A novel internal model control structure with multiple output error feedbacks is proposed in this paper, by means of multi model decomposition technique.
通过对受控对象模型的并行结构分解，引入多重输出误差反馈，构成了一种新的内模控制结构。
Theoretical analysis shows that, pole placement control can be realized using this newly developed internal model control structure just from appropriate selection of the feedback gains.
理论分析表明，采用该内模控制结构，只要适当选择输出误差反馈增益，可实现闭环系统极点的任意配置。
Separate designs of a dual PID controller were presented based on the large time-varying robust digital PID control combining with two degrees of freedom internal model control structure.
在大时变鲁棒数字PID控制方法的基础上，结合二自由度的内模控制结构，实现了控制器参数的数字双PID分离设计。
The simulation model of air defense fire oppugning effect was based on simulation design theory, simulation control mechanism, model internal structure and model algorithm.
从仿真设计原理、仿真控制机制、模型内部结构和模型算法三方面研究防空火力抗击效果的仿真模型。
This paper proposed a method of coordinated control of human- like intelligent based on internal model structure for the first- order and second- order plants with time delay.
针对一阶和二阶纯滞后对象，本文提出了一种基于内模结构的仿人智能协调控制方法。
Optimal tracking performance for a class of uncertainty systems is discussed in the presence of control energy constraint under internal model control (IMC) structure.
在内模控制(IMC)结构下，对控制能量存在约束时一类不确定系统所能达到的最优跟踪性能进行了探讨。
The optimal control and simulation method for systems with stochastic perturbation were investigated in the case that control effort is to be considered under internal model control (IMC) structure.
在内模控制（IMC）结构下对控制能量存在约束时一类随机摄动系统的最优控制及其仿真方法作了探讨。
Based on MATLAB, simulation results show that internal model control has simple structure and is easy to be designed and readjusted, so it has certain application value.
并基于MATLAB仿真研究表明，线性时滞过程的内模控制具有较好的鲁棒性，有一定的应用价值。
Simulation shows that if chosen the appropriate ANN structure and training data quantity, its ANN internal model self-tuning control can be realized and the results can be acceptable.
仿真研究表明，只要恰当地选择神经网络正、逆模型的结构和辨识数据的长度等参数，实现加热炉神经网络内模自校正控制的结果是令人满意的。
Simulation shows that if chosen the appropriate ANN structure and training data quantity, its ANN internal model self-tuning control can be realized and the results can be acceptable.
仿真研究表明，只要恰当地选择神经网络正、逆模型的结构和辨识数据的长度等参数，实现加热炉神经网络内模自校正控制的结果是令人满意的。
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