基于无模型PID控制器自适应安全实验动力学整定的DC/DC Buck-Boost变换器-逆变器-直流电机控制

M. R. Ghazali, Mohd Ashraf Ahmad, M. H. Suid, M. Tumari
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引用次数: 2

摘要

本研究通过自适应安全实验动力学(ASED)方法的优化,目前将无模型PID控制用于DC/DC Buck-Boost转换器-逆变器-直流电机结构的检测。PID控制器以其结构简单、使用方便、可调参数有限、适用范围广等优点得到了广泛的应用。演示了DC/DC Buck-Boost converter - invertver -DC电机MIMO结构的非线性、复杂性和高维参数,并要求具有极高精度的控制器。在此,采用基于神经网络的方法作为优化方法,根据需要具有相当高的精度,对PID控制器进行微调,使其能够在较小的处理间隔内通过排除数学建模来评估系统的输入和输出,从而最小化控制跟踪的输出和能耗。跟踪结果关于电压的转换器和双向角速度进一步说明性能评估推荐的电机系统配备无模型PID控制器后,基于优化的方法。进一步比较了拟议的基于sed的方法与传统的基于sed的方法之间的操作。通过对给定目标函数的最小化进行仿真,得到了该方法的收敛稳定性。由此获得的结果证实,相对于传统方法的性能,基于神经网络的方法在操作跟踪精度方面的目标函数和总范数误差较小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A DC/DC Buck-Boost Converter-Inverter-DC Motor Control based on model-free PID Controller tuning by Adaptive Safe Experimentation Dynamics Algorithm
Model-free PID control is currently utilized for the examination of a DC/DC Buck-Boost Converter-Inverter-DC motor structure in this study through optimization of the adaptive safe experimentation dynamics (ASED) method. PID controller has been popularized on its uncomplicated construct, convenient employment with limited tuneable parameters, and broad applicability to diverse mechanistic circumstances. Demonstrated nonlinearity, complexity, and high dimensional parameters within MIMO structure of the DC/DC Buck-Boost Converter-Inverter-DC motor then demand controller with immense precision. The ASED method is hereby adopted as the optimization approach with considerable precision as needed towards fine-tuning the PID controller for its ability to minimize both output of control tracking and energy consumption at reduced processing interval by the exclusion of mathematical modeling in assessing input and output of the system. Traced outcomes regarding voltage of the converter and bidirectional angular velocity are further accounted for performance appraisal of the recommended motor system equipping model-free PID controller following optimization of the ASED approach. A comparison was further operationalized between the proposed ASED approach and its conventional SED-based counterpart. Convergence stability was successively reached by the proposed approach via undertaken simulation with minimization of the specified objective function. Acquired results hereby confirmed smaller values of the objective function and total norm error by the ASED approach towards the precision of operation tracing against the performance of its conventional counterpart.
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