在分析自适应模糊控制及PID参数变化对系统性能影响的基础上，提出在动态过程中对PID参数进行整定。
Based on the analysis of self-adaptive fuzzy control and the influence of PID control parameter changes, the rules of fuzzy adjustment of PID parameters in a dynamic process are put forward.
在分析自适应模糊控制及PID参数变化对系统性能影响的基础上，提出在动态过程中对PID参数进行整定。
Based on the analysis of self-adaptive fuzzy control and the influence of PID control parameter changes, the rules of fuzzy adjustment of PID parameters in a dynamic process is put forward.
论述了综合运用非线性动态逆、自适应模糊系统和滑模控制的优点进行飞行控制律设计的方法。
The design of the flight controller that exploits the advantages of the nonlinear dynamic inversion, adaptive fuzzy system and slide model control is discussed.
利用模糊控制在线自适应调整PID控制器的参数，从而使系统的静态和动态性能指标较为理想。
Fuzzy control is used to adjust the parameters of PID control on-line, accordingly it can make static and dynamic performance index comparatively ideal.
提出一种基于GA的自适应模糊积分型滑模控制策略，并将其用于具有非线性动态摩擦力的单轴运动控制系统中。
An adaptive fuzzy integral type sliding mode control method based on GA was proposed to control single-axis motion control system with nonlinear dynamic friction.
对一类非线性多变量未知动态系统，提出了一种模糊自适应控制策略。
A fuzzy adaptive tracking control scheme for a class of unknown multivariable nonlinear systems is presented.
对一般非线性系统，推导了一种综合运用非线性动态逆、自适应模糊逻辑系统和滑动模态控制进行控制律设计的方法。
For general nonlinear system, a control law design method which integrated the nonlinear dynamic inverse theory, adaptive fuzzy system and slide model control is developed.
其中直接自适应模糊控制器还与PID控制器一起组成并行控制系统来抑制系统静态误差和动态干扰。
Adaptive fuzzy controller was combined with PID controller to compose parallel control system, which was aimed at reducing static error and suppressing dynamic disturbance of the whole system.
仿真实验结果表明，具有自适应神经网络的模糊推理系统控制的异步电机矢量控制系统不仅动态和稳态性能都得到提高，而且具有较强的鲁棒性。
Simulation results show that the induction motor vector control system with adaptive neuro-fuzzy inference system can improve the static and dynamic performance of the motor and has good robust.
针对仿射非线性系统，提出了一种新型的基于动态递归模糊神经网络(DRFNN)的间接自适应控制器。
A novel indirect adaptive controller based on dynamic recurrent fuzzy neural network (DRFNN) is proposed for affine nonlinear system.
采用模糊动态模型研究大范围、高阶非线性系统的自适应模糊控制问题。
The adaptive fuzzy control for nonlinear systems with large working range and high order is studied by using fuzzy dynamic models.
自适应模糊控制对系统的调节作用是明显的，能使系统很快在平衡位置达到稳定，改善了系统的动态特性。
The result shows that self-adaptive fuzzy control has better static and dynamic performances than routine fuzzy control.
在分析自适应模糊控制及PID参数变化对系统性能影响的基础上，提出在动态过程中对PID参数进行整定。
The analysis of adaptive fuzzy control and PID parameter change on the impact of system performance based on the dynamic process of PID tuning parameters.
为了改进伺服系统的动态跟随性能，提出了一种位置环模糊自适应PID控制方法。
In order to improve the performance dynamic following of the servo system, a fuzzy self-adapting PID control method is proposed in this paper.
为了改进伺服系统的动态跟随性能，提出了一种位置环模糊自适应PID控制方法。
In order to improve the performance dynamic following of the servo system, a fuzzy self-adapting PID control method is proposed in this paper.
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