The vibration of nonlinear structure is difficult to control precisely by means of linear control theory. A method that combines neural networks with inverse system theory is proposed.
针对非线性结构振动控制难以用线性控制方法精确控制的情况，提出神经网络离散逆系统方法。
The inverse dynamic method of manipulator and the Linear Quadrics (LQ) optimum control method are employed to investigate the problems of trajectory tracking and eliminating the remaining vibration.
利用机械臂逆动力学方法和线性二次型（LQ）最优控制方法讨论刚柔性耦合机械臂的轨迹跟踪控制问题和消除残余振动的控制问题。
Adaptive inverse control is a very simple and highly effective way for controlling linear or nonlinear control systems.
无论对于线性的还是非线性的对象，自适应逆控制都是一种简单而有效的控制方法。
Firstly, the whole control system can exhibit satisfactory dynamic result only by perfect matching the controller and composite pseudo linear system in the generalized inverse control.
首先，在广义逆系统控制中，控制器必须与复合伪线性系统的传递函数相互配合才能使整个控制系统达到满意的动态控制效果。
This paper discusses the synthetical control designing problem for discrete linear stochastic systems with generalized inverse theory and the singular value decomposition theory.
利用广义逆理论和奇异值分解理论，研究离散型线性随机系统的综合控制设计问题。
The results of test show that this inverse model feed-forward compensator has effectively reduced the non-linear error of the system and has improved the control precision of GMA.
实验结果表明，逆模前馈补偿器有效地减小了系统的非线性误差，提高了执行器的控制精度。
The results of test show that this inverse model feed-forward compensator has effectively reduced the non-linear error of the system and has improved the control precision of GMA.
实验结果表明，逆模前馈补偿器有效地减小了系统的非线性误差，提高了执行器的控制精度。
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