Dynamic modeling and adaptive controller design for the track-stand motion of a front-wheel drive bicycle robot under 90 degrees front-bar steering angle

The track stand motion for the bicycle robot with front-wheel drive under 90 degrees front-bar turning angle is analyzed in this paper. A kind of dynamic model is proposed based on Appell Equation. To achieve the goal of track stand motion control, the controller is designed based on RBF neural network and adaptive sliding mode control algorithm. And the computer simulation is carried out based on MATLAB to compare the stable equilibrium motion of the robot without interference and under interference separately. The validity of the dynamic model and the control algorithm are testified by the simulation results. And the coefficients in the controller can be tuned automatically. The uncertainties in the model are estimated by the RBF neural network so that the controller is adaptive. Besides, it has certain ability of anti-interference.