Though optimizing quantification factor and proportionality factor of Fuzzy-PI controller, optimizing the membership function, then make the system response has good dynamic and steady performance.
通过优化模糊pi控制器的量化因子和比例因子，从而优化隶属函数，使控制系统具有很好的稳态和动态性能。
Simulation results implied that output dynamic response performance of secondary element improved greatly by adopting fuzzy auto-tuning PID control, the results attained expect aim .
仿真结果表明采用模糊PID自整定控制后使得二次元件输出动态响应性能大大改善，达到了预期的目标。
Then it discusses the design of Fuzzy control in details, and it also shows the respective curves of the dynamic response during adjusting the torque under the PID and Fuzzy control.
详细论述了系统模糊控制器设计的方法和思路，并给出了转矩调节在PID控制和模糊控制下的动态响应曲线。
The inverter system adopts digital fuzzy controller with feed forward correction and which proportion coefficient and integral coefficient is changeable, so dynamic response is improved.
逆变系统采用带前馈校正的变比例变积分系数的模糊控制器，提高了系统的动态响应指标；
By using control strategy of parameter parameters self-turning fuzzy PID, lead secondary loop the automatic doing control offers excellent dynamic response and stable characteristic.
应用参数自整定模糊pid的控制策略，使自动加药控制具有很好的动态响应和稳态特性。
The fuzzy control is used to ensure the dynamic response speed of the position servo system, and the integral control is used to ensure its steady-state performance.
在系统的动态过程中，利用模糊控制的快速响应能力保证位置随动系统具有较快的动态响应速度；
This paper may serve as the basis of the general theory of dynamic fuzzy random response analysis (including fuzzy random vibration).
本文的理论为进一步建立动态模糊随机响应分析(包括模糊随机振动)的一般理论奠定了基础。
The dynamic response of a truss to fuzzy-random changes in design parameters under stationary random excitation is studied in this paper.
研究了具有模糊随机参数的桁架结构在平稳随机激励下的动力响应。
Simulation results show that the fuzzy controller with self-adjusting parameters makes the system have rapid dynamic response speed and high positioning accuracy.
仿真结果表明，较之常规模糊控制器，采用参数自整定的模糊控制器能使系统获得更快的动态响应速度和更高的定位精度。
The result indicates that the fuzzy model reference learning control has quicker dynamic response and the same steady accuracy as PI control, but its overshoot is slightly larger.
结果表明，模糊模型参考学习控制具有响应快的优点，同时具有与PI控制同样高的稳态精度，但超调量比PI控制稍大。
Finally the simulation test of the fuzzy model is carried out by using GUI in MATLAB, which shows that the model can approximate very well the dynamic response process of the real system...
进而运用MA TLAB的GUI工具对所建模糊模型进行了仿真检验。其结果表明，该模糊模型能很好地逼近实际系统的动态响应过程，从而可为进一步的智能优化控制工作做好铺垫。
Simulation results show that this controller could yield better performance in dynamic response, robustness and anti-interference than both immune controller and fuzzy controller.
仿真结果表明：该模糊免疫控制器能够取得比免疫控制器和模糊控制器更好的动态控制效果，并且在鲁棒性、抗干扰能力方面都更胜一筹。
Simulation results show that this controller could yield better performance in dynamic response, robustness and anti-interference than both immune controller and fuzzy controller.
仿真结果表明：该模糊免疫控制器能够取得比免疫控制器和模糊控制器更好的动态控制效果，并且在鲁棒性、抗干扰能力方面都更胜一筹。
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