江西科学2026，Vol.44Issue(3)：469-477,9.DOI:10.13990/j.issn1001-3679.2026.03.014
基于改进差分搜索的沿墙机器人模糊逻辑控制算法
Fuzzy Wall-Following Control Algorithm for Mobile Robots Based on Improved Differential Search
摘要
Abstract
Fuzzy logic control effectively handles uncertainties and nonlinear problems in mo-bile robot motion control,but its performance depends on parameter and rule base configura-tion,requiring significant manual tuning effort.To reduce the workload of fuzzy logic pa-rameter adjustment in wall-following robot control,a fuzzy logic control algorithm based on improved differential search(FLC-IDS)is proposed.The algorithm introduces an adap-tive adjustment strategy for randomization probability parameters P1 and P2 to balance global exploration and local exploitation and automatically optimizes fuzzy logic control pa-rameters through preset reward-penalty strategies and reinforcement learning-based fit-ness evaluation mechanisms.Experimental results show that compared with manual tuning methods,FLC-IDS reduces the number of manually tuned parameters by 55.7%,achieving mean absolute errors of 43 mm and 52 mm in training and testing environments respectively,demonstrating good control accuracy and robustness.The method provides an effective ap-proach for automatic FLC parameter optimization without relying on labeled data.关键词
移动机器人/沿墙移动/模糊逻辑控制/改进差分搜索/强化学习Key words
mobile robot/wall-following/fuzzy logic control/improved differential search/reinforcement learning分类
信息技术与安全科学引用本文复制引用
张志孟,张露萍..基于改进差分搜索的沿墙机器人模糊逻辑控制算法[J].江西科学,2026,44(3):469-477,9.基金项目
江西省自然科学基金项目(20242BAB25062). （20242BAB25062）
