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IMPLEMENTING FUZZY LOGIC IN THE CONTROL OF A BIOLOGICALLY INSPIRED ROBOTIC CAT LEG

机译:在生物启发式机器人猫腿的控制中实现模糊逻辑

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摘要

This research discusses the implementation of a fuzzy logic control system to drive the movement of a simplified cat leg model. The system's movement in this paper addresses a planar motion where the model experiences a fixed horizontal velocity and a harmonic vertical displacement. The fuzzy logic (FL) controller applies membership functions to fuzzify the position and velocity errors and applies height defuzzification to generate the time dependant forcing function for the system's horizontal and vertical governing equations. A PID controller is also applied as a benchmark for this research. Both controllers are optimized using the simplex method for which the FL controller performed just as well as the PID controller with more promise of accounting for the nonlinear influences that were neglected in this simplified cat leg model and requiring actuators with a lower required force range. This research provides the skeletal structure for which an effective total controller can be built on.
机译:这项研究讨论了驱动简化猫腿模型运动的模糊逻辑控制系统的实现。本文中系统的运动是针对平面运动的,其中模型经历了固定的水平速度和谐波垂直位移。模糊逻辑(FL)控制器应用隶属度函数对位置和速度误差进行模糊处理,并对高度进行去模糊化处理以生成与系统的水平和垂直控制方程有关的时间相关强迫函数。 PID控制器也被用作本研究的基准。两种控制器都使用单纯形方法进行了优化,其中FL控制器的性能与PID控制器的性能相同,并有望解决简化的猫腿模型中所忽略的非线性影响,并要求执行器的作用力范围较低。这项研究提供了可以建立有效的总控制器的骨架结构。

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