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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

机译:正轮驱动自行车机器人在90度前杆转向角下的前轮驱动自行车机器人的动态建模和自适应控制器设计

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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.
机译:本文分析了在90度前方转动角度下的前轮驱动器的自行车机器人的轨道站运动。 基于Appell方程提出了一种动态模型。 为了实现轨道站运动控制的目标,控制器是基于RBF神经网络和自适应滑动模式控制算法设计的。 并且计算机仿真基于MATLAB进行,以比较机器人的稳定平衡运动而不会分开干扰和干扰。 通过模拟结果作证了动态模型和控制算法的有效性。 并且可以自动调谐控制器中的系数。 模型中的不确定性由RBF神经网络估计,以便控制器是自适应的。 此外,它具有一定的抗干扰能力。

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