Multi-agent source seeking via discrete-time extremum seeking control

Automatica ◽  
2014 ◽  
Vol 50 (9) ◽  
pp. 2312-2320 ◽  
Author(s):  
Sei Zhen Khong ◽  
Ying Tan ◽  
Chris Manzie ◽  
Dragan Nešić
Keyword(s):  
Discrete Time ◽  
Extremum Seeking ◽  
Extremum Seeking Control ◽  
Source Seeking ◽  
Multi Agent

scholarly journals Extremum Seeking Control for Discrete-Time with Quantized and Saturated Actuators

Processes ◽  
2019 ◽  
Vol 7 (11) ◽  
pp. 831
Author(s):  
Martin Guay ◽  
Daniel J. Burns
Keyword(s):  
Discrete Time ◽  
Input Saturation ◽  
Estimation Algorithm ◽  
Extremum Seeking ◽  
Input Constraints ◽  
Bias Estimation ◽  
Extremum Seeking Control ◽  
Probing Signal ◽  
Excitation Conditions ◽  
System Approaches

This paper proposes an extremum-seeking controller (ESC) design for a class of discrete-time nonlinear control systems subject to input constraints or quantized inputs. The proposed method implements a proportional-integral ESC design along with a discrete-time anti-windup mechanism. The anti-windup enforces input saturation while preserving the input dither signal. The technique incorporates a mechanism for adjusting the amplitude of the extremum seeking control dither signal. This mechanism ensures that any violation of constraints due to the dither signal is removed while maintaining the probing signal active. An amplitude update routine is also proposed. The amplitude update is coupled with a saturation bias estimation algorithm that correctly accounts for the inherent bias associated with systems operated at or near saturation conditions. The amplitude update is designed to remove the dither signal when the system approaches the optimum. It also ensures that a lower bound of the amplitude is enforced to guarantee that excitation conditions are maintained.

Multi-agent gradient climbing via extremum seeking control

2014 ◽  
Vol 47 (3) ◽  
pp. 9973-9978 ◽  
Author(s):  
Sei Zhen Khong ◽  
Chris Manzie ◽  
Ying Tan ◽  
Dragan Nešić
Keyword(s):  
Extremum Seeking ◽  
Extremum Seeking Control ◽  
Multi Agent
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