该控制器能够根据系统的误差、误差变化及误差积分值自动调整控制器的控制参数，使模糊控制器具有自适应的能力。
The parameter of the controller can be auto-adjusted by the error, error change and the integral value. It makes the fuzzy controller have the ability of self-adaptive.
阐述基于模糊优化算法的导航系统惯性元件误差补偿方法。
The method of error compensation for inertial elements in navigation system based on fuzzy optimal algorithm is presented.
在此基础上设计的模糊自适应控制器能够保证整个闭环系统稳定且跟踪误差收敛到零的一个邻域内。
The fuzzy adaptive controller designed based on this method can guarantees that the closed-loop system is globally stable and the tracking error converges to a neighborhood of zero.
该文讨论了模糊系统的数字逼近特性，同时分析了逼近误差和初始状态误差对模糊系统的影响。
In this paper, the numerical approximation characteristics of fuzzy system are discussed, and the influence of approximation error and initial state error on fuzzy system are analyzed.
将模糊控制与常规pid控制相结合，根据不同的误差、误差变化率对PID的参数进行在线自动调整，这就是PID参数自整定模糊控制器。
Combine blur control with general PID control, on line self-adjusting PID parameters according to different error and error variety-rate, which is called PID parameters self-tuning blur controller.
斜坡根据密度跟踪误差和误差变化情况，通过模糊逻辑对控制器参数进行调整，确定了测量速度。
The ramp metering rate is determined by the PID controller whose parameters are tuned by fuzzy logic according to the density tracking error and error variation.
本文首先分析基本模糊控制系统存在稳态误差的根本原因，然后有针对性地引入两种插值方法对基本模糊控制器进行改进。
First, this paper analyses the essential cause why a basic fuzzy control system has steady-state error, then incorporates interpolation technique to improve basic fuzzy controller.
理论计算和计算机模拟实验结果显示，模糊控制迭代算法的迭代结果其振幅均方误差为0.69%，振幅不均匀度为1.01%。
Computer simulation experiment, as well as theoretical research show that the amplitude mean square error of the iterative output derived from IAFC is 0.69%, and the amplitude un-uniformity is 1.01%.
仿真结果表明，该模糊优化算法对导航系统惯性元件的误差补偿是可行的，而且是有效的，具有一定的实用价值。
The simulation results demonstrate that the fuzzy optimal method has certain validity and feasibility for error compensation of inertial elements in navigation system, it has better practical worth.
对于未知的非线性系统，利用误差滤波方法，提出了一种自适应模糊调节器的设计方法。
For unknown nonlinear systems, by using error filtering method, a design method of adaptive fuzzy regulator is proposed.
通过理论分析，证明了模糊变结构控制系统是全局稳定的，跟踪误差可收敛到零的一个邻域内。
By theoretical analysis, the fuzzy variable structure control system is proved to be globally stable, with tracking errors converging to a neighborhood of zero.
该方法依据系统的轮廓误差，通过自适应模糊控制手段向各联动轴提供附加补偿作用，进而提高CNC系统的轮廓加工精度。
This method provides each axis with an additional compensating function according to the contour errors by adaptive fuzzy inference control, so the CNC system contour machining accuracy is modified.
这两种方法可完全消除量化误差和调节死区，为设计高精度模糊控制系统提供了一种新途径。
The two methods can eliminate quantization errors and adjusting dead zone thoroughly, and provide a new way for designing fuzzy control system with high accuracy.
提出了一种自适应模糊小波神经网络的滑模控制策略，保证系统的跟踪误差和对外界干扰的抑制被衰减到期望的程度。
An adaptive sliding mode control based on fuzzy wavelet network is proposed to guarantee the effects of the tracking error and external disturbances can be attenuated to a specific attenuation level.
计算结果表明，这些模糊控制值与相应工况的优化设计值的相对误差除两个工况外均小于5 %。
The results show that the relative errors between the fuzzy control values and the corresponding optimized design values are less than 5% except two engine work status.
采用RBF神经网络在线补偿不确定项和模糊建模误差，能够使飞机获得满意的控制效果。
Using RBF NN can restore the airplane to the normal state by online regulating the effect of the uncertainties and the error caused by fuzzy modeling.
根据模糊系统的逼近性质，非线性系统可以表示为线性参数化模型加上一建模误差项。
Based on the approximation property of fuzzy systems, a nonlinear system can be expressed as the form of linear parametric model and a modelling error term.
对模糊逼近所带来的误差以及外部干扰项，采用控制补偿方法。
Furthermore, the error resulted from fuzzy approximation and the external disturbances are compensated so that the influence on the system is minimized.
利用灰色理论本身的特征对经济参数进行预测，并运用自适应模糊神经网络对其拟合误差进行预测，从而达到较好的预测效果。
This article utilizes the character of Gray Theory to predict the economy parameter, and then in order to obtain a better predicting effect, the ANFIS is employed to predict its simulating error.
结果表明，与传统的基于误差平方和准则的学习算法相比，采用模糊学习算法可以大大简化网络结构，有效提高模拟精度和效率。
The modeling results showed that the introduction of fuzzy learning method can not only simplify the structure of neural network, but also effectively improve the modeling accuracy and efficiency.
针对常规模糊控制器在控制上存在稳态误差的缺点，在分析产生稳态误差主要原因的基础上，采用插值算法来进行控制。
For the shortcoming of stability error of conventional fuzzy controller, it analyzes the primary reason of having stability error about this controller and USES interpolation algorithm in control.
介绍了一种能够根据位置误差和误差变化率自动调整模糊规则和比例因子的规则可调自适应模糊控制器。
A kind of adaptive fuzzy controller was introduced whose control-rule and scale-gene can be adjusted by itself according to the system position error and error change ratio.
对此提出误差增益补偿算法以减小增益误差，并进一步用模糊补偿替代增益补偿以提高系统的鲁棒性。
The gain error compensation algorithm is proposed to reduce gain error, and moreover fuzzy compensation replacing gain compensation is used to improve the robustness of the system.
普通的模糊控制器是以误差和误差的变化作为输入量，类似常规PD控制器的作用，存在超调、抗干扰能力差的弊端。
With functions as PD controller, general fuzzy controller takes error and error change as its input parameters, which has over shoot and poor anti, disturb ability.
普通的模糊控制器是以误差和误差的变化作为输入量，类似常规PD控制器的作用，存在超调、抗干扰能力差的弊端。
With functions as PD controller, general fuzzy controller takes error and error change as its input parameters, which has over shoot and poor anti, disturb ability.
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