TIME-DELAY FEEDBACK CONTROL OF COMPLEX PATHOLOGICAL RHYTHMS IN AN ATRIOVENTRICULAR CONDUCTION MODEL

2000 ◽  
Vol 10 (12) ◽  
pp. 2781-2784 ◽  
Author(s):  
MICHAEL E. BRANDT ◽  
GUANRONG CHEN

We describe the emergence of complex cardiac rhythms in a nonlinear model of the atrioventricular (AV) nodal conduction system, and a method based on linear time-delay feedback (LTDF) control for suppressing them. The LTDF controller is effective at suppressing these rhythms by stabilizing the map to one of a set of unstable fixed points. Additionally, we show that the method is robust to both measurement error and experimental noise.

1997 ◽  
Vol 56 (2) ◽  
pp. R1334-R1337 ◽  
Author(s):  
Michael E. Brandt ◽  
Hue-Teh Shih ◽  
Guanrong Chen

Author(s):  
Kaiwei Wu ◽  
Chuanbo Ren ◽  
Yuanchang Chen

Time-delay feedback control can effectively broaden the damping frequency band and improve the damping efficiency. However, the existing time-delay feedback control strategy has no obvious effect on multi-frequency random excitation vibration reduction control. That is, when the frequency of external excitation is more complicated, there is no better way to obtain the best time-delay feedback control parameters. To overcome this issue, this paper is the first work of proposing an optimal calculation method that introduces stochastic excitation into the process of solving the delay feedback control parameters. It is a time-delay control parameter with a better damping effect for random excitation. In this paper, a 2 DOF one-quarter vehicle suspension model with time-delay is studied. First, the stability interval of time-delay feedback control parameters is solved by using the Lyapunov stability theory. Second, the optimal control parameters of the time-delay feedback control under random excitation are solved by particle swarm optimization (PSO). Finally, the simulation models of a one-quarter vehicle suspension simulation model are established. Random excitation and harmonic excitation are used as inputs. The response of the vehicle body under the frequency domain damping control method and the proposed control method is compared and simulated. To make the control precision higher and the solution speed faster, this paper simulates the model by using the precise integration method of transient history. The simulation results show that the acceleration of the vehicle body in the proposed control method is 13.05% less than the passive vibration absorber under random excitation. Compared with the time-delay feedback control optimized by frequency response function, the damping effect is 12.99%. The results show that the vibration displacement, vibration velocity, and vibration acceleration of the vehicle body are better than the frequency domain function optimization method, whether it is harmonic excitation or random excitation. The ride comfort of the vehicle is improved obviously. It provides a valuable tool for time-delay vibration reduction control under random excitation.


2014 ◽  
Vol 541-542 ◽  
pp. 1248-1255
Author(s):  
Jiang Xu ◽  
Tao Li

In various kinds of feedback control, delayed control is an important topic for chaos control, which deserves more thorough researches. However, only a few researchers take in to account that whether the delayed feedback control (DFC) can be employed to control chaotic systems with time-delay. To investigate the control strategy, a stabilization problem of unstable fixed points in the discrete time-delay system is taken into considerations in this paper. Based on our conclusion, it is obvious that the odd number limitation property existing in the system without delay also exists in the time-delay one while the DFC is employed to stabilize the unstable fixed points. Second, based on the property of the root-locus diagram, a developed DFC strategy is proposed to release the limitation. The numerical simulation results validate the effectiveness of our design and are in agreement of our analysis.


2003 ◽  
Vol 36 (19) ◽  
pp. 209-214 ◽  
Author(s):  
Takehito Azuma ◽  
Hiroyuki Naito ◽  
Seiichi Sagara ◽  
Masayuki Fujita ◽  
Kenko Uchida

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