Design and Implementation of Self-tuning Control Method for the Underwater Spherical Robot

被引：0
|
作者：
He, Yanlin [1 ,2 ]
Guo, Shuxiang [1 ,2 ,3 ]
Shi, Liwei [1 ,2 ]
Xing, Huiming [1 ]
Chen, Zhan [1 ]
Su, Shuxiang [1 ]
机构：
[1] Beijing Inst Technol, Key Lab Convergence Med Engn Syst & Healthcare Te, Minist Ind & Informat Technol, 5 Zhongguancun South St, Beijing 100081, Peoples R China
[2] Beijing Inst Technol, Minist Educ, Key Lab Biomimet Robots & Syst, 5 Zhongguancun South St, Beijing 100081, Peoples R China
[3] Kagawa Univ, Fac Engn, 2217-20 Hayashi Cho, Takamatsu, Kagawa 7608521, Japan
来源：
2017 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION (ICMA) | 2017年
基金：
中国国家自然科学基金;
关键词：
Underwater Spherical Robot; Virtual Prototype; Neutral Network PID Control; Auto-tuning; Cooperative Simulation; SLIDING MODE CONTROLLER; FUZZY;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Considering the complicated disturbance in underwater circumstance, usually it is difficult to solve the control problem when the robot changes its motion state or it is subject to ocean currents, its performance deteriorates since the fixed set of parameters is no longer valid for the new conditions. Thus, in this paper, an auto-tune PID (Proportional + Integral + Derivative)-like controller based on Neural Networks is applied to our amphibious spherical underwater robot, which has a great advantage on processing online for the robot due to their nonlinear dynamics. The Neural Networks (NN) plays the role of automatically estimating the suitable set of PID gains that achieves stability of the system. The NN adjusts online the controller gains that attain the smaller position tracking error. The performance of the NN-based controller is investigated in ADAMS and MATLAB cooperative simulation. The velocity of the spherical robot can be controlled to precisely track desired trajectory in body-fixed coordinate system. Additionally, real time experiments on our underwater spherical robot are conducted to show the effectiveness of the algorithm.
引用
收藏
页码：632 / 637
页数：6
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