Output feedback adaptive robust control of hydraulic actuator with friction and model uncertainty compensation

2017 ◽  
Vol 354 (13) ◽  
pp. 5328-5349 ◽  
Author(s):  
Xudong Li ◽  
Jianyong Yao ◽  
Changsheng Zhou
Keyword(s):  
Robust Control ◽  
Output Feedback ◽  
Model Uncertainty ◽  
Adaptive Robust Control ◽  
Hydraulic Actuator ◽  
Uncertainty Compensation

scholarly journals Posture Stabilization of Wheeled Mobile Robot Based on Passivity-Based Robust Switching Control with Model Uncertainty Compensation

2019 ◽  
Vol 9 (23) ◽  
pp. 5233 ◽  
Author(s):  
Jung ◽  
Bang
Keyword(s):  
Robust Control ◽  
Global Convergence ◽  
Model Uncertainty ◽  
Switching Control ◽  
Initial Position ◽  
Wheeled Mobile Robots ◽  
Control Laws ◽  
Rotational Perturbation ◽  
Posture Stabilization ◽  
Uncertainty Compensation

Thisstudy presents apassivity-based robust switching control for the posture stabilization of wheeled mobile robots (WMRs) with model uncertainty. Essentially, this proposed strategy is switching between (1) passivity-based robust control to lead the robot to the neighborhood of local minima with a finite time and (2) another robust control to perturb the w-rotational motion of the WMR before the v-kinetic energy of the WMR become meaningless, thereby, eventually converging to the desired posture. Thus, combining two switching control laws ensures the global convergence of (x,y)-navigation of WMRs from any initial position to desired set. Especially, the inter-switching time is intentionallyselected before the WMR completely loses its mobility, which ensures a strict decrease in (x,y)-navigation potential energy and a better global convergence rate. In addition, this control architecture also includes model uncertainty compensation, often neglected in practice, and analytical study of rotational perturbation was also conducted. The Lyapunov technique and energetic passivity wereutilized to derive this control law. Simulation results are presented to illustrate the effectiveness of the proposed technique. It wasfound from the results that the WMR wasquickly converged to the desired posture even under the presence of model uncertainty.

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