경사 감소 학습에 기초한 적응 PID 제어기 설계

An Adaptive PID Controller Design based on a Gradient Descent Learning

  • 박진현 (진주산업대학교 메카트로닉스공학과) ;
  • 김현덕 (진주산업대학교 전자공학과) ;
  • 최영규 (부산대학교 전자전기정보컴퓨터공학부)
  • 발행 : 2006.02.01

초록

본 연구에서는 구조가 단순한 PID 제어기의 장점을 살리고, 시스템 파라메터의 변동에 대하여 강인성 성능을 내는 온라인 적응 PID 제어 시스템을 개발하고자 한다. 또한, 제안된 적응 제어 시스템의 초기 제어 구간에서 안정한 스타트-엎(start-up)을 보장하기 위하여 초기 제어기의 이득을 적절한 이득으로 설정하고, 그 이득의 변화량을 경사 감소법에 의하여 학습하는 방법으로 수정 제안하고자 한다. 제안된 적응 PID제어기의 성능 평가를 위하여 비선형 DC 모터의 가변 속도제어에 적용하고, 결과를 모의실험을 통하여 보이고자한다.

PID controller has been widely used in industry. Because it has a simple structure and robustness to modeling error. But it is difficult to have uniformly good control performance in system parameters variation or different velocity command. In this paper, we propose an adaptive PID controller based on a gradient descent learning. This algorithm has a simple structure like conventional PID controller and a robustness to system parameters variation and different velocity command. To verify performances of the proposed adaptive PID controller, the speed control of nonlinear DC motor is performed. The simulation results show that the proposed control systems are effective in tracking a command velocity under system parameters variation.

키워드

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