|Table of Contents|

Vehicle path and speed tracking control of robotdriver based on fuzzy immune PID(PDF)


Research Field:
Publishing date:


Vehicle path and speed tracking control of robotdriver based on fuzzy immune PID
Wang JiweiChen GangWang Jun
School of Mechanical Engineering,Nanjing University of Science and Technology,Nanjing 210094,China
robot driver path tracking speed tracking fuzzy control immune control proportional integration differential control
A control method based on fuzzy immune proportional integration differential(PID)is proposed to realize the path and speed tracking control of a vehicle drove by a robot driver.A fuzzy immune proportional path tracking controller controls the steering manipulator on the steering wheel by calculating the lateral deviation between the expected vehicle path and the actual vehicle path.A fuzzy immune PID speed tracking controller controls the brake/accelerator mechanical leg on the brake/accelerator pedal respectively by calculating the deviation of expected speed and actual speed.The longitudinal speed control and the vehicle steering control are decoupled by updating the vehicle lateral acceleration gain of the vehicle speed feedback.The co-simulation results of Carsim/Simulink reveal the maximum error of vehicle path tracking and vehicle speed tracking is 0.28 m and 1 km/h.


[1] Chen Gang,Zhang Weigong.Hierarchical coordinated control method for unmanned robot applied to automotive test[J].IEEE Transactions on Industrial Electronics,2016,63(2):1039-1051.
[2]Nicholas W,Christopher C,Karl S,et al.Development of a robotic driver for autonomous vehicle following[J].International Journal of Intelligent Systems Technologies and Applications,2010,8(1-4):276-287.
Xiong Bo,Qu Shiru.Intelligent vehicle’s path tracking based on fuzzy control[J].Journal of Transportation Systems Engineering and Information Technology,2010,10(2):70-75.
[4]Qu Ting,Chen Hong,Ji Yan,et al.Modeling driver steering control based on stochastic model predictive control[C]//IEEE International Conference on Systems,Man,and Cybernetics.Manchester,UK:IEEE,2013:3704-3709.
[5]Zhang Weizhong,Chen Gang,Hu Liming,et al.Research of vehicle trajectory tracking based on human-simulated intelligent control[C]//Machinery,Materials Science and Engineering Applications.Wuhan,China:TTP Press,2014:375-379.
[7]Chen Gang,Zhang Weigong,Zhang Xiaona.Fuzzy neural control for unmanned robot applied to automotive test[J].Industrial Robot—An International Journal,2013,40(5):450-461.
Chen Gang,Zhang Weigong,Chang Siqin.Fuzzy velocity tracking control of vehicle robot driver[J].Journal of Nanjing University of Science and Technology,2012,36(2):226-231.
[9]Guo Konghui,Ding Haitao,Zhang Jianwei,et al.Development of a longitudinal and lateral driver model for autonomous vehicle control[J].International Journal of Vehicle Design,2004,36(1):50-65.
Bai Yu,Sang Nan.Vehicle variable ratio steering control based on active disturbance rejection technology[J].Journal of Nanjing University of Science and Technology,2015,39(4):452-459.
Guan Xin,Cui Wenfeng,Jia Xin.Vehicle longitudinal speed split-phase control[J].Journal of Jilin University,2013,43(2):273-277.


Last Update: 2017-12-31