基于自适应控制算法的机械控制系统优化研究  

Research on Optimization of Mechanical Control System Based on Adaptive Control Algorithm

作　　者：杨继红 Yang Jihong(Pingdingshan Industrial School,Pingdingshan,Henan 467000,CHN)

机构地区：[1]平顶山市工业学校,河南平顶山467000

出　　处：《模具制造》2024年第7期35-37,共3页Die & Mould Manufacture

摘　　要：研究了基于自适应控制算法的机械控制系统优化,通过系统辨识建立了机械臂的线性参数空间模型,并采用径向基神经网络(RBFNN)构建了两级自适应控制器。实验结果验证了所提方法在提高轨迹跟踪精度和系统鲁棒性方面的有效性,特别是在应对复杂时变信号时表现突出,为工业机器人的高精度运动控制提供了新的解决方案,并为自适应控制算法的应用提供了实践指导。This research investigates the optimization of mechanical control systems based on adaptive control algorithms.By establishing a linear parameter space model of a robotic arm through system identification,a two-level adaptive controller was constructed using Radial Basis Function Neural Networks(RBFNN).Experimental results validate the effectiveness of the proposed method in enhancing trajectory tracking accuracy and system robustness,particularly when dealing with complex time-varying signals.This study provides a new solution for high-precision motion control of industrial robots and offers practical guidance for the application of adaptive control algorithms.

关 键 词：自适应控制 机械臂 轨迹跟踪 鲁棒性 系统辨识 

分 类 号：TG659[金属学及工艺—金属切削加工及机床]