Control Of Free-floating Space Robot Research Articles

Error model-oriented vibration suppression control of free-floating space robot with flexible joints based on adaptive neural network

At the same time, considering the uncertain factors such as load variation, external interference and joint flexibility in engineering practice, a robust control method based on adaptive neural network is proposed. The dynamic model of free-floating space robot is established, and the error model caused by uncertain factors is deduced. Different from the traditional compensation algorithm that ignores the error model, a compensation controller based on Radial basis function neural network (RBFNN) is designed to approximate the error model. The approximation error is eliminated by robust controller to improve the control accuracy. In order to make full use of the nonlinear approximation ability of neural network, the error model is decomposed into four parts according to the input characteristics, and the neural network compensator is designed for separate and overall compensation, which further improves the control accuracy and robustness. The adaptive learning rates of network weights are designed to ensure online real-time adjustment without offline learning stage. A flexible compensator based on torque and a controller based on moment difference feedback controller (MDFC) are designed to suppress elastic vibration. Simulation and experimental studies show that the proposed strategy can have good compensation performance and robustness, and can better suppress elastic vibration, which proves the effectiveness and superiority of the proposed scheme.

Minimum Base Disturbance Control of Free-Floating Space Robot during Visual Servoing Pre-capturing Process

SUMMARYDuring visual servoing space activities, the attitude of free-floating space robot may be disturbed due to dynamics coupling between the satellite base and the manipulator. And the disturbance may cause communication interruption between space robot and control center on earth. However, it often happens that the redundancy of manipulator is not enough to fully eliminate this disturbance. In this paper, a method named off-line optimizing visual servoing algorithm is innovatively proposed to minimize the base disturbance during the visual servoing process where the degrees-of-freedom of the manipulator is not enough for a zero-reaction control. Based on the characteristic of visual servoing process and the robot system modeling, the optimal control method is applied to achieve the optimization, and a pose planning method is presented to achieve a second-order continuity of quaternion getting rid of the interruption caused by ambiguity. Then simulations are carried out to verify the method, and the results show that the robot is controlled with optimized results during visual servoing process and the joint trajectories are smooth.

Speed Trajectory Tracking Control for Free-Floating Space Robot with Uncertain Inertial Parameters

A speed trajectory tracking control (STTC) approach is proposed to optimize the end-effector trajectory tracking control for free-floating space robot (FFSR) with uncertain inertial parameters, where two stages controller are designed by the state dependent Riccati equation (SDRE). Firstly, the first-stage SDRE nominal optimization controller is designed by using the nominal system model. Next, by analyzing the error transfer process resulting from uncertain parameters under the nominal control law, the second-stage SDRE compensated controller is designed by the state dependent matrix (SDM) of the system state errors. Then, the optimization tracking control for the FFSR with uncertain inertial parameters is achieved by combining the first-stage SDRE nominal optimization controller and the second-stage SDRE compensated controller. Finally, numerical simulations are given to demonstrate the proposed approach which satisfies the precision of the tracking error and the optimization requirement of the input torque.

Adaptive robust control for free-floating space robot with unknown uncertainty based on neural network

It is difficult to obtain a precise mathematical model of free-floating space robot for the uncertain factors, such as current measurement technology and external disturbance. Hence, a suitable solution would be an adaptive robust control method based on neural network is proposed for free-floating space robot. The dynamic model of free-floating space robot is established; a computed torque controller based on exact model is designed, and the controller can guarantee the stability of the system. However, in practice, the mathematical model of the system cannot be accurately obtained. Therefore, a neural network controller is proposed to approximate the unknown model in the system, so that the controller avoids dependence on mathematical models. The adaptive learning laws of weights are designed to realize online real-time adjustment. The adaptive robust controller is designed to suppress the external disturbance and compensate the approximation error and improve the robustness and control precision of the system. The stability of closed-loop system is proved based on Lyapunov theory. Simulations tests verify the effectiveness of the proposed control method and are of great significance to free-floating space robot.

Back-stepping Control of Free-Floating Space Robot based on Adaptive Neural Network

Trajectory tracking control problems of the free-floating space robot are considered by the paper, back-stepping control method based on adaptive neural network is put forward. The complex system is decomposed into several simple sub-systems. The control laws are designed by derived, so that closed-loop stability can be obtained by each subsystem; Because of the influence of interference and the measurement level limitation, accurate mathematical model is difficult to be obtained. Neural network controller of good nonlinear approximation ability is designed to compensate the uncertainty of system model. Adaptive learning laws are designed to ensure that weights can be adjusted online real-time. The system uniformly ultimately bounded (UUB) is proved based on the Lyapunov theory. Simulation experiments show that the control method can fast track the desired trajectory, and has a good application value for space robotic manipulators with uncertainty.