控制理论(社会学)
模糊控制系统
超调(微波通信)
塔楼
迭代学习控制
计算机科学
模糊逻辑
背景(考古学)
数学
数学优化
算法
工程类
控制(管理)
人工智能
电信
古生物学
土木工程
生物
作者
Radu-Emil Precup,Raul-Cristian Roman,Elena-Lorena Hedrea,Emil M. Petriu,Claudia-Adina Bojan-Dragos,Alexandra- Iulia Szedlak-Stinean
标识
DOI:10.1109/ciss56502.2023.10089708
摘要
This current paper proposes to improve the performance of three Single Input-Single Output (SISO) fuzzy control systems of controlling every position of tower crane systems using Proportional-Derivative (PD)-type indirect iterative learning rules at the higher hierarchical levels in each SISO control loop. The lower hierarchical levels in the three SISO control loops are built upon three low-cost Takagi-Sugeno Proportional-Integral (PI)-fuzzy controllers tuned by the initial application of Extended Symmetrical Optimum (ESO) method to the linear PI controllers and next the transfer of the results to the PI-fuzzy controllers in terms of the modal equivalence principle. Set-point filters are included at the lower hierarchical level in the context of the ESO method for overshoot reduction. The design approach is presented in a unified way for all three controllers. The gains of the PD-type learning rules are optimally computed in the iteration domain considering a metaheuristic Slime Mold Algorithm (SMA) in a transparent and simplified version, that settles the optimization problems with objective functions expressed as the sums of squared control errors multiplied by time. The enhanced performance is settled considering ten sets of iterations of SMA.
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