Neural network-based adaptive terminal sliding mode control for the deployment process of the dual-body tethered satellite system

Abstract

The dual-body tethered satellite system, which consists of two spacecraft connected by a single tether, is one of the most promising configurations in numerous space missions. To ensure the stability of deployment, the radial basis function neural network-based adaptive terminal sliding mode controller is proposed for the dual-body tethered satellite system with the model uncertainty and external disturbance. The terminal sliding mode controller serves as the main control framework for its properties of the strong robustness and finite-time convergence. The radial basis function neural network is adopted to approximate the model uncertainty, in which the weight vector of the radial basis function neural networks and the unknown upper bound of the external disturbance are estimated by using two adaptive laws. Finally, the Lyapunov theory and numerical simulations are used to prove the validity of the proposed controller.

Adaptive intelligent terminal sliding mode controller for stabilizing a chaotic plasma torch system

“…There are many SM-based control methods in which fuzzy, neural, and adaptive system methods can be applied to the system of this article. However, our results can also be compared with the results obtained from some other works such as Liu et al (2020), Mardani et al (2016), Qian and Fan (2018), Sun et al (2019), Vali et al (2016 and Zare et al (2019). However, we have considered only those methods which have been applied to the PTS.…”

“…In Sun et al (2019), the tracking control problem has been investigated by means of adaptive TSM control in which an NN has been used to approximate an unknown nonlinear part of the system. Liu et al (2020) have proposed an NN-based TSM controller in which the RBF NN is adopted to approximate the model uncertainty. These methods have been applied to different systems, and they have provided some advantages such as robustness with chattering-free response, adaptability and learnability for variable environments, and finite-time convergence which make them suitable for controlling nonlinear systems such as the PTS.…”

Deployment of Hub-Spoke Tethered Satellite Formation with Adaptive Sliding Mode Tension Control

“…An adaptive sliding mode controller was proposed in [22] to deploy an electro-dynamic tether with the consideration of partial unknown parameters. For a more extreme situation, when the nonlinear dynamic model has uncertainty and there exist external disturbances, the terminal sliding mode control (TSMC) approach combined with neural network was employed to deploy a dual-body tethered system [23]. In addition, in order to achieve better dynamic responses, fractional order SMC method, characterized by its favorable historical memory effect, was applied to control the process of tether deployment [24,25].…”