Analysis and design of IMC-PI Controller with faster set point tracking and disturbance rejection for Interleaved DC-DC SEPIC converter based Power Factor Correction

2020 ◽  
Vol 11 (1) ◽  
pp. 1
Author(s):  
Komathi Chandraselvam ◽  
Umamaheswari M.G
Keyword(s):  
Power Factor ◽  
Disturbance Rejection ◽  
Power Factor Correction ◽  
Pi Controller ◽  
Set Point ◽  
Analysis And Design ◽  
Point Tracking

scholarly journals A Modified 2-DOF Control Framework and GA Based Intelligent Tuning of PID Controllers

Processes ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 423
Author(s):  
Gun-Baek So
Keyword(s):  
Disturbance Rejection ◽  
Pid Controller ◽  
Weighting Function ◽  
Pid Controllers ◽  
Set Point ◽  
Tuning Method ◽  
Point Tracking ◽  
Load Disturbance ◽  
Control Framework ◽  
Feedforward Controller

Although a controller is well-tuned for set-point tracking, it shows poor control results for load disturbance rejection and vice versa. In this paper, a modified two-degree-of-freedom (2-DOF) control framework to solve this problem is proposed, and an optimal tuning method for the pa-rameters of each proportional integral derivative (PID) controller is discussed. The unique feature of the proposed scheme is that a feedforward controller is embedded in the parallel control structure to improve set-point tracking performance. This feedforward controller and the standard PID con-troller are combined to create a new set-point weighted PID controller with a set-point weighting function. Therefore, in this study, two controllers are used: a set-point weighted PID controller for set-point tracking and a conventional PID controller for load disturbance rejection. The parameters included in the two controllers are tuned separately to improve set-point tracking and load dis-turbance rejection performances, respectively. Each controller is optimally tuned by genetic algo-rithm (GA) in terms of minimizing the IAE performance index, and what is special at this time is that it also tunes the set-point weighting parameter simultaneously. The simulation results performed on four virtual processes verify that the proposed method shows better performance in set-point tracking and load disturbance rejection than those of the other methods.

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