Adaptive neural control of MIMO nonlinear state time-varying delay systems with unknown dead-zones and gain signs

Automatica ◽  
2007 ◽  
Vol 43 (6) ◽  
pp. 1021-1033 ◽  
Author(s):  
T.P. Zhang ◽  
S.S. Ge
Keyword(s):  
Neural Control ◽  
Delay Systems ◽  
Time Varying ◽  
Adaptive Neural Control ◽  
Dead Zones ◽  
State Time ◽  
Time Varying Delay ◽  
Varying Delay ◽  
Nonlinear State

Robust Adaptive Neural Control for a Class of Time-Varying Delay Systems with Backlash-like Hysteresis Input

2015 ◽  
Vol 18 (3) ◽  
pp. 1087-1101 ◽  
Author(s):  
Xiuyu Zhang ◽  
Zhi Li ◽  
Chun-Yi Su ◽  
Xinkai Chen ◽  
Jianguo Wang ◽  
...  
Keyword(s):  
Neural Control ◽  
Delay Systems ◽  
Time Varying ◽  
Adaptive Neural Control ◽  
Time Varying Delay ◽  
Robust Adaptive ◽  
Varying Delay

Adaptive neural control for MIMO nonlinear systems with state time-varying delay

2011 ◽  
Vol 10 (3) ◽  
pp. 309-318 ◽  
Author(s):  
Ruliang Wang ◽  
Kunbo Mei ◽  
Chaoyang Chen ◽  
Yanbo Li ◽  
Hebo Mei ◽  
...  
Keyword(s):  
Nonlinear Systems ◽  
Neural Control ◽  
Time Varying ◽  
Adaptive Neural Control ◽  
State Time ◽  
Mimo Nonlinear Systems ◽  
Time Varying Delay ◽  
Varying Delay

scholarly journals Robust Adaptive Control for a Class of Uncertain Nonlinear Systems with Time-Varying Delay

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Ruliang Wang ◽  
Jie Li ◽  
Shanshan Zhang ◽  
Dongmei Gao ◽  
Huanlong Sun
Keyword(s):  
Neural Control ◽  
Tracking Error ◽  
Robust Adaptive Control ◽  
Delay Systems ◽  
Time Varying ◽  
Triangular Form ◽  
Time Varying Delay ◽  
Robust Adaptive ◽  
Error Dynamics ◽  
Varying Delay

We present adaptive neural control design for a class of perturbed nonlinear MIMO time-varying delay systems in a block-triangular form. Based on a neural controller, it is obtained by constructing a quadratic-type Lyapunov-Krasovskii functional, which efficiently avoids the controller singularity. The proposed control guarantees that all closed-loop signals remain bounded, while the output tracking error dynamics converge to a neighborhood of the desired trajectories. The simulation results demonstrate the effectiveness of the proposed control scheme.

Dynamic Surface Neural Control for a Class of Nonlinear Time-Varying Delay Systems Preceded by Unknown Hysteresis

2013 ◽  
Vol 651 ◽  
pp. 937-942 ◽  
Author(s):  
Xiu Yu Zhang ◽  
Cui Ping Liu ◽  
Yan Sun
Keyword(s):  
Neural Control ◽  
Tracking Error ◽  
Dynamic Surface Control ◽  
Delay Systems ◽  
Time Varying ◽  
Dynamic Surface ◽  
Time Varying Delay ◽  
Complexity Problem ◽  
Robust Adaptive ◽  
Varying Delay

In this paper, a new robust adaptive neural dynamic surface control is proposed for a class of time-varying delay nonlinear systems preceded by backlash-like hysteresis. Compared with the present schemes of dealing with time-varying delay and hysteresis input, the main advantages of the proposed scheme are that the prespecified transient and steady state performance of tracking error can be guaranteed for the first time when using DSC to deal with the time-varing delays; the computational burden can be greatly reduced and the explosion of complexity problem inherent in backstepping control can be eliminated. It is proved that the new scheme can guarantee all the closed-loop signals semi-globally uniformly ultimate bounded. Simulation results are presented to demonstrate the validity of the proposed scheme.

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