Multivariable Self-organizing fuzzy logic control (SOFLC) using a switching mode linguistic compensator

Q. Lu, M. Mahfouf
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引用次数: 5

Abstract

Due to the interactions between the control channels, it is not an easy task to express the control strategies in the form of related multi-situations to multi-actions control fuzzy rules. Decoupled control is one answer to this problem. It separates the control task into two types: one is the dominating controller applied to fulfil the tracking task of a particular single-situation to a single-action loop, and the other is the compensator used to decouple the channels themselves. This paper adopts the self-organizing fuzzy logic control (SOFLC) strategy, which has the ability of self-generating and modifying the control rules depending on the on-line system control information, as the main controller for each channel. The compensating controller is triggered according to the nature of the effect of the interaction from the corresponding channel. The strategy of identifying the interaction effect follows the system performance evaluation method applied in SOFLC as well. A series of simulations were carried out on a two-input and two-output biomedical process, with the conclusion that the proposed decoupling control mechanism has the ability to deal with varying system dynamics, noise and inaccurate estimation of compensator gains very effectively
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基于切换模式语言补偿器的多变量自组织模糊控制(SOFLC)
由于控制通道之间的相互作用,将控制策略以相关多情境的形式表达为多动作控制模糊规则是一件不容易的事情。解耦控制是解决这个问题的一种方法。它将控制任务分为两种类型:一种是用于完成特定单情况对单动作回路的跟踪任务的支配控制器,另一种是用于解耦通道本身的补偿器。本文采用自组织模糊逻辑控制(SOFLC)策略作为各通道的主控制器,该策略具有根据在线系统控制信息自生成和修改控制规则的能力。补偿控制器根据来自相应通道的相互作用的影响的性质被触发。识别交互效应的策略也沿用了sofflc中应用的系统性能评价方法。对一个双输入双输出生物医学过程进行了一系列仿真,结果表明所提出的解耦控制机制能够有效地处理系统动态变化、噪声和补偿器增益估计不准确等问题
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