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首页> 外文期刊>Journal of robotics and mechatronics >Fuzzy Self-Tuning Precompensation PD Control with Gravity Compensation of 3 DOF Planar Robot Manipulators
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Fuzzy Self-Tuning Precompensation PD Control with Gravity Compensation of 3 DOF Planar Robot Manipulators

机译:具有3个自由度平面机器人机械手的重力补偿的模糊自调整预补偿PD控制

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摘要

Industrial robot control covers nonlinearity, uncertainty and external perturbation considered in control laws design. Proportional and Derivative (PD) with gravity compensation control is well-known control used in manipulators to ensure global asymptotic stability for fixed symmetrical positive definite gain matrices. To enhance PD with gravity compensation controller performance, in this paper, we propose hybrid fuzzy PD control precompensation with gravity compensation, consisting of a fuzzy logic-based precompensator followed by hybrid fuzzy PD with gravity compensation controller. Hybrid fuzzy control is done by a Supervisory Hierarchical Fuzzy Controller (SHFC) for tuning conventional controller Proportional and Derivative gains based on actual tracking location and velocity error. Hierarchical hybrid fuzzy control consists of an intelligent upper supervisory fuzzy controller and a lower direct conventional PD controller. Numerical simulations using the dynamic model of a three DOF planar rigid robot manipulator with uncertainty show the effectiveness of the approach in trajectory tracking problems. Our results show that the proposal controller has performance superior to a conventional controller.
机译:工业机器人控制涵盖了控制律设计中考虑的非线性,不确定性和外部干扰。具有重力补偿控制的比例和微分(PD)是操纵器中众所周知的控制,用于确保固定对称正定增益矩阵的全局渐近稳定性。为了提高具有重力补偿控制器的局部放电性能,本文提出了一种具有重力补偿的混合模糊局部放电控制预补偿方法,该方法由基于模糊逻辑的预补偿器和带有重力补偿控制器的混合模糊局部放电组成。混合模糊控制是由监督分层模糊控制器(SHFC)完成的,用于根据实际跟踪位置和速度误差来调整常规控制器的比例和微分增益。分层混合模糊控制由智能上层监督模糊控制器和下层直接常规PD控制器组成。使用具有不确定性的三自由度平面刚性机器人机械手的动力学模型进行的数值仿真表明,该方法在轨迹跟踪问题中是有效的。我们的结果表明,建议控制器具有优于常规控制器的性能。

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