Neural Network Feed-forward Control of Free-floating Dual-arm Space robot System in Joint Space
- Paper number
IAC-08.C1.1.11
- Author
Mr. Huang Dengfeng, China
- Coauthor
Prof. Li Chen, Fuzhou University, China
- Year
2008
- Abstract
Space robot systems will play an important role in the future space projects. The application of space robot systems in outer space can improve astronauts’ working efficiency and save on expenses effectively. It is necessary to employ space robot systems without the base’s control because control fuel is extremely precious in space. As a result, the kinematics, dynamics and control of this kind of space robot systems has received extensive attention. Because of the high dynamic coupling between the robot arms and the base, the motion of the arms will disturb the position and attitude of the base. As a result, the dynamic equation of the system cannot be linearly parameterized. This results in infeasibility of most adaptive control and nonlinear control schemes which are currently used in terrestrial robot control, because the linear parameterization is a prerequisite of these schemes. In order to overcome the above problem, the neural network modeling technique is employed to approximate the dynamic model of dual-arm space robot system. The neural network feed-forward control of free-floating dual-arm space robot systems in joint space is discussed in this paper. According to the law of conservation of the linear and angular momentum, the dynamic equations of space robot systems are established through Lagrange equation of the second kind. Based on the above results, the dynamic equations are modeled by Gaussian radial basis function neural network. A combined scheme of neural network feed-forward control and routine feedback control for space robot systems with unknown parameters is proposed to track desired trajectories in joint space. The proposed control scheme needs neither linearly parameterize the dynamic equations of the system, nor know any dynamic parameters. Besides, it uses an on-line stable weight updating mechanism, so it does not require the time-consuming training process and saves the training time of neural network. To show the performance of the proposed controllers, a simulation is carried out on a planar free-floating dual-arm space robot system. The simulation results show that the proposed control scheme is feasible and effective.
- Abstract document
- Manuscript document
IAC-08.C1.1.11.pdf (🔒 authorized access only).
To get the manuscript, please contact IAF Secretariat.