Distributed adaptive output consensus tracking control of higher-order systems with unknown control directions

2016 ◽  
Author(s):  
Gang Wang ◽  
Chaoli Wang
Keyword(s):  
Tracking Control ◽  
Higher Order ◽  
Unknown Control Directions ◽  
Consensus Tracking ◽  
Unknown Control

scholarly journals Distributed Adaptive Neural Consensus Tracking Control for Multiple Euler-Lagrange Systems with Unknown Control Directions

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Fanfeng Meng ◽  
Lin Zhao ◽  
Jinpeng Yu
Keyword(s):  
Tracking Control ◽  
Backstepping Technique ◽  
Computation Complexity ◽  
Parameter Uncertainties ◽  
Tracking Errors ◽  
Unknown Control Directions ◽  
Consensus Tracking ◽  
Complexity Problem ◽  
Adaptive Laws ◽  
Unknown Control

This paper investigates the distributed adaptive neural consensus tracking control for multiple Euler-Lagrange systems with parameter uncertainties and unknown control directions. Motivated by the Nussbaum-type function and command-filtered backstepping technique, the error compensations and neural network approximation-based adaptive laws are established, which can not only overcome the computation complexity problem of backstepping but also make the consensus tracking errors reach to the desired region although the control directions and system nonlinear dynamics are both unknown. Numerical example is given to show the proposed algorithm is effective at last.

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