本文将模糊优化控制方法应用于对柴油机的燃油消耗率进行控制。
This peper applies the fuzzy optimizing control method to control fuel consumption rate of a diesedcngine.
最后采用第一种改进方案，实现了输油泵系统的模糊优化控制，并且消除系统切换时的扰动。
The paper adopts the first advance scheme to realize the fuzzy optimization control of Oil Feeding Pump System and eliminates the turbulence generated by changing control ways.
对每个控制模块设计了相应的模糊优化控制算法，并用改进的BP神经网络实现算法的模糊关系。
Fuzzy optimal control arithmetic was designed for each module, and an improved BP neural network was introduced to implement the fuzzy relation.
通过分析对模糊控制器作优化的原理，提出了一种新的优化设计方法。
By analyzing the principle of optimization, a new optimization method for fuzzy controller's design is put forward.
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。
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.
设计了一种基于RBF网络和遗传优化的船舶操纵模糊控制器。
A fuzzy controller for ship steering based on RBF networks and genetic algorithms is designed.
设计了基于CAN总线的预焙铝电解槽计算机控制系统的总体方案及基于混沌优化的电解质温度模糊控制器。
The computer control system scheme of Aluminum electrolytic cell based on CAN bus and Fuzzy controller based on chaos optimization are designed.
文中提出了一种优化设计方法，使模糊控制性能接近最优，并保证了自适应控制的稳定性。
We come up with a new method to optimize the fuzzy logic controller, which makes the controller approach to the most optimization, and ensure the stability of self-tuning control.
建立了UPFC的频域模型，给出了主控制和辅助控制的框图，推导了模糊阻尼控制器参数优化的公式。
The UPFC power frequency model with its main and supplementary control block diagrams and the formulation for FDC parameter optimization are presented.
提出一种模糊控制与PID控制相结合的优化算法，实现了对高频加热设备温度系统的良好控制。
An optimized algorithm combining the fuzzy control with the PID control has been put forward, realizing a good control of the temperature system in the high frequency heating equipment.
本文将采用模糊控制设计防滑刹车的控制策略，并应用自调整因子算法对模糊控制的参数进行优化。
In this paper, a fuzzy control approach is used in the design of the control strategy of anti-skid braking systems, with self-regulation factors for optimization of the fuzzy control parameters.
利用免疫进化算法，提出了一种新的模糊控制器优化设计方法。
By use of immune evolutionary algorithm, a new optimal method of fuzzy controller was presented.
本文提出了一种基于经验数据的T - S型模糊控制器设计与优化方法，并在倒立摆上进行了验证。
An approach for designing and optimizing Takagi-Sugeno type fuzzy logic controller is proposed in this paper, which is based on experience data.
本文针对单瓶颈节点网络，考虑两个饱和非线性因素，制定控制规则，寻找优化参数，设计模糊控制器。
In this paper, single bottleneck node network is considered. With two saturation factors, we make control rules, find optimal parameters and design the controller.
采用浮点数编码对模糊控制规则进行优化，既提高了运算效率和计算精度，又保证了控制系统的快速性和全局最优性。
Floating-point coding is adopted to optimize fuzzy control rules, it can improve the efficiency and accuracy of calculation, also can guarantee fastness and global optimal.
与普通模糊控制以及仅采用遗传优化的模糊控制相比，具有在线自调整功能的模糊控制具有更好的控制效果和鲁棒性。
Comparing with the conventional FLC and the FLC optimized by GA only, the FLC with online self-tuning performance has better control effect and robustness.
利用模糊控制器的模糊推理能力来实现煤气阀门开度在线调整，以达到优化控制的目的。
It can use the fuzzy theory of the controller to realize the adjustment of the valve, which can make it control better.
利用模糊控制器的模糊推理能力来实现PID控制器参数在线调整，以达到优化控制的目的。
By using ability of fuzzy reasoning, realize at-line adjust to PID controller parameter, to achieve optimize control.
所以，本论文最后采用了遗传算法对输入输出语言变量的隶属函数进行优化以改善模糊控制器的性能。
So, at last, Genetic Algorithms are capitalized on to optimize the membership functions of the input and output linguistic variables of the fuzzy controller so as to better its performance.
为了避免模糊控制器设计过程中参数的大量调试工作，并使其具有最佳的控制性能，本文首次将混沌优化方法应用于模糊控制器参数设计。
In order to improve the control performance and avoid a great deal of adjusting work of the parameters, we applied chaos optimization method in design of fuzzy controller firstly.
本文提出一种基于基因算法优化的自学习模糊控制器的设计。
This paper proposes a design of the self adaptive learning fuzzy controller based on Genetic Algorithms optimization.
本文提出一种基于基因算法优化的自学习模糊控制器的设计。
This paper proposes a design of the self adaptive learning fuzzy controller based on Genetic Algorithms optimization.
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