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Design of an evolving Fuzzy-PID controller for optimal trajectory control of a 7-DOF redundant manipulator with prioritized sub-tasks

机译:一种不断变化的模糊PID控制器,实现7-DOF冗余机械手优先级子任务的优化轨迹控制

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摘要

Articulated manipulators constitute a major fraction of industrial robots. With the increase in the need to perform complex tasks requiring a higher degree of accuracy, such manipulators require a more robust and efficient control. In this paper, an evolving Fuzzy-PID control design for the trajectory tracking problem of a redundant 7-DOF serial manipulator is proposed. The scaling factors of the Fuzzy controller are evolved over time by using recent meta-heuristic techniques, namely, Moth-Flame Optimisation (MFO), Novel Bat Algorithm (NBA) and Sine Cosine Algorithm (SCA). The proposed technique which utilizes Intelligent control methods combined with meta-heuristics provides a promising hybrid control design, which has been found to be more efficient in our software implementation, in terms of reduced tracking error of the manipulator for its kinematic control in the joint space as compared to other controllers of the same nature that are generally used in practise. The performance of the controller is compared in the time domain responses under external disturbances and have been found to outperform standard controllers without the need of any additional training. (C) 2019 Elsevier Ltd. All rights reserved.
机译:铰接式操纵器构成了工业机器人的主要分数。随着需要进行需要更高精度的复杂任务的增加,这种操纵器需要更强大和有效的控制。在本文中,提出了一种冗余7-DOF串行机械手轨迹跟踪问题的演化模糊控制设计。通过使用最近的元启发式技术,即蛾火焰优化(MFO),新型BAT算法(NBA)和正弦余弦算法(SCA),随着时间的推移,模​​糊控制器的缩放因子随时间的推移而进化。利用智能控制方法与元启发式机结合的建议技术提供了一个有前途的混合控制设计,这些设计在我们的软件实施方面已经发现在手动控制中的跟踪误差方面可以更有效地在关节空间中的运动控制与通常在实践中通常使用的相同性质的其他控制器相比。控制器的性能在外部干扰下的时域响应中进行了比较,并且已发现以不需要任何额外的培训来实现标准控制器。 (c)2019 Elsevier Ltd.保留所有权利。

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