AI 中文总结
本文针对带恒定时滞的不确定非线性双边遥操作系统，提出仅含两个自适应参数的紧凑双侧自适应RBFNN控制器，经2-DOF机械臂仿真验证，可实现约2秒同步，揭示精度与控制颤振的权衡。
AI 中文摘要
双边遥操作需要在主从端动力学不确定及通信通道存在时滞的情况下仍保证系统稳定。现有的径向基函数神经网络（RBFNN）控制器主要在不确定性分解方面存在差异，而在线自适应参数往往随网络规模增大而增加。本文针对具有恒定前向和反向时滞的非线性双边遥操作器，提出一种紧凑的双侧自适应控制器。将操作者和环境阻抗纳入机械臂动力学，两侧仅使用两个标量自适应估计值：一个用于理想RBF权重范数，另一个用于摩擦、逼近误差和干扰的综合效应。两个估计值均通过sigma修正更新，无论RBF节点数量多少，仅需两个自适应参数。构建整合滑模变量能量、估计误差和依赖时滞积分项的Lyapunov-Krasovskii泛函，基于滑模面恒等式的自由加权矩阵提供依赖时滞的矩阵条件，保证同步误差、滑模变量和自适应估计值的一致最终有界性。对两个带摩擦、外部干扰和阶跃式操作者输入的2自由度（2-DOF）旋转机械臂进行仿真，结果显示同步时间约为2秒，并揭示了精度与控制颤振之间的权衡关系。
英文摘要
Bilateral teleoperation requires stability despite uncertain master and slave dynamics and delayed communication channels. Existing radial basis function neural network (RBFNN) controllers mainly differ in uncertainty decomposition, while online adaptive parameters often increase with network size. This paper proposes a compact two-sided adaptive controller for a nonlinear bilateral teleoperator with constant forward and backward delays. Operator and environment impedances are incorporated into the manipulator dynamics, and each side uses only two scalar adaptive estimates: one for the ideal RBF weight norm and another for the combined effects of friction, approximation error, and disturbances. Both estimates are updated through sigma-modification, resulting in only two adaptive parameters regardless of the number of RBF nodes. A Lyapunov-Krasovskii functional integrating sliding-variable energy, estimation errors, and delay-dependent integral terms is developed. Free-weighting matrices based on sliding-surface identities provide delay-dependent matrix conditions that guarantee uniform ultimate boundedness of synchronization errors, sliding variables, and adaptive estimates. Simulations on two 2-degree-of-freedom (2-DOF) revolute manipulators with friction, external disturbance, and stepwise operator inputs demonstrate synchronization within approximately 2 s and reveal the trade-off between accuracy and control chattering.
Comments20 Pages, 7 Figures
