摘要
针对双轮自平衡机器人的运动控制,设计了区间二型模糊逻辑控制器(T2FLC),提出函数融合的方法,解决模糊控制器规则繁杂的问题。首先对双轮机器人进行运动学建模,针对机器人的数学模型,设计双闭环二型模糊自适应PID控制器,分别控制机器人的直立平衡和行走速度。将机器人的反馈变量进行函数融合,简化T2FLC的模糊规则。对设计的控制器进行仿真,结果表明T2FLC比PID控制器具有更快的响应速度。进一步考虑输入扰动和机器人数学模型参数不确定对控制器的影响,仿真表明T2FLC具有更好的抗干扰能力和更强的鲁棒性。
An interval type-2 fuzzy logic controller(T2 FLC) was designed for the motion control of a two-wheeled self-balancing robot. A method of function fusion was proposed to solve the complex rules of the fuzzy controller. Firstly, the kinematics model of the two-wheeled robot was built. Based on the mathematical model of the robot, a double closed-loop type-2 fuzzy adaptive PID controller was designed to control the upright balance and walking speed of the robot respectively. The feedback variables of the robot were fused with functions to simplify the fuzzy rules of T2 FLC. The simulation results show that T2 FLC has a faster response speed than the PID controller. The influence of input disturbance and parameter uncertainty of the mathematical model on the controller is considered. Simulation results show that T2 FLC has a better anti-interference ability and stronger robustness.
作者
黄泽琼
谢小鹏
HUANG Ze-qiong;XIE Xiao-peng(School of Mechanical&Automotive Engineering,South China University of Technology,Guangzhou Guangdong 510641,China)
出处
《计算机仿真》
北大核心
2022年第2期380-386,共7页
Computer Simulation
基金
2018年度广东省高等教育教学改革项目(2018049)。
关键词
信息融合
模糊集
区间二型模糊逻辑控制
双轮自平衡机器人
自适应控制
Information fusion
Fuzzy set
Interval type-2 fuzzy logic control
Two-wheeled self-balanced robot
Adaptive control
