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Hierarchical Learning-Based Design of a Hybrid Fuzzy Pid Controller

机译:基于分层学习的混合模糊PID控制器设计

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The development of a systematic design procedure has been of interest since the introduction of fuzzy logic controllers (FLCs). As the dimensions of the system's input and output spaces become larger, the design problem becomes exponentially more difficult. Partitioning the input space into smaller, more manageable regions simplifies the design procedure. The problem then becomes one of integrating the regional controllers designed for each input space partition. This article demonstrates a systematic and hierarchical approach to the design of a hybrid fuzzy-PID controller through the application of a learning-based algorithm. The proposed method is applied to a two-link robotic arm. Favorable simulation results are obtained when comparing our approach to fixed PID Control and Variable Structure Control.
机译:自引入模糊逻辑控制器 (FLC) 以来,系统设计程序的开发一直备受关注。随着系统输入和输出空间的尺寸变大,设计问题的难度也呈指数级增长。将输入空间划分为更小、更易于管理的区域可简化设计过程。然后,问题就变成了集成为每个输入空间分区设计的区域控制器。本文通过应用基于学习的算法,展示了一种系统化和分层的混合模糊PID控制器设计方法。将所提方法应用于双连杆机械臂。通过比较固定PID控制和可变结构控制的方法,获得了良好的仿真结果。

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