Optimal iterative learning control design for generator voltage regulation system
The purpose of this paper is to design a good tracking controller for the generator automatic voltage regulator (AVR) system. It uses an iterative learning control (ILC) algorithm as a control rule and tries to keep voltage error as low as possible, while replying to set point changes as fast as possible. Two models of ILC are discussed: P-type learning and linear quadratic (LQ) optimal design. The results of designing by LQ optimal method are compared with a Ziegler-Nichols proportional-integral-derivative (PID) controller. The effects of changing different parameters are investigated and illustrated by simulation. In order to provide better robustness for the design, a PID-ILC parallel structure is designed and simulated under system parameter changes.
iterative learning control automatic voltage regulation linear quadratic optimal control