From human to humanoid locomotion—an inverse optimal control approach

2009 ◽  
Vol 28 (3) ◽  
pp. 369-383 ◽  
Author(s):  
Katja Mombaur ◽  
Anh Truong ◽  
Jean-Paul Laumond
2001 ◽  
Vol 11 (03) ◽  
pp. 857-863 ◽  
Author(s):  
EDGAR N. SANCHEZ ◽  
JOSE P. PEREZ ◽  
GUANRONG CHEN

This Letter suggests a new approach to generating chaos via dynamic neural networks. This approach is based on a recently introduced methodology of inverse optimal control for nonlinear systems. Both Chen's chaotic system and Chua's circuit are used as examples for demonstration. The control law is derived to force a dynamic neural network to reproduce the intended chaotic attractors. Computer simulations are included for illustration and verification.


2004 ◽  
Vol 14 (10) ◽  
pp. 3505-3517 ◽  
Author(s):  
HUAGUANG ZHANG ◽  
ZHILIANG WANG ◽  
DERONG LIU

In this paper, the problem of chaotifying the continuous-time fuzzy hyperbolic model (FHM) is studied. By tracking the dynamics of a chaotic system, a controller based on inverse optimal control and adaptive parameter tuning methods is designed to chaotify the FHM. Simulation results show that for any initial value the FHM can track a chaotic system asymptotically.


2015 ◽  
Vol 25 (02) ◽  
pp. 1550031 ◽  
Author(s):  
Edgar N. Sanchez ◽  
David I. Rodriguez

In this paper, a control strategy based on the inverse optimal control approach is applied for pinning weighted complex networks with chaotic systems at their nodes; additionally, a cost functional is minimized. This control strategy does not require to have the same coupling strength for all node connections.


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