Underactuated Attitude–Orbit Coupling Control for Microsatellite Based on a Single Orbital Thruster

Lu, Junjie; Meng, Zhongjie

doi:10.1109/taes.2023.3349365

IEEE Trans. Aerosp. Electron. Syst.

2024

DOI: 10.1109/taes.2023.3349365

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Underactuated Attitude–Orbit Coupling Control for Microsatellite Based on a Single Orbital Thruster

Junjie Lu,

Zhongjie Meng

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Cited by 3 publications

References 33 publications

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Convex set reliability-based optimal attitude control for space solar power station with bounded and correlated uncertainties

Yang,

Wu,

Fan

et al. 2025

Chaos, Solitons & Fractals

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Convex set reliability-based optimal attitude control for space solar power station with bounded and correlated uncertainties

Yang,

Wu,

Fan

et al. 2025

Chaos, Solitons & Fractals

View full text Add to dashboard Cite

A Survey of Planar Underactuated Mechanical System

Huang,

Yu,

Zeng

et al. 2024

Machines

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Planar underactuated mechanical systems have been a popular research issue in the area of mechanical systems and nonlinear control. This paper reviews the current research status of control methods for a class of planar underactuated manipulator (PUM) systems containing a single passive joint. Firstly, the general dynamics model and kinematics model of the PUM are given, and its control characteristics are introduced; secondly, according to the distribution position characteristics of the passive joints, the PUM is classified into the passive first joint system, the passive last joint system, and the passive intermediate joint system, and the analysis and discussion are carried out in respect to the existing intelligent control methods. Finally, in response to the above discussion, we provide a brief theoretical analysis and summarize the challenges faced by PUM, i.e., uncertainty and robustness of the system, unified control methods and research on underactuated systems with uncontrollable multi-passive joints; at the same time, the practical applications have certain limitations that need to be implemented subsequently, i.e., anti-jamming, multi-planar underactuated robotic arm co-control and spatial underactuated robotic arm system development. Aiming at the above challenges and problems in the control of PUM systems, we elaborate on them in points, and put forward the research directions and related ideas for future work, taking into account the contributions of the current work.

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Modeling, Simulation, and Control of a Rotary Inverted Pendulum: A Reinforcement Learning-Based Control Approach

Hernandez,

Garcia-Hernandez,

Jurado

2024

Modelling

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In this paper, we address the modeling, simulation, and control of a rotary inverted pendulum (RIP). The RIP model assembled via the MATLAB (Matlab 2021a)®/Simulink (Simulink 10.3) Simscape (Simscape 7.3)™ environment demonstrates a high degree of fidelity in its capacity to capture the dynamic characteristics of an actual system, including nonlinear friction. The mathematical model of the RIP is obtained via the Euler–Lagrange approach, and a parameter identification procedure is carried out over the Simscape model for the purpose of validating the mathematical model. The usefulness of the proposed Simscape model is demonstrated by the implementation of a variety of control strategies, including linear controllers as the linear quadratic regulator (LQR), proportional–integral–derivative (PID) and model predictive control (MPC), nonlinear controllers such as feedback linearization (FL) and sliding mode control (SMC), and artificial intelligence (AI)-based controllers such as FL with adaptive neural network compensation (FL-ANC) and reinforcement learning (RL). A design methodology that integrates RL with other control techniques is proposed. Following the proposed methodology, a FL-RL and a proportional–derivative control with RL (PD-RL) are implemented as strategies to achieve stabilization of the RIP. The swing-up control is incorporated into all controllers. The visual environment provided by Simscape facilitates a better comprehension and understanding of the RIP behavior. A comprehensive analysis of the performance of each control strategy is conducted, revealing that AI-based controllers demonstrate superior performance compared to linear and nonlinear controllers. In addition, the FL-RL and PD-RL controllers exhibit improved performance with respect to the FL-ANC and RL controllers when subjected to external disturbance.

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Underactuated Attitude–Orbit Coupling Control for Microsatellite Based on a Single Orbital Thruster

Cited by 3 publications

References 33 publications

Convex set reliability-based optimal attitude control for space solar power station with bounded and correlated uncertainties

Convex set reliability-based optimal attitude control for space solar power station with bounded and correlated uncertainties

A Survey of Planar Underactuated Mechanical System

Modeling, Simulation, and Control of a Rotary Inverted Pendulum: A Reinforcement Learning-Based Control Approach

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