所设计的自组织模糊控制器，其模糊控制规则用解析形式进行描述，并通过修正因子的在线调整而改变，适应了系统动态响应的过程。
As for the fuzzy controller, the rule is depicted with analytic form and changed through self-regulating correction factor on line, so that it ADAPTS the system dynamic process.
而实际要求的控制规则应是可以自调整的。
本论文提出了一种控制规则自调整模糊控制器的设计方案。
This paper adopts a fuzzy rule self-adjust control method to the need of industrial constant temperature control.
提出了一种简化模糊控制的方案，大大减少了模糊控制规则的数目，简化了控制策略、控制器的设计及调整过程。
And we brought forward a sample fuzzy control method that could lessen the number of the rules of the fuzzy control, make sample the design and adjustment of the control policy and control implement.
设计了一种在线可调整的模糊控制器，其模糊控制规则表可以用解析的方法进行计算。
An adjustable fuzzy controller of which the fuzzy control rule table can be obtained by numerical calculation is designed.
详细讨论了在参数自调整模糊控制器中使用的模糊控制规则和模糊调整规则表的设计步骤。
The design rules of the fuzzy control table and fuzzy adjustable scheme are also discussed for the use of the fuzzy control with selfadjustment parameters.
针对模糊控制稳态精度较差的问题，提出了“双模”模糊控制器，通过调整因子来优化控制规则。
The dual mode ambiguity controller, which optimizes the controll rule by adjusting factors, works out the solution to the problem of poor stable precision of ambiguity controlling.
以车辆操纵稳定性及行驶平顺性为控制目标，提出一种在线可调整的模糊控制算法，其模糊控制规则表可以用解析方法得到。
To improve the riding comfort and handling safety of a vehicle, an adjustable fuzzy control algorithm, whose fuzzy control rule table can be obtained with the numerical calculation.
该模型无需事先确定模糊控制规则，并能通过神经网络的结构及参数学习调整模糊神经网络的结构。
By using this model, people need not select any fuzzy logic in advance, and can adjust the network structure by the structure and parameter learning of the neural network.
模糊pd控制研究了采用模糊控制规则调整PD控制的增益，以提高整个控制系统的性能。
Fuzzy PD control emphasizes how to adjust the gains of PD control to improve the performance of the system.
采用带有自调整因子的模糊控制规则设计了有源滤波器直流侧电压的模糊控制器。
A fuzzy controller for capacitor voltage at DC side is designed by using fuzzy control rule with self-adjusting factors.
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.
应用一种变结构神经网络算法对初始化的模糊规则进行调整，提高模糊控制规则的自学习和自适应能力。
A kind of variable structure neural network algorithm is adopted to adjust fuzzy rules, and improves the ability of self-studying and self-adjusting in fuzzy control rules.
采用自定中心、非线性量化、控制规则自调整等方法实现了模糊控制算法的自适应。
The self-adaptive fuzzy control algorithm was achieved by using auto-center, non-linear quantification, and self-adjust rules and so on.
该控制器采用分段解析函数控制规则，函数运算结果直接作为输出控制量，简化了模糊处理过程，且使得输出控制量参数具有自调整能力。
Fuzzy Algorithm is proposed in this paper. The controller adopts subsection analysis function control rules. The result of the function computation directly ACTS as the output control variable.
这种自适应模糊控制器基于模糊推理规则自学习和自调整的控制算法，无需知道太多的专家控制规则，因此解决了制冷系统MIMO模糊推理规则难以获取的问题。
This adaptive fuzzy controller is based on fuzzy inference rules self-learning without needing so much expert control rules, which solves the problem of acquiring MIMO fuzzy inference rules.
在对模糊规则的仿真试验和调整的基础上，得到了实际用于模糊控制器软件设计的控制规则（第六章）。
A fuzzy model of 3-Dimensional PID parameter regulating rules is established, which can be used in self-adaptive fuzzy controller through simulating tests.
提出了一种规则自校正模糊控制器 ，并将其用于交流伺服系统的控制中 ，设计了一种在线的模糊推理算法 ，使得模糊控制规则可以得到实时在线的调整 。
On the basis of manipulators theoretical model of the operating arm, the self-tuning fuzzy controllers model of predictive control will be constructed.
提出了一种规则自校正模糊控制器 ，并将其用于交流伺服系统的控制中 ，设计了一种在线的模糊推理算法 ，使得模糊控制规则可以得到实时在线的调整 。
On the basis of manipulators theoretical model of the operating arm, the self-tuning fuzzy controllers model of predictive control will be constructed.
应用推荐