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Systematic design and analysis of fuzzy-logic control and application to robotics, part I. modeling

机译：模糊逻辑控制的系统设计与分析及其在机器人技术中的应用，第一部分，建模

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A systematic methodology for synthesis and analysis of fuzzy-logic controllers is proposed in this paper (Part I) and its follow up (Part II) [M.R. Emami, et al., Robotics and Autonomous Systems 33 (2000) 89-108]. A robust model-based control structure is suggested that includes a fuzzy-logic inverse dynamics model and several robust fuzzy control rules. The model encapsulates the knowledge of the system dynamics in the form of IF-THEN rules. The paper focuses on how to obtain this knowledge systematically from the input-output data of a complex system; one that is ill-defined or contains complicated phenomena that are difficult to interpret analytically. All practical steps, from data acquisition to model validation, are illustrated using a four degree-of-freedom robot manipulator. Comparing the results with those of a complete analytical model and a heuristic fuzzy modeling technique illustrates the strength of the proposed methodology in terms of capturing effects that are difficult to model. In the follow-up paper, this model is used in the proposed control structure.
机译：本文提出了一种模糊逻辑控制器的综合和分析的系统方法（第一部分），并提出了其后续措施（第二部分）。 Emami et al。，Robotics and Autonomous Systems 33（2000）89-108]。提出了一种基于鲁棒模型的控制结构，其中包括模糊逻辑逆动力学模型和几种鲁棒的模糊控制规则。该模型以IF-THEN规则的形式封装了系统动力学的知识。本文着重于如何从复杂系统的输入输出数据中系统地获得这些知识。一种定义不明确或包含复杂现象的分析难以解释的现象。使用四自由度机器人操纵器说明了从数据采集到模型验证的所有实际步骤。将结果与完整的分析模型和启发式模糊建模技术的结果进行比较，就捕获难以建模的效果而言，说明了所提出方法的优势。在后续文件中，此模型用于建议的控制结构中。

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