Robust adaptive vibration control for an uncertain flexible Timoshenko robotic manipulator with input and output constraints

2017 ◽  
Vol 48 (13) ◽  
pp. 2860-2870 ◽  
Author(s):  
Xiuyu He ◽  
Wei He ◽  
Changyin Sun
2018 ◽  
Vol 28 (17) ◽  
pp. 5213-5231 ◽  
Author(s):  
Wei He ◽  
Zhe Jing ◽  
Xiuyu He ◽  
Jin-Kun Liu ◽  
Changyin Sun

2018 ◽  
Vol 25 (4) ◽  
pp. 834-850 ◽  
Author(s):  
H. MoradiMaryamnegari ◽  
A.M. Khoshnood

Designing a controller for multi-body systems including flexible and rigid bodies has always been one of the major engineering challenges. Equations of motion of these systems comprise extremely nonlinear and coupled terms. Vibrations of flexible bodies affect sensors of rigid bodies and might make the system unstable. Introducing a new control strategy for designing control systems which do not require the rigid–flexible coupling model and can dwindle vibrations without sensors or actuators on flexible bodies is the purpose of this paper. In this study, a spacecraft comprising a rigid body and a flexible panel is used as the case study, and its equations of motion are extracted using Lagrange equations in terms of quasi-coordinates. For oscillations on a rigid body to be eliminated, a frequency estimation algorithm and an adaptive filtering are used. A controller is designed based on the rigid model of the system, and then robust stability conditions for the rigid–flexible system are obtained. The conditions are also developed for the spacecraft with more than one active frequency. Finally, the robust adaptive vibration control system is simulated in the presence of resonance. Simulations’ results indicate the advantage of the control method even when several active frequencies simultaneously resonate the dynamics system.


2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Trong-Toan Tran ◽  
Tan-No Nguyen ◽  
Duc-Duy Nguyen ◽  
Viet-Long Nguyen ◽  
Nguyen-Vu Truong

This paper addresses the problem of nonlinear robust adaptive output feedback controller for a class of underactuated aerial vehicles with input and output constraints. To solve the problem, the modular design strategy is proposed for the control design. By using the neural networks (NNs) to approximate system uncertainties and observers to reconstruct system states, robust adaptive output feedback controllers are developed. By using a combination of saturation functions and barrier functions, input and output constraints are simultaneously dealt with. The design methodology shows that a cascaded system of an input-to-state stable (ISS) subsystem driven by an ultimate bounded (UB) subsystem enjoys ultimate boundedness property. In addition, the tracking error converges to adjustable neighbourhoods of the origin.


2021 ◽  
pp. 1-11
Author(s):  
Wei He ◽  
Fengshou Kang ◽  
Linghuan Kong ◽  
Yanghe Feng ◽  
Guangquan Cheng ◽  
...  

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