The improved GA is used to optimize the parameters of pole assignment control and LQR control about inverted pendulum systems. And the better simulation results are obtained.
运用改进遗传算法来优化极点配置方法和线性二次型调节器方法的倒立摆控制参数，并取得比较好的仿真效果。
This paper presents a class adaptive pole assignment control of servo systems based on neural state estimation and develops the system structure and the weight learning algorithms.
提出了一类基于神经元状态估计器的自适应广义极点配置控制，研究了该控制系统的网络结构和权值学习方法。
This paper presents a class adaptive pole assignment control of servo systems based on neural state estimation and develops the system structure and the weight learning algorithms.
提出了一类基于神经元状态估计器的自适应广义极点配置控制，研究了该控制系统的网络结构和权值学习方法。
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