Design of PID controller with incomplete derivation based on ant system algorithm

被引:0
|
作者
Guanzheng TAN
机构
基金
中国国家自然科学基金;
关键词
PID controller; Incomplete derivation; Parameter tuning; Ant system algorithm; Genetic algorithm; Simulated annealing;
D O I
暂无
中图分类号
TP273.4 [];
学科分类号
080201 ; 0835 ;
摘要
A new and intelligent design method for PID controller with incomplete derivation is proposed based on the ant system algorithm (ASA) . For a given control system with this kind of PID controller, a group of optimal PID controller parameters Kp* , Ti*. and Td* can be obtained by taking the overshoot, settling time, and steady-state error of the system’s unit step response as the performance indexes and by use of our improved ant system algorithm. Kp* , Ti* , and Td* can be used in real-time control. This kind of controller is called the ASA-PID controller with incomplete derivation. To verify the performance of the ASA-PID controller, three different typical transfer functions were tested, and three existing typical tuning methods of PID controller parameters,including the Ziegler-Nichols method (ZN),the genetic algorithm (GA),and the simulated annealing (SA).were adopted for comparison. The simulation results showed that the ASA-PID controller can be used to control different objects and has better per
引用
收藏
页码:246 / 252
页数:7
相关论文
共 50 条
  • [1] Design of PID controller with incomplete derivation based on ant system algorithm
    Guanzheng Tan
    Qingdong Zeng
    Wenbin Li
    Journal of Control Theory and Applications, 2004, 2 (3): : 246 - 252
  • [2] Design of PID controller with incomplete derivation based on differential evolution algorithm
    Wu Lianghong1
    2. Coll. of Electric and Information Engineering
    Journal of Systems Engineering and Electronics, 2008, (03) : 578 - 583
  • [3] Design of PID controller with incomplete derivation based on differential evolution algorithm
    Wu Lianghong
    Wang Yaonan
    Zhou Shaowu
    Tan Wen
    JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS, 2008, 19 (03) : 578 - 583
  • [4] Adaptive and robust design for PID controller based on ant system algorithm
    Tan, GZ
    Zeng, QD
    He, SJ
    Cai, GC
    ADVANCES IN NATURAL COMPUTATION, PT 3, PROCEEDINGS, 2005, 3612 : 915 - 924
  • [5] Optimal design of PID controller using modified ant colony system algorithm
    Zeng, Qingdong
    Tan, Guanzheng
    ICNC 2007: THIRD INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 5, PROCEEDINGS, 2007, : 436 - +
  • [6] Modified ant colony optimization based PID controller design for coupled tank system
    Chauhan, Sumika
    Singh, Bhawana
    Singh, Manmohan
    ENGINEERING RESEARCH EXPRESS, 2021, 3 (04):
  • [7] Optimization Algorithm Based PID Controller Design for a Magnetic Levitation System
    Dey, Soham
    Dey, Jayati
    Banerjee, Subrata
    2020 IEEE CALCUTTA CONFERENCE (CALCON), 2020, : 258 - 262
  • [8] Regulation of PID controller parameters based on ant colony optimization algorithm in bending control system
    Yu Yuzhen
    Ren Xinyi
    Deng Chunyan
    Yu Jingjing
    Li Shuzhen
    Shi Junjie
    MEASURING TECHNOLOGY AND MECHATRONICS AUTOMATION IV, PTS 1 AND 2, 2012, 128-129 : 205 - +
  • [9] Design of ant algorithm-based optimal PID controller and its application to intelligent artificial leg
    Tan, Guan-Zheng
    Li, Wen-Bin
    Zhongnan Gongye Daxue Xuebao/Journal of Central South University of Technology, 2004, 35 (01):
  • [10] CAS algorithm-based optimum design of PID controller in AVR system
    Zhu, Hui
    Li, Lixiang
    Zhao, Ying
    Guo, Yu
    Yang, Yixian
    CHAOS SOLITONS & FRACTALS, 2009, 42 (02) : 792 - 800