effecting a revolution in space-based systems. Proceedings of the International Society for Optical Engineering, 2004: 48-56.

[16] Slotin J E, Li W P. On the adaptive control of robot manipulators. Journal of the Robots Research, 1987, 6(3): 49-59.

Dynamics Modeling for Free-floating Space-based Robot During Satellite Capture and RBF Neural Network Control for Compound Body Stable Movement

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