采用动态对角回归神经网络作为辨识器和控制器，实现了机器人轨迹跟踪的最小误差控制。
Using dynamic recurrent neural networks as identification and controller, the minimum error control of robot tracking the idea locus is implemented.
本文将最小误差激励(mee)法推广应用于多机电力系统分散输出反馈控制器的设计。
This paper proposes the application of extended minimum error excitation (MEE) method to designing decentralized output feedback controllers for multi-machine power systems.
定义了线性系统脉冲响应模型的相对模型误差和模型失配时的最小鲁棒指数，并在此基础上分析了各种拍控制器的性能。
Based on the definitions of the relative model error of plus response model in linear system and the minimum index of robustness, the robustness of all kinds of dot-controllers was analyzed.
定义了线性系统脉冲响应模型的相对模型误差和模型失配时的最小鲁棒指数，并在此基础上分析了各种拍控制器的性能。
Based on the definitions of the relative model error of plus response model in linear system and the minimum index of robustness, the robustness of all kinds of dot-controllers was analyzed.
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