This article aims to provide a new perspective on how the deployment of general type-2 (GT2) fuzzy sets affects the mapping of a class of fuzzy logic controllers (FLCs). It is shown that an α-plane represented a GT2-FLC is easily designed via baseline type-1 and interval type-2 FLCs and two design parameters (DPs). The DPs are the total number of α planes and the tuning parameter of the secondary membership function that are interpreted as sensitivity and shape DPs, respectively. We provide a clear understanding and interpretation of the sensitivity and shape DPs on controller performance through various comparative analyses. We present design approaches on how to tune the shape DP by providing a tradeoff between robustness and performance. We also propose two online scheduling mechanisms to tune the shape DP. We explore the effect of the sensitivity DP on the GT2-FLC and provide practical insights on how to tune the sensitivity DP. We present an algorithm for tuning the sensitivity DP that provides a compromise between computational time and sensitivity. We validate our analyses, interpretations, and design methods with experimental results conducted on a drone. We believe that this article provides clear explanations on the role of DPs on the performance, robustness, sensitivity, and computational time of GT2-FLCs.

中文翻译：

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通用 2 类模糊逻辑控制器的系统设计：分析、解释和调整


本文旨在提供一个新的视角来了解通用 2 型 (GT2) 模糊集的部署如何影响一类模糊逻辑控制器 (FLC) 的映射。结果表明，通过基线类型 1 和间隔类型 2 FLC 以及两个设计参数 (DP) 可以轻松设计代表 GT2-FLC 的 α 平面。 DP 是 α 平面的总数和二次隶属函数的调整参数，分别解释为灵敏度和形状 DP。通过各种比较分析，我们对控制器性能的灵敏度和形状 DP 提供了清晰的理解和解释。我们提出了如何通过在鲁棒性和性能之间进行权衡来调整形状 DP 的设计方法。我们还提出了两种在线调度机制来调整形状DP。我们探讨了灵敏度 DP 对 GT2-FLC 的影响，并提供了有关如何调整灵敏度 DP 的实用见解。我们提出了一种调整灵敏度 DP 的算法，该算法在计算时间和灵敏度之间提供了折衷方案。我们用无人机上进行的实验结果验证了我们的分析、解释和设计方法。我们相信本文清楚地解释了 DP 对 GT2-FLC 的性能、鲁棒性、灵敏度和计算时间的作用。