摘要
针对履带机器人这一结构不稳定性、参数不确定性的非线性系统,本文结合神经网络理论与滑模控制,提出了基于模糊神经网络的自适应滑模控制,对不确定非线性系统的控制问题设计了控制器。本文首先建立了履带式机器人的运动学模型,以自适应滑模控制理论为基础,构建了等效控制器,依据模糊神经网络理论基础构建切换控制器,在保证控制器全局稳定性和收敛性的同时,同时获得抑制系统抖振。仿真验证了利用神经网络对履带式机器人这一非线性系s统具有较强的自适应性和鲁棒性。并且具有快速响应和较强的跟踪性能的特点。
According to the nonlinear structure of the tracked robot instability,parameter uncertainty,combined with the theory of neural network and sliding mode control,the adaptive sliding mode control based on fuzzy neural network,the control problem of uncertain nonlinear systems to design the controller. This paper firstly established the kinematics model of the tracked robot,the adaptive sliding mode control theory,establishes the equivalent controller based on fuzzy neural network theory based switching controller,controller to ensure global stability and convergence at the same time,also won the chattering. The simulation results show that the neural network has strong adaptability and robustness to the s system of the tracked robot. And has the characteristics of fast response and strong tracking performance.
作者
李郑涛
焦俊
张政云
倪力
古冉
王强
LIZheng-tao JIAOJun ZHANGZheng-yun NiLi GuRan WangQiang(College of Engineering, Anhui Agriculture University, Hefei 230036, China College of information and computer science, Anhui Agriculture University, Hefei 230036, China)
出处
《内蒙古农业大学学报（自然科学版）》
CAS
2017年第4期34-38,共5页
Journal of Inner Mongolia Agricultural University(Natural Science Edition)
基金
安徽省教育厅质量工程项目资助(K4AO74)
2014jyxm091
2014tszyo90
