当被控对象的特性发生变化时，可对混合神经网络权值及时进行修正并调整控制器参数使控制系统始终保持良好的控制性能。
The control system can adjust the weights of hybrid neural network and the parameters of controller timely to keep good control performance when the character of controlled plant varies.
并用这种改进的共轭梯度法对神经网络PID控制器参数实现在线修正。
The parameters of the neural network PID controller are modified on line by the improved conjugate gradient.
模糊控制器通过对洗衣机初始状态的学习，自动调整并选择合适的布量检测零点，修正水位判定参数。
By studding the initial state of washer, the fuzzy controller automatically adjust and select the appropriate zero point of detecting cloth weight, and correct the judgment parameter of water level.
本文提出一种由自校正调节器—最小方差控制器（以下简记为STR—MV）的双模控制和在线修正不辨识参数所构成的新的自校正控制方法。
This paper presents a new self-tuning control consisting of a dual mode control by use of STR-MV and the on-line regulation parameter which is unnecessary to be identified.
对伺服系统速度环采用模糊PID控制器，利用模糊控制实时修正PID参数，提高了系统的响应速度、控制精度以及鲁棒性；
Velocity loop servo system with fuzzy PID controller, correcting PID parameters instantaneously using fuzzy control, improved response speed, control accuracy and robustness of the system.
本文针对工业控制中一类常见的非线性时变系统，提出了一种利用参数反馈在线修正规则的模糊控制器；
This article puts forward a kind of self organization fuzzy controller with parameter feedback for a kind of common nonlinear time varying system in industry.
基于该辨识模型，设计了一个自适应模糊神经电压控制器，其参数采用改进的BP算法进行在线修正。
Based on the identification model, an adaptive fuzzy neural networks voltage controller was designed. The parameters of the controller are regulated by adopting the novel BP algorithm.
提出一种在线修正pid参数的模糊控制器改进算法。
An improved fuzzy logical algorithm is proposed which is suitable for self tuning parameters online in PID controller.
提出了一种解析规则模糊控制器的改进结构，并引入了能够动态调整模糊控制规则的修正函数；同时，通过遗传算法，实现了模糊控制器控制参数的组合优化设计。
An improved structure of analytic expression based fuzzy controller is proposed, and a modifying function capable of regulating the fuzzy control rules dynamically is introduced.
该方法利用参数调整控制器在线自动修正基本模糊控制器的量化因子和比例因子，从而改善基本模糊控制器对任意设定气压的控制性能。
The properties of the basic fuzzy controllers can be improved through compiling S-function that automatically corrects the quantizing factors Ke and Kc , as well as proportional factor Ku.
该方法利用参数调整控制器在线自动修正基本模糊控制器的量化因子和比例因子，从而改善基本模糊控制器对任意设定气压的控制性能。
The properties of the basic fuzzy controllers can be improved through compiling S-function that automatically corrects the quantizing factors Ke and Kc , as well as proportional factor Ku.
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