The performance optimization of induction motor speed control system is studied and self-tuning PID controller based on diagonal recurrent neural network (DRNN) is presented in this paper. Neural network control does not require the precise mathematical model of the system, and it only needs to train neural network online or offline, then use the training results to design the control system. It is applicable of the nonlinear, strong coupling and multi variable system, which is composed of inverter and induction motor. The speed regulation control performances are tested on the experimental platform constructed by SIMATIC S7-300 power PLC. The results of experiment indicate that, compared with conventional PID controller, induction motor speed control system, which is controlled by self-tuning PID controller based on DRNN, has better static-dynamic and following performances, stronger anti-interference ability and robustness.
목차
Abstract 1. Introduction 2. Mathematical Model 0f Induction Motor Speed Control System 3. The Application of Neural Network Control in Induction Motor Speed Control System 3.1. Self-Tuning PID Controller Based on DRNN 4. Experiments 4.1. System Composition 4.2. Design of Structured Program 4.3. Realization of the System Communication 4.4. Experimental Results and its Analysis 5. Conclusion References
보안공학연구지원센터(IJCA) [Science & Engineering Research Support Center, Republic of Korea(IJCA)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Control and Automation
간기
월간
pISSN
2005-4297
수록기간
2008~2016
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Control and Automation Vol.8 No.10