Muhammed Gaafar, A. Maged, M. Magdy, N. A. Mansour, A. El-Betar
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引用次数: 3
摘要
在机器人运动学与控制中,求解运动学逆解是一个非常困难的问题。包括代数和几何在内的传统方法并不总是适用于复杂的节理结构。与这些方法相比,自适应神经模糊推理系统(ANFIS)更容易应用,效率更高。ANFIS遇到的问题通常发生在设计过程中。它包括各种参数的设置,这些参数对于迭代来说可能是复杂和耗时的。针对这一问题,本文将采用实验设计(Design of Experiment, DoE)方法对ANFIS应用于运动学逆解时的重要参数进行优化。采用响应面法(RSM),将四个因素作为输入变量。结果表明,采用该方案可以显著改善验证误差。对于每个theta,确定显著参数,并给出最优值。
Design and Analysis of Experiments in ANFIS Modeling of a 3-DOF Planner Manipulator
In robot kinematics and control, it is very hard to find the solution of inverse kinematics. Conventional methods including algebraic and geometric cannot be always adequate for complex joint structures. Adaptive Neuro-Fuzzy Inference System (ANFIS) can be easier to apply and more efficient compared to these methods. The problem encountered with ANFIS usually occurs in the designing process. it includes the setting of various parameters which can be complicated and time-intensive for iterations. Facing this problem, in this paper, a Design of Experiment (DoE) methodology will be used to optimize the significant parameters of ANFIS when it is applied to inverse kinematics solution. Using Response Surface Methodology (RSM), four factors are considered as input variables. Results show that the validation error can be significantly improved using the proposed scheme. For each theta, the significant parameters were determined, and the optimal values were presented.