不确定双因果键图与自适应模糊PID容错控制

Y. Lounici, Y. Touati, S. Adjerid, B. O. Bouamama, D. Benazzouz
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引用次数: 2

摘要

本文提出了一种基于不确定双因果键图和自适应模糊PID控制器的不确定系统容错控制方法。主要目标是使控制系统在存在故障和不确定性的情况下更快、更有效地行动。当前工作的科学兴趣仍然是整合基于不确定双因果键图模型的故障估计和模糊PID控制器的优点,以有效地对不确定动态系统进行容错控制。对于该任务,不确定故障估计是由不确定双因果键图生成的,该键图的标称部分与不确定部分完全分离。其次,提出了一种模糊推理方案来实时调整PID增益,其中模糊推理中使用估计故障和由于存在不确定性而超过估计故障的误差作为输入。最后,将补偿故障影响的所需输入传递给系统。通过对全向移动机器人牵引系统的实验应用,将该方法与传统方法进行了比较。实验结果表明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Uncertain Bicausal Bond Graph and Adaptive Fuzzy PID Controller for Fault-Tolerant Control
In this paper, a new fault-tolerant control scheme for uncertain systems is proposed based on uncertain bicausal Bond Graph and Adaptive Fuzzy PID Controller. The main objective is to make the control system act faster and more effectively in the presence of the faults and uncertainties. The scientific interest of the present work remains in integrating the benefits of uncertain bicausal bond graph model-based fault estimation and Fuzzy PID controller for effective fault-tolerant control of uncertain dynamic systems. For this task, the uncertain fault estimation is generated from the uncertain bicausal bond graph with perfectly separate nominal part from the uncertain part. Second, a fuzzy inference scheme is proposed to tune the PID gains in real-time, where the estimated fault and the errors over the estimated fault due to the presence of uncertainties are used in the fuzzy inference as inputs. Finally, the required input that compensates the fault effects are delivered to the system. The proposed approach is compared with the conventional one through an experimental application to the traction system of an omnidirectional mobile robot. The results show the effectiveness of the proposed approach.
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