Title :
Neural Network Force Control Technique for Four Wheel Driven Snow Blower Robotic Vehicle under Uncertain Environment
Author :
Jung, Seul ; Lasky, Ty ; Hsia, T.C.
Author_Institution :
Dept. of Mechatronics Eng., Chungnam Nat. Univ., Daejeon
Abstract :
In this paper, neural network force control technique is applied to a four wheel driven snow blower vehicle under uncertain environment, unknown stiffness and position. The four wheel driven vehicle is a nonlinear system that is driven by front and rear steering angles independently. The explicit force controller is used to regulate lateral force tracking task with a constant longitudinal velocity. However, the performance of the lateral force tracking task becomes worse when uncertain load from the environment is applied to the vehicle. To improve the force tracking task, neural network is added to compensate for the uncertainties from the environment
Keywords :
force control; mobile robots; neurocontrollers; nonlinear control systems; tracking; constant longitudinal velocity; force controller; four wheel driven snow blower robotic vehicle; front-rear steering angles; lateral force tracking task regulation; neural network force control technique; nonlinear system; uncertain environment; Force control; Mobile robots; Neural networks; Nonlinear systems; Snow; Uncertainty; Vehicle driving; Vehicles; Velocity control; Wheels; Snow blower vehicle; explicit force control; neural network control;
Conference_Titel :
SICE-ICASE, 2006. International Joint Conference
Conference_Location :
Busan
Print_ISBN :
89-950038-4-7
Electronic_ISBN :
89-950038-5-5
DOI :
10.1109/SICE.2006.315595