Variable Structure Control for Space Robots Based on Neural Networks

Abstract

Problems of trajectory tracking for a class of freefloating robot manipulators with uncertainties are considered. Two neural network controls are designed. The first scheme consists of a PD feedback and a dynamic compensator which is an RBF neural network controller. The second scheme syncretizes neural networks with variable structures using a saturation function. Neutral networks are used to adaptively learn about and compensate for the unknown system. Approach errors are eliminated as disturbances by using the variable structure controller. The shortcomings of local networks are considered. The control is based on dividing aspects into three sections with classification and integration: state dimensional, neural network and variable structure separate control. When invalidations of the neutral network appeared, the controller was able to guarantee good robustness as well as the stability of the closed-loop system. The simulation results show that the methods presented are effective.

Robust Adaptive Control of a Free-Floating Space Robot System in Cartesian Space

“…If k s is big enough and the parameter C 0 satisfies C 0 − C 1 D 1 > 0 , then the control system constructed by (21) and (25) is stable. That is, the variables in the loop are bounded, and the reference-tracking error η and the torque-prediction error σ are located in the ellipse defined by the following inequation:…”

“…The following theorem, Theorem 1, is established considering the robust stability of the closed-loop system (21).…”

“…An indirect adaptive control strategy was proposed based on the extended manipulator model, but the parameters of the controller needed to be obtained via online calculations, which increased the calculation burden and could not guarantee the reversibility of the inertial matrix [19]. Other scholars [20][21][22][23] studied the adaptive control issue of the FFSR system using fuzzy or neural network theories, but these were approximations of the mathematical model of the system, which had errors when compared with the actual model of the system. A robust, adaptive trajectory-tracking control method in Cartesian space is proposed in the paper.…”

Adaptive multivariable generalized super-twisting algorithm based robust coordinated control for a space robot subjected to coupled uncertainties

“…The coordinated attitude control scheme 4 has been demonstrated in the project Engineering Test Satellite VII (ETS-VII). 5 Variety of control techniques have been developed for space robot coordinated control systems, including variable structure control methods, [6][7][8][9] adaptive control approaches, [10][11][12][13] optimal control strategies, [14][15][16][17] neural network, 18,19 and extended state observer. 20 It should be pointed out that the manipulator motion 10,14 yields no platform attitude disturbance, which is based on the reaction null space (RNS).…”

Target Capturing Control for Space Robots with Unknown Mass Properties: A Self-Tuning Method Based on Gyros and Cameras

“…Based on these models and concepts, a number of control methods have been proposed for free-floating space robots. A variable structure control strategy was presented by Fang [ 14 ], where a neural network controller is used as the dynamic compensator. Huang et al studied the tethered space robot (TSR), and presented several trajectory planning and control methods [ 15 , 16 , 17 ].…”