双车把两轮车机器人同步摆把平衡控制研究
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摘要
针对一种具有两个车把的双轮车机器人系统,提出在同步转动车把的情况下使其保持平衡的方法。采用査普雷金方程建立系统的欠驱动力学模型;根据部分反馈线性化原理将车轮转角线性化,并选择车轮转角为控制输入,设计出系统在原地摆把定车和曲线行进的平衡控制器;针对控制器参数漂移对系统的影响的问题,引入模糊算法对其进行在线整定以提高控制效果。对车把在±45°范围内转动时的原地和行进中平衡运动控制进行数值仿真研究。结果表明:车架俯仰角经快速调整可以由初始的倾角恢复到平衡位置,并且引入模糊算法参数整定的控制器具有更短的调整时间和较小的超调量。物理样机试验进一步验证了所提的控制器设计的有效性。
This paper presents the strategy to balance a two-bared and two-wheeled vehicle robot under synchronously turning its two bars. Dynamics model of the vehicle robot was established by Chaplygin Formulation. As for the balance controller, the running angle of the robot's wheel was linearized by partial feedback linearization method, and the running angle of the two wheels was taken as input. Moreover,considering the undesirable influence of the drifting controller parameters, a fuzzy algorithm was adopted to tuning these parameters online. On the condition that the handlebars being turn between ±45°, the mode switching numerical simulations of the track-stand motion and the forward movement were performed. The results show that, the pitch angle of the frame can rapidly turn back to a balanced state, and the controller with the fuzzy algorithm has shorter adjustment time and smaller overshoot. Physical prototype experiments further testify the effectiveness of the controlling strategy.
This paper presents the strategy to balance a two-bared and two-wheeled vehicle robot under synchronously turning its two bars. Dynamics model of the vehicle robot was established by Chaplygin Formulation. As for the balance controller, the running angle of the robot's wheel was linearized by partial feedback linearization method, and the running angle of the two wheels was taken as input. Moreover,considering the undesirable influence of the drifting controller parameters, a fuzzy algorithm was adopted to tuning these parameters online. On the condition that the handlebars being turn between ±45°, the mode switching numerical simulations of the track-stand motion and the forward movement were performed. The results show that, the pitch angle of the frame can rapidly turn back to a balanced state, and the controller with the fuzzy algorithm has shorter adjustment time and smaller overshoot. Physical prototype experiments further testify the effectiveness of the controlling strategy.
引文
[1]郭磊,魏世民,孟祥珺.一种变结构自平衡两轮车[P].北京:CN102582738A,2012-07-18.Guo L,Wei S M,Mneg X J.Variable Structure Self Balancing Two Wheeled Vehicle[P].Beijing:Beijing University of Posts and Telecommunications,2012.
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[4]Sikander A,Prasad R.Reduced Order Modelling Based Control of Two Wheeled Mobile Robot[J].Journal of Intelligent Manufacturing,2017,30(03):1-11.
[5]CHI Chenghung,CHOU Juijen.Riderless Bicycle with Gyroscopic Balancer Controlled by FSMC and AFSMC[C]//7th International Congress on Ultra Modern Telecommu-nications and Control Systems and Workshops,October 6-8,2015,Brno:IEEE,2015:150-157.
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[7]阮晓钢,李世臻,侯旭阳,等.基于非线性PID的柔性两轮机器人运动控制[J].控制工程,2012,19(03):498-501.Ruan X G,Li S Z,Hou X Y,et al.Motion Balancing Control of Flexible Two-wheeled Robot Based on Nonlinear PID[J].Control Engineering of China,2012,03:498-501.
[8]茅力非.两轮自平衡移动机器人建模与控制研究[D].武汉:华中科技大学,2013.Mao L F.Study on Modeling and Control of Two-wheeled Self Balancing Mobile Robot[D].Wuhan:Huazhong University of Science and Technology,2013.
[9]Xiangjun Meng.Analysis of Nonholonomic Constraints About a Variable Structure Bicycle Robot[C].2012 IEEE International Conference on Automation and Logistics,15-17 Aug.2012,Zheng Zhou,China,2012:628-633.
[10]CUI Yanbo,GUO Lei,WEI Shimin,et al.Design and Implementation of a kind of Neural Networks Robustness Controller for Variable Structure Bicycle Robot's Track-stand Motion[C]//2014 IEEEInternational Conference on Information and Automation,July 28-30,2014,Hailar:IEEE,2014:689-694.
[2]Li J,Wei S,Guo L,et al.Adaptive Fuzzy Control of a Front-wheel Drive Bicycle Robot[C]//Cloud Computing and Intelligence Systems(CCIS),2016 4th International Conference on.IEEE,2016:113-116.
[3]Yin S,Yamakita M.Passive Velocity Field Control Approach to Bicycle Robot Path Following[C]//Society of Instrument and Control Engineers of Japan(SICE),2016 55th Annual Conference of the.IEEE,2016:1654-1659.
[4]Sikander A,Prasad R.Reduced Order Modelling Based Control of Two Wheeled Mobile Robot[J].Journal of Intelligent Manufacturing,2017,30(03):1-11.
[5]CHI Chenghung,CHOU Juijen.Riderless Bicycle with Gyroscopic Balancer Controlled by FSMC and AFSMC[C]//7th International Congress on Ultra Modern Telecommu-nications and Control Systems and Workshops,October 6-8,2015,Brno:IEEE,2015:150-157.
[6]HUANG Yonghua,LIAO Qizheng,GUO Lei,et al.Simple Realization of Balanced Motions Under Different Speeds for a Mechanical Regulator-free Bicycle Robot[J].Robotica,2015,33(9):1958-1972.
[7]阮晓钢,李世臻,侯旭阳,等.基于非线性PID的柔性两轮机器人运动控制[J].控制工程,2012,19(03):498-501.Ruan X G,Li S Z,Hou X Y,et al.Motion Balancing Control of Flexible Two-wheeled Robot Based on Nonlinear PID[J].Control Engineering of China,2012,03:498-501.
[8]茅力非.两轮自平衡移动机器人建模与控制研究[D].武汉:华中科技大学,2013.Mao L F.Study on Modeling and Control of Two-wheeled Self Balancing Mobile Robot[D].Wuhan:Huazhong University of Science and Technology,2013.
[9]Xiangjun Meng.Analysis of Nonholonomic Constraints About a Variable Structure Bicycle Robot[C].2012 IEEE International Conference on Automation and Logistics,15-17 Aug.2012,Zheng Zhou,China,2012:628-633.
[10]CUI Yanbo,GUO Lei,WEI Shimin,et al.Design and Implementation of a kind of Neural Networks Robustness Controller for Variable Structure Bicycle Robot's Track-stand Motion[C]//2014 IEEEInternational Conference on Information and Automation,July 28-30,2014,Hailar:IEEE,2014:689-694.