Neural control of a nonlinear system with inherent time delays

Author(s):  
Edward A. Rietman ◽  
Robert C. Frye
Author(s):  
Shuli Guo ◽  
Shaoze Yan ◽  
Shizhu Wen

The time delay of Lurie nonlinear system is systems is estimated in which the origin of the nonlinear systems is absolute stability by using a Liapunov-Razumikhn function. Many sufficient conditions are obtained about absolute stability criteria of nonlinear systems. A example is presented to explain the strange time delay phenomena.


Author(s):  
YF Zhang ◽  
S Zhang ◽  
FX Liu ◽  
C Zhou ◽  
YJ Lu ◽  
...  

A rotor system with double time delays supported by the high-speed self-acting gas-lubricated bearings with three-axial grooves is modeled to implement active delay control of the system. The differential transformation method is employed to solve the time-dependent compressible gas Reynolds equation due to its rapid convergence rate and minimal calculation error. Based on the precise integration method, a calculation method is proposed to analyze the dynamic responses of a gas bearing-rotor nonlinear system with time delays. The motion analysis of the self-acting gas-lubricated bearing-rotor system with double time delays is implemented by the orbit diagrams, the time series, and the phase diagrams. The influence of time delays and feedback control gains on the dynamic responses of the bearing-rotor nonlinear system is analyzed. The numerical results show that the amplitude of the responses of the system with time delays control is reduced, the motion is more stable and good control effect is achieved when the chosen feedback control gains match the time delays of the bearing-rotor system.


2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Wei Zheng ◽  
Hong-bin Wang ◽  
Zhi-ming Zhang

This paper addresses the dynamic output feedback control problem for a class of discrete system with uncertainties and multiple time-delays. First, the system is decomposed into two subsystems based on the output matrix and input control matrix. Secondly, a dynamic compensator is employed for the first subsystem, and then, given the multiple uncertainties, the output feedback controller is designed based on the second subsystem and the dynamic compensator. Thirdly, by choosing the Lyapunov-Krasovskii function, it can be seen that the developed controller makes the closed-loop system convergent to an adjustable region, which can be rendered arbitrary small by adjusting design parameters. Compared with the previous researches, the proposed controller is not only smooth and memoryless, but also only dependent on the system output. Furthermore, with the given dynamic compensator, the controller design conditions are relaxed, while the approach is extended to the conventional nonlinear system. Finally, numerical example is given to illustrate the effectiveness of the theoretical results.


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