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Fuzzy digital PID controller design based on robust stability criteria

机译:基于鲁棒稳定性准则的模糊数字PID控制器设计

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A robust fuzzy digital PID control methodology based on gain and phase margins specifications, is proposed. A mathematical formulation, based on gain and phase margins specifications, the Takagi-Sugeno fuzzy model of the process to be controlled, the structure of the digital PID controller and the time delay, was developed. From input and output data of the process, a Fuzzy C-Means (FCM) clustering algorithm estimates the antecedent parameters and the rules number of a Takagi-Sugeno fuzzy model, whereas the least squares algorithm estimates the consequent parameters. A multiobjective genetic strategy is developed to tune the fuzzy digital PID controller parameters, so the gain and phase specified margins are obtained for the fuzzy control system. An analysis of necessary and sufficient robust stability conditions for fuzzy digital PID controller design, with the proposal of two theorems are presented. The digital fuzzy PID controller was implemented on a real time acquisition data platform, based on CompactRIO (NI cRIO-9073) and LabVIEW, from National Instruments, for temperature control of a thermic process. The experimental results for real time robust fuzzy digital PID control of the thermic process demonstrate the effectiveness and practical viability of the proposed methodology.
机译:提出了一种基于增益和相位裕度指标的鲁棒模糊数字PID控制方法。根据增益和相位裕度规范,要控制的过程的Takagi-Sugeno模糊模型,数字PID控制器的结构和时间延迟,开发了数学公式。根据过程的输入和输出数据,模糊C均值(FCM)聚类算法估计Takagi-Sugeno模糊模型的先行参数和规则数,而最小二乘算法估计后继参数。开发了一种多目标遗传策略来调节模糊数字PID控制器的参数,从而获得了模糊控制系统的增益和相位指定的余量。提出了两个定理,对模糊数字PID控制器设计的必要和充分的鲁棒稳定性条件进行了分析。数字模糊PID控制器是在基于CompactRIO(NI cRIO-9073)和美国国家仪器的LabVIEW的实时采集数据平台上实现的,用于热过程的温度控制。热过程的实时鲁棒模糊数字PID控制的实验结果证明了该方法的有效性和实用性。

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