基于CMAC-PID和遗传算法的水下植物控制研究

Lei Wang, Peilong Li
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引用次数: 0

摘要

针对水下实验装置运动控制的各种不确定性和非线性,提出了一种基于CMAC-PID和遗传算法的水下实验装置控制方法。该方法结合了CMAC神经网络前馈控制和PID反馈控制的优点,形成了一种并联控制结构,其中PID参数通过遗传算法进行优化。仿真结果表明,遗传算法可以有效地改进PID参数的整定过程。同时,CMAC-PID组合控制具有良好的动态特性和稳态精度,可在一定程度上为水下试验场的运动控制提供借鉴。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study on the Control of Underwater Plant Based On CMAC-PID and GA
Against a variety of uncertainties and nonlinearities of the underwater plant motion control, this paper proposed a control method of underwater test plant based on CMAC-PID and GA algorithm. This approach combined the advantages of both CMAC neural network feedforward control and PID feedback control to form a parallel control structure, in which PID parameters were optimized via genetic algorithm. The simulation results showed that the genetic algorithm can effectively improve the setting process of PID parameters. Meanwhile, the CMAC-PID combination control has good dynamic characteristics and steady-state accuracy, which, to some extent, can be used for reference to the motion control of underwater test plant.
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