反推
控制理论(社会学)
人工神经网络
稳健性(进化)
计算机科学
自适应控制
李雅普诺夫函数
控制工程
伺服机构
非线性系统
PID控制器
径向基函数
Lyapunov稳定性
伺服电动机
工程类
人工智能
控制(管理)
物理
基因
量子力学
化学
温度控制
生物化学
作者
Haibo Zhao,Peng Fei Gao
标识
DOI:10.1109/rcae56054.2022.9995855
摘要
In order to weaken the adverse effect of backlash nonlinearity on dual-motor driving servo system, an adaptive control strategy was proposed. The state-space model of the system was first given. By introducing the virtual control quantity, using backstepping approach and recursively selecting the Lyapunov function, and adopting a radial-basis-function (RBF) neural network to design adaptive law, a state feedback-based RBF neural network backstepping adaptive controller was designed, and its stability was analyzed. Compared with the conventional PID control in simulation results, the proposed control strategy shows better position tracking performance and higher robustness.
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