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首页> 外文期刊>Journal of applied mathematics >Adaptive Sliding Mode Control of Mobile Manipulators with Markovian Switching Joints
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Adaptive Sliding Mode Control of Mobile Manipulators with Markovian Switching Joints

机译:马尔可夫切换关节的机械臂自适应滑模控制

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The hybrid joints of manipulators can be switched to either active (actuated) or passive (underactuated) mode as needed. Consider the property of hybrid joints, the system switches stochastically between active and passive systems, and the dynamics of the jump system cannot stay on each trajectory errors region of subsystems forever; therefore, it is difficult to determine whether the closed-loop system is stochastically stable. In this paper, we consider stochastic stability and sliding mode control for mobile manipulators using stochastic jumps switching joints. Adaptive parameter techniques are adopted to cope with the effect of Markovian switching and nonlinear dynamics uncertainty and follow the desired trajectory for wheeled mobile manipulators. The resulting closed-loop system is bounded in probability and the effect due to the external disturbance on the tracking errors can be attenuated to any preassigned level. It has been shown that the adaptive control problem for the Markovian jump nonlinear systems is solvable if a set of coupled linear matrix inequalities (LMIs) have solutions. Finally, a numerical example is given to show the potential of the proposed techniques.
机译:机械手的混合关节可以根据需要切换到主动(致动)或被动(欠致动)模式。考虑混合关节的特性,系统在主动和被动系统之间随机切换,并且跳跃系统的动力学不能永远停留在子系统的每个轨迹误差区域上;因此,很难确定闭环系统是否是随机稳定的。在本文中,我们考虑了使用随机跳跃切换关节的移动机械手的随机稳定性和滑模控制。采用自适应参数技术来应对马尔可夫切换和非线性动力学不确定性的影响,并遵循轮式移动机械手的期望轨迹。最终的闭环系统具有概率限制,并且由于外部干扰而导致的对跟踪误差的影响可以衰减到任何预先指定的水平。已经表明,如果一组耦合线性矩阵不等式(LMI)具有解,则马尔可夫跳跃非线性系统的自适应控制问题是可解决的。最后,通过数值例子说明了所提出技术的潜力。

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