首页> 外文会议>2013 Fifth Conference on Measuring Technology and Mechatronics Automation. >Adaptive Neural Network H#x00A1;#x00DE; Tracking Control of Wheeled Mobile Robots with Unknown Slipping Based on Transverse Function Approach
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Adaptive Neural Network H#x00A1;#x00DE; Tracking Control of Wheeled Mobile Robots with Unknown Slipping Based on Transverse Function Approach

机译:基于横向函数法的未知滑动轮式机器人的自适应神经网络HÞ跟踪控制

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Proposed in this paper is a new trajectory tracking controller for the uncertain wheeled mobile robots (WMR) violating the pure nonholonomic constraint. Firstly, the group operation for left-invariant system by using the transverse function is employed to solve the under actuated and MIMO coupled problem in WMR. Then in order to attenuate external disturbance and compensate the unknown slipping, a con-troller combines H¡Þ control and adaptive neural network is presented. Hence, the H¡Þ tracking performance with a prescribed disturbance attenuation lever is guaranteed and the system uncertainty including the slipping is approximated optimally. The validity of proposed control method is verified by the simulation results.
机译:本文针对不确定的轮式移动机器人(WMR),提出了一种新的轨迹跟踪控制器,该控制器违反了纯粹的非完整约束。首先,利用横向函数对左不变系统进行分组运算,以解决WMR中的欠驱动和MIMO耦合问题。然后为了减小外部干扰并补偿未知的滑移,提出了一种结合了HÞ控制和自适应神经网络的控制器。因此,保证了具有规定的干扰衰减杆的H跟踪性能,并且包括滑移在内的系统不确定性被最佳地近似。仿真结果验证了所提控制方法的有效性。

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