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Uncertain Bicausal Bond Graph and Adaptive Fuzzy PID Controller for Fault-Tolerant Control

机译:不确定二叉键图和自适应模糊PID控制器的容错控制

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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.
机译:本文提出了一种基于不确定双键图和自适应模糊PID控制器的不确定系统容错控制方案。其主要目的是使控制系统在存在故障和不确定性的情况下更快,更有效地工作。当前工作的科学兴趣仍然在于将基于不确定双因果关系图模型的故障估计和模糊PID控制器的好处相结合,以对不确定的动态系统进行有效的容错控制。对于此任务,不确定的故障估计是从不确定的双峰结合图生成的,标称部分与不确定部分完全分开。其次,提出了一种模糊推理方案来实时调整PID增益,其中将估计故障和由于不确定性的存在而导致的估计故障误差用作模糊推理的输入。最后,补偿故障影响的所需输入被传送到系统。通过在全向移动机器人牵引系统上的实验应用,将所提出的方法与传统方法进行了比较。结果表明了该方法的有效性。

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