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P-type ILC with phase lead compensation for a pneumatically driven parallel robot

机译:具有相位超前补偿的P型ILC,用于气动并联机器人

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Iterative learning control is a popular method for accurate trajectory tracking of systems that repeat the same motion many times. This paper presents a P-type iterative learning control for a fast two-degree-of-freedom parallel robot driven by two pairs of pneumatic muscle actuators. The robot consists of a light-weight closed-chain structure with four moving links connected by revolute joints. The two base joints are active and driven by pairs of pneumatic muscles by means of a toothed belt and a pulley, respectively. The proposed control has a cascade structure. The internal pressure of each pneumatic muscle is controlled by a fast underlying control loop. Hence, the control design for the outer control loop, with the angles of the active joints and their velocities as controlled variables, can be simplified by considering these controlled muscle pressures as ideal control inputs. The suggested ILC algorithm is employed to modify the desired trajectory of the outer control loop. Experimental results from an implementation on a test rig show an excellent control performance.
机译:迭代学习控制是一种用于对多次重复相同运动的系统进行精确轨迹跟踪的流行方法。本文提出了一种由两对气动肌肉执行器驱动的快速两自由度并行机器人的P型迭代学习控制。该机器人由轻巧的闭链结构组成,具有通过旋转关节连接的四个运动链节。两个基础关节是活动的,分别由成对的气动肌肉通过齿形带和滑轮驱动。提出的控件具有级联结构。每个气动肌肉的内部压力由快速的基础控制回路控制。因此,可以通过将活动关节的角度及其速度作为控制变量来简化外部控制回路的控制设计,方法是将这些受控的肌肉压力视为理想的控制输入。建议的ILC算法用于修改外部控制回路的所需轨迹。在试验台上实施的实验结果显示了出色的控制性能。

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