Negative impedance stabilizing controls for PWM DC-DC converters using feedback linearization techniques

Author(s):  
A. Emadi ◽  
M. Ehsani
2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
Hai-Yan Li ◽  
Yun-An Hu ◽  
Jian-Cun Ren ◽  
Min Zhu

For a class of MIMO nonaffine block nonlinear systems, a neural network- (NN-) based dynamic feedback backstepping control design method is proposed to solve the tracking problem. This problem is difficult to be dealt with in the control literature, mainly because the inverse controls of block nonaffine systems are not easy to resolve. To overcome this difficulty, dynamic feedback, backstepping design, sliding mode-like technique, NN, and feedback linearization techniques are incorporated to deal with this problem, in which the NNs are used to approximate and adaptively cancel the uncertainties. It is proved that the whole closed-loop system is stable in the sense of Lyapunov. Finally, simulations verify the effectiveness of the proposed scheme.


2010 ◽  
Vol 57 (2) ◽  
pp. 345-354 ◽  
Author(s):  
Jangheon Kim ◽  
Changjoon Park ◽  
Junghwan Moon ◽  
Bumman Kim

2005 ◽  
Vol 128 (3) ◽  
pp. 473-481 ◽  
Author(s):  
Z. Doulgeri ◽  
A. Golfakis

This paper refers to the control of the position and contact forces of a compliant rectangular object grasped by a pair of robot fingers for the planar case, using input-output feedback linearization techniques. Point contact with friction is assumed and the linearizing control is designed for the case of controlling the object position and grasping force and then extended to include the constraint forces and the object orientation. In the last case, an appropriate output transformation is proposed to avoid the singularity of the decoupling matrix and apply the method successfully. This work considers the planar case and provides simulation results that confirm the theoretical findings.


Sign in / Sign up

Export Citation Format

Share Document