中文摘要：

这篇论文考虑平行操纵者的适应控制与模糊神经的网络算法(FNNA ) 结合了。与这个算法，坚韧性被适应控制法律保证；参量的不确定性被消除。FNNA 被用来处理模型不确定性；外部骚乱。在建议控制计划，我们考虑修改模糊规则的重量；与超过三 degrees-of-freedom (DoF ) 介绍这些规则给平行操纵者的一个 MIMO 系统。算法有的优点不特别为低 DoF 平行操纵者要求 Jacobian 矩阵的逆。控制计划的有效性与三 DoF 通过一个 6-RPS 平行操纵者的数字模拟被显示出。

英文摘要：

This paper considers adaptive control of parallel manipulators combined with fuzzy-neural network algorithms （FNNA）. With this algorithm, the robustness is guaranteed by the adaptive control law and the parametric uncertainties are eliminated. FNNA is used to handle model uncertainties and external disturbances. In the proposed control scheme, we consider modifying the weight of fuzzy rules and present these rules to a MIMO system of parallel manipulators with more than three degrees-of-freedom （DoF）. The algorithm has the advantage of not requiring the inverse of the Jacobian matrix especially for the low DoF parallel manipulators. The validity of the control scheme is shown through numerical simulations of a 6-RPS parallel manipulator with three DoF.