A model of inverse system is proposed and used to drive control laws for induction motors 利用得到的逆系统模型将感应电动机补偿为伪线性系统，而伪线性系统相当于两个解耦的线性子系统。
The inverse control method for pulse width modulation ( pwm ) inverter - fed induction motors is discussed 摘要针对电压源型逆变器供电的感应电动机，应用逆系统理论提出了一种新型控制策略。
A new decouple gpc strategy is designed , in which wavelet networks are used to model the generalized inverse model of the nonlinear system 利用小波网络阶逆系统将非线性多变量系统解耦线性化，对复合后伪线性系统设计预测控制器。
The inverse system analysis technique is employed to establish the error estimation equation and by applying the noncausal wiener fitering theory , the optimal estimator of dynamic loads is derived out 首先，采用逆系统分析方法建立误差估计方程；基次，利用非因果维纳滤波理论导出了动态载荷的优化估计器。
At the same time it has a simple control structure and can linearize the system even it is unnecessary to know mathematical models and actual parameters of original system 而且控制结构简单，在无须知道系统的数学模型和具体参数的情况下，即可实现系统的大范围线性化，从而为逆系统方法的工程实现提供了一条有效途径。
The fuzzy neural network is used to identify the dynamics of the system to be controlled , the trained fuzzy neural network is used in the inverse system method for chaos control and chaotifying control 采用模糊神经网络洲触被控系统的动态特性，将训练好的神经网络应用于逆系统方法中，实现了混沌系统的控制和混沌化控制。
One is differential geometry method for affine - type nonlinear system , and the other one is based on the inversion of nonlinear system , which is capable of managing general nonlinear system from the theoretical point of view 提出基于仿射神经网络模型的约束非线性模型预测控制。研究非仿射非线性系统反馈线性化方法? ?逆系统方法，及其在非线性模型预测控制中的应用。
Inversion dynamics is an effective technique to decouple system through output feeedback which is very important in the design of unmanned aerial vehicle ( auv ) side force control ( dsfc ) law . but precise uav model is difficult to obtain 采用了一种新的控制结构，利用逆系统的精确解耦和h _控制的较强鲁棒性，对系统的输出解耦控制和系统的鲁棒性进行分别设计。
By combining the idea of inverse system and ann ath - order inverse system , the optimal control theory and the strategy of decentralized and coordinated control , this paper studies the stability control of one machine and multi - machine power system 本文根据逆系统方法、神经网络方法、最优控制理论及分散协调控制理论的特点，综合运用于电力系统单机、多机系统的稳定控制。
For the above methods , the performance of the closed - loop system is analyzed ( 3 ) nonlinear gpc based on wavelet networks inverse system is proposed , in which wavelet network is used to model the a - inverse system of the nonlinear system ( 3 )研究了基于小波网络阶逆系统的非线性广义预测控制：利用小波网络逼近系统阶逆系统，针对复合后的阶时延伪系统设计广义预测控制器。
