An optimal fuzzy logic controller for an underactuated unicycle

Jian-xin Xu, Zhao-Qin Guo, Tong-heng Lee
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引用次数: 2

Abstract

In this paper, we propose a hybrid design method for fuzzy logic controller (FLC), where the control objective for unicycle is to achieve velocity control of the wheel while keep the pendulum at the balanced position that is an unstable equilibrium. The hybrid design consists of three phases. First, FLC structure including the number of rules, membership function, inference, and parametric relations, are chosen based on heuristic knowledge about the unicycle. Then, based on a linearized model and linear feedback, the output parameters of FLC are determined quantitatively for the stabilization of the unicycle. Next, fine tuning of FLC output parameters are carried out using an iterative learning tuning (ILT) algorithm, where ILT iteratively minimizes an objective function that specifies the desired unicycle performance. The rationale of introducing the hybrid FLC design is to fully utilize available information, which is achieved by combining model-based and model-free designs, hence improve FLC performance. Through intensive simulations and comparisons, the effectiveness of the proposed hybrid FLC is validated.
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欠驱动独轮车的最优模糊逻辑控制器
本文提出了一种模糊逻辑控制器(FLC)的混合设计方法,其中对独轮车的控制目标是实现车轮的速度控制,同时使摆摆处于不稳定平衡的平衡位置。混合设计包括三个阶段。首先,根据单轮的启发式知识选择FLC结构,包括规则数、隶属函数、推理和参数关系。然后,基于线性化模型和线性反馈,定量确定了FLC的输出参数,实现了独轮车的稳定。接下来,使用迭代学习调谐(ILT)算法对FLC输出参数进行微调,其中ILT迭代最小化指定所需单轮性能的目标函数。引入混合FLC设计的基本原理是充分利用现有信息,将基于模型和无模型设计相结合,从而提高FLC的性能。通过大量的仿真和比较,验证了该混合FLC的有效性。
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