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Path following controller for mobile robots based on neural network backstepping


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Path following controller for mobile robots based on neural network backstepping
Jia Heming1Song Wenlong1Chen Ziyin2Yang Xin1Duan Haiqing2
1.College of Mechanical and Electrical Engineering,Northeast Forestry University,Harbin 150040,China; 2.College of Automation,Harbin Engineering University,Harbin 150001,China
wheeled mobile robot path following control neural network backstepping
In order to implement the path following control of wheeled mobile robot with non-holonomic constraint,a backstepping method is designed based on feedback gain technique.Through the tuning of the controller's parameters,the nonlinear terms in error dynamic robot model can be eliminated,and the form of designed controller can be much simpler.Neural network is adopted to compensate the model uncertainties.An adaptive robust controller is designed to compensate the estimated error of neural network on-line,and the learning performance of neural network can be optimized.The simulation results illustrate that the parameters of controller are easy to be adjusted,and can make wheeled mobile robot track the desired arbitrary path precisely.


[1] 王义萍,陈庆伟,胡维礼.基底神经节的尖峰神经元网络模型及其在机器人中的应用[J].南京理工大学学报,2010,34(6):717-722.Wang Yiping,Chen
Wang Yiping,Chen Qingwei,Hu Weili.Spiking neuron network model of basal ganglia and its application in robot[J].Journal of Nanjing University of Science and Technology,2010,34(6):717-722.
Wang Jian,Zhang Xiaowei,Yang Jing.Design and implementation of a self-tracking smart car based on visual sensor[J].Industrial Instrument and Automation,2010,6(1):34-44.
[3]Jiang Z P,Nijmeijer H.Tracing control of mobile robots:a case study in backstepping[J].Automatica,1997,33(7):1393-1399.
[4]Jiang Z P,Nijmeijer H.A recursive technique for tracking control of nonholonomic systems in chained form[J].IEEE Transactions on Automatic Control,1999,44(2):265-279.
Dong Wenjie,Huo Wei.Trajectory tracking control of chained systems[J].Acta Automatica Sinica,2000,26(3):310-316.
[6]Djapic V,Farrell J,Dong Wenjie.Land vehicle control using a command filtered backstepping approach[A].American Control Conference[C].Seattle,USA:IEEE,2008:2461-2466.
[7]Pu Shi,Zhao Yiwen,Cui Yujie.Modeling and control of wheeled mobile robot based on hybrid automata[A].2010 Chinese Control and Decision Conference[C].Xuzhou,China:IEEE,2010:3375-3379.
Fang Hao,Dou Lihua,Chen Jie.Sliding reconstruction and anti-sliding control of wheeled mobile robots[J].Control and Decision,2010,25(5):701-705.
Gu Yikun,Ni Fenglei,Liu Hong.Flexible-joint manipulator adaptive control based on recurrent Elman neural networks and dynamic surface approach[J].Control and Decision,2011,26(12):1783-1790.
Liu Shuguang,Sun Xiuxiang,Dong Wenhan,et al.Simplified adaptive neural dynamic surface control for a class of nonlinearsystems in pure feedback form[J].Control and Decision,2012,27(2):266-270.
Wu Zhongqiang,Xia Qing,Peng Yan,et al.Backstepp-ing dynamic surface control for high-order nonlinear hydraulic roll gap system[J].Chinese Journal of Scientific Instrument,2012,33(4):949-954.
Zou Xiyong,Xu De,Li Ziyin.Piecewise fuzzy control for path tracking of nonholonomic mobile robots[J].Control and Decision,2008,23(6):655-659.
[13]Micaelli A,Samson C.Trajectory tracking for unicycle-type and two-steering wheels mobile robots[R].Technical Report No.2097,INRIA,Sophia-Antipolis,France,1993.


Last Update: 2014-02-28