欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
针对一类具有未知死区和未知控制增益符号的单输入单输出非线性系统，根据滑模控制原理，并利用Nussbaum函数的性质，提出两种自适应神经网络控制器的设计方案。通过引入示性函数，提出一种简化死区模型，取消了死区模型的倾斜度相等的条件。通过引入逼近误差的自适应补偿项来消除建模误差和参数估计误差的影响。理论分析证明闭环系统是半全局一致终结有界。仿真结果表明该方法的有效性。
英文摘要：
The problem of adaptive neural network control for a class of single input single output （SISO） nonlinear systems with unknown dead-zone and function control gain sign is studied in this paper. Based on the principle of sliding mode control and the property of Nussbaum function, two design schemes of adaptive neural network controller are proposed. By introducing characteristic function for the dead-zone model in the systems, a simplified dead-zone model is developed. The approach removes the condition of the equal slope with defined region. The adaptive compensation term of the approximation error is adopted to minify the influence of modeling errors and parameter estimation errors. By theoretical analysis, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded. Simulation results demonstrate the effectiveness of the approach.
同期刊论文项目
同项目期刊论文
Adaptive variable structure control for large-scale time-delayed systems with unknown nonlinear dead
Adaptive variable structure control of MIMO nonlinear systems with time-varying delays and unknown d
Adaptive Neural Control of MIMO Nonlinear Time-Varying Delay Systems with Minimum Adjustable Paramet
Adaptive neural control of non-affine pure-feedback non-linear systems with input nonlinearity and p
Adaptive Neural Network Tracking Control of MIMO Nonlinear Systems With Unknown Dead Zones and Contr
期刊信息
位置：