Due to strongly coupled nonlinearities of the grasped dual-arm robot and the internal forces generated by grasped objects, the dual-arm robot control with uncertain kinematics and dynamics raises a challenging problem. In this paper, an adaptive fuzzy control scheme is developed for a dual-arm robot, where an approximate Jacobian matrix is applied to address the uncertain kinematic control, while a decentralized fuzzy logic controller is constructed to compensate for uncertain dynamics of the robotic arms and the manipulated object. Also, a novel finite-time convergence parameter adaptation technique is developed for the estimation of kinematic parameters and fuzzy logic weights, such that the estimation can be guaranteed to converge to small neighborhoods around their ideal values in a finite time. Moreover, a partial persistent excitation property of the Gaussian-membership-based fuzzy basis function was established to relax the conventional persistent excitation condition. This enables a designer to reuse these learned weight values in the future without relearning. Extensive simulation studies have been carried out using a dual-arm robot to illustrate the effectiveness of the proposed approach.

中文翻译：

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运动学和动力学未知的双臂机器人有限时间收敛自适应模糊控制


由于抓取双臂机器人的强耦合非线性和抓取物体产生的内力，运动学和动力学不确定的双臂机器人控制提出了一个具有挑战性的问题。本文针对双臂机器人开发了一种自适应模糊控制方案，其中采用近似雅可比矩阵来解决不确定的运动学控制，同时构建分散模糊逻辑控制器来补偿机器人手臂的不确定动力学和被操纵的对象。此外，还开发了一种新颖的有限时间收敛参数自适应技术，用于运动学参数和模糊逻辑权重的估计，从而保证估计在有限时间内收敛到理想值周围的小邻域。此外，建立了基于高斯隶属度的模糊基函数的部分持续激励性质，以放宽传统的持续激励条件。这使得设计者能够在将来重复使用这些学习到的权重值，而无需重新学习。使用双臂机器人进行了广泛的模拟研究，以说明所提出方法的有效性。