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Adaptive neural-fuzzy control of uncertain constrained multiple coordinated nonholonomic mobile manipulators

机译:不确定约束多协调非完整移动机械臂的自适应神经模糊控制

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Most studies on the coordination of multiple mobile manipulators system assume exact knowledge of system kinematics and dynamics, and deal only with motion tracking control. However, actual applications may involve tasks in which multiple coordinated mobile manipulators system is required to keep contact on the contour of the constraint surface in tasks. In this paper, we consider multiple mobile manipulators grasping a rigid object in contact with deformable working surfaces, whose geometric and physical model is unknown. The contact forces are nonlinear and unknown. Adaptive neuro-fuzzy (NF) control for coordinated mobile manipulators is proposed for robust force/motion tracking on the constraint surface while it is in motion. The control law is decoupled in three subspaces and adaptive tuning mechanism is developed to deal with the uncertain environmental constraints, disturbances, and unknown robotic dynamics. The proposed adaptive NF hybrid force/motion controller guarantees robust tracking of the desired motion and force trajectories. Simulation examples are presented to illustrate the results.
机译:关于多移动机械手系统协调的大多数研究都假设系统运动学和动力学具有确切的知识,并且仅涉及运动跟踪控制。但是,实际应用可能涉及需要多个协同移动操纵器系统以保持接触任务中约束表面轮廓的任务。在本文中,我们考虑了多个移动机械手,它们抓住与变形工作面接触的刚性物体,其几何和物理模型未知。接触力是非线性的并且是未知的。提出了用于协调移动机械手的自适应神经模糊(NF)控制,以在约束表面运动时对其进行鲁棒的力/运动跟踪。控制律在三个子空间中解耦,并开发了自适应调整机制来应对不确定的环境约束,干扰和未知的机器人动力学。提出的自适应NF混合力/运动控制器保证了对所需运动和力轨迹的鲁棒跟踪。给出了仿真示例以说明结果。

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