A robust adaptive controller design for manipulators with uncertain dynamics

Author(s):  
I.O. Bucak ◽  
F. Gurleyen ◽  
H. Palaz
2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Guoqiang Zhu ◽  
Lingfang Sun ◽  
Xiuyu Zhang

A neural network robust control is proposed for a class of generic hypersonic flight vehicles with uncertain dynamics and stochastic disturbance. Compared with the present schemes of dealing with dynamic uncertainties and stochastic disturbance, the outstanding feature of the proposed scheme is that only one parameter needs to be estimated at each design step, so that the computational burden can be greatly reduced and the designed controller is much simpler. Moreover, by introducing a performance function in controller design, the prespecified transient and performance of tracking error can be guaranteed. It is proved that all signals of closed-loop system are uniformly ultimately bounded. The simulation results are carried out to illustrate effectiveness of the proposed control algorithm.


Author(s):  
Nga Thi-Thuy Vu

This paper presents a robust adaptive controller that does not depend on the system parameters for an excavator arm. Firstly, the model of the excavator arm is demonstrated in the Euler-Lagrange form considering with overall excavator system. Next, a robust adaptive controller has been constructed from information of state error. In this paper, the stability of overall system is mathematically proven by using Lyapunov stability theory. Also, the proposed controller is model free then the closed loop system is not affected by disturbances and uncertainties. Finally, the simulation is executed in Matlab/Simulink for both presented scheme and the PD controller under some conditions to ensure that the proposed algorithm given the good performances for all cases.


1992 ◽  
Vol 9 (2) ◽  
pp. 101-112 ◽  
Author(s):  
R.A. Al-Ashoor ◽  
K. Khorasani ◽  
R.V. Patel ◽  
A.J. Al-Khalili

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