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基于神经网络的时变时滞系统自适应内模控制(英文)
Adaptive Internal Model Control based on the Artificial Neural Network for Time-varying Delay Systems
【摘要】 将基于人工神经网络的时变时滞系统参数辨识算法与内模控制相结合 ,提出了时变时滞系统自适应内模控制算法 .理论分析及仿真结果表明 ,该算法能克服时滞及参数的变化 ,具有鲁棒性好、抗干扰能力强的特点 .
【Abstract】 By combining an artificial neural network approach for parameter identification with internal model control, an adaptive internal model control algorithm for time varying delay systems (AIMC) is proposed. Theory analyses and computer simulation results show that the proposed algorithm can overcome time varying delays and parameters. It possesses better robustness and ability of anti disturbance.
【关键词】 人工神经网络;
参数辨识;
时变时滞系统;
自适应内模控制;
鲁棒性;
【Key words】 artificial neural network; parameter identification; time varying delay systems; adaptive internal model control; robustness;
【Key words】 artificial neural network; parameter identification; time varying delay systems; adaptive internal model control; robustness;
【基金】 Supported by the Natural Science Foundation of Gansu Province!(ZR- 96 - 0 2 9)
- 【文献出处】 兰州大学学报 ,Journal of Lanzhou University , 编辑部邮箱 ,2000年04期
- 【分类号】TP18
- 【被引频次】2
- 【下载频次】107