Robust Control for Coordinated Motion of Flexible Space Manipulator Based on the Augmentation Approach

2010 ◽  
Author(s):  
Zhiyong Chen ◽  
Li Chen
Keyword(s):  
Robust Control ◽  
A Priori ◽  
Joint Space ◽  
Momentum Conservation ◽  
Network Control ◽  
Coordinated Motion ◽  
Space Manipulator ◽  
Assumed Mode Method ◽  
Uncertainty Bound ◽  
Mode Method

In this paper, the coordinated control of a flexible space manipulator system with a front flexible link is discussed. With the assumed mode method and linear momentum conservation of the system, the dynamics of the manpulator is derived in Lagrangian formulation. By using the augmentation approach, a robust control scheme for the coordinated motion between the spacecraft’s attitude and arm’s joints of the flexible space manipulator with bounded external disturbances and uncertain parameters to track the desired trajectories in joint space is proposed. It is designed based on a priori knowledge about the uncertainty-bound and possesses the advantage that it can greatly reduce the calculation time needed by the adaptive or neural network control schemes. Simulation results show that the presented controller can stabilize the system to track the desired trajectories and keep the vibration amplitude of the flexible arm to be relatively low-level.

Fuzzy Wavelet Neural Network Control for Coordinated Motion of Free-Floating Space Manipulator System in Joint Space

2009 ◽  
Author(s):  
Huang Dengfeng ◽  
Chen Li
Keyword(s):  
Neural Network ◽  
Lagrange Equation ◽  
Joint Space ◽  
Wavelet Neural Network ◽  
Dynamic Equations ◽  
Back Propagation Algorithm ◽  
Coordinated Motion ◽  
Space Manipulator ◽  
Control Scheme ◽  
Fuzzy Wavelet Neural Network

The dynamic control for coordinated motion of free-floating space manipulator system in joint space is discussed. According to the geometrical relationship and the linear momentum conservation law, the dynamic equations of space manipulator system are established through Lagrange equation of the second kind. Based on the above, a fuzzy wavelet neural network scheme is designed to control the base’s attitude and the joint angle of manipulator to track desired trajectories synchronously in joint space. The control scheme needs neither linearly parameterize the dynamic equations of the system, nor know any dynamic parameters. Moreover, its network weight is learning by back propagation algorithm online so the training time is saved. Numerical simulations are presented to verify the feasibility and effectiveness of the proposed control scheme.

Tracking and vibration control of a free-floating space manipulator system with flexible links and joints

2021 ◽  
pp. 095441002110311
Author(s):  
Yuming Huang ◽  
Weidong Chen ◽  
Minqiang Shao
Keyword(s):  
Cross Sections ◽  
Coupled System ◽  
Joint Space ◽  
Momentum Conservation ◽  
Singular Perturbation Theory ◽  
Linear Quadratic ◽  
Space Manipulator ◽  
Hybrid Controller ◽  
System Method ◽  
Integral Manifolds

The problem of modeling and controlling of a free-floating space manipulator with flexures in both links and joints is addressed in this study. A mathematical model of the system is developed by combining Lagrange’s equations and momentum conservation. The finite element method is introduced to discretize multi-links with complex cross-sections. In order to reduce the dimensions and maintain the precision of a rigid-flexible coupled system, an iterated improved reduction system method is adopted. Then, a novel composite control scheme for the reduced system is presented that uses the concept of integral manifolds and singular perturbation theory. Finally, an augmented computed torque controller is applied to the under-actuated slow subsystem to realize trajectory tracking in joint space, while a linear-quadratic controller is designed to damp out the vibration of joints and links. Numerical simulation results verified that the proposed hybrid controller can successfully suppress vibration and track trajectory at the same time.

A Method to Improve the Modal Convergence for Structures With External Forcing

1987 ◽  
Vol 54 (4) ◽  
pp. 904-909 ◽  
Author(s):  
Keqin Gu ◽  
Benson H. Tongue
Keyword(s):  
Spatial Distribution ◽  
Free Vibration ◽  
Convergence Rate ◽  
Traditional Approach ◽  
Vibration Modes ◽  
External Forcing ◽  
Slow Convergence ◽  
Assumed Mode Method ◽  
Mode Method ◽  
Assumed Mode

The traditional approach of using free vibration modes in the assumed mode method often leads to an extremely slow convergence rate, especially when discete interactive forces are involved. By introducing a number of forced modes, significant improvements can be achieved. These forced modes are intrinsic to the structure and the spatial distribution of forces. The motion of the structure can be described exactly by these forced modes and a few free vibration modes provided that certain conditions are satisfied. The forced modes can be viewed as an extension of static modes. The development of a forced mode formulation is outlined and a numerical example is presented.

Multi-Objective Trajectory Optimization of Free-Floating Space Manipulator Using NSGA-II

2015 ◽  
Vol 713-715 ◽  
pp. 800-804 ◽  
Author(s):  
Gang Chen ◽  
Cong Wei ◽  
Qing Xuan Jia ◽  
Han Xu Sun ◽  
Bo Yang Yu
Keyword(s):  
Trajectory Optimization ◽  
Interpolation Method ◽  
Optimal Solution ◽  
Optimization Method ◽  
Joint Space ◽  
Motion Path ◽  
Objective Functions ◽  
Nsga Ii ◽  
Space Manipulator ◽  
Multi Objective

In this paper, a kind of multi-objective trajectory optimization method based on non-dominated sorting genetic algorithm II (NSGA-II) is proposed for free-floating space manipulator. The aim is to optimize the motion path of the space manipulator with joint angle constraints and joint velocity constraints. Firstly, the kinematics and dynamics model are built. Secondly, the 3-5-3 piecewise polynomial is selected as interpolation method for trajectory planning of joint space. Thirdly, three objective functions are established to simultaneously minimize execution time, energy consumption and jerk of the joints. At last, the objective functions are combined with the NSGA-II algorithm to get the Pareto optimal solution set. The effectiveness of the mentioned method is verified by simulations.

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