当模型复杂且非线性时（换句话说，在线性方式下参数不共变），或者当模型涉及多于两三个不确定参数时，使用该方法。
The method is used when the model is complex and nonlinear (that is, parameters do not co-vary in a linear manner), or when the model involves more than just two or three uncertain parameters.
烧结是一个典型的时变、非线性、大滞后的系统，很难用一个确定的数学模型去描述整个过程。
As sinter is a typical time varying and nonlinear system with large delay time, it is difficult to describe the whole process using a mathematical model.
针对其存在非线性、参数时变和大延迟等难以控制的特性，提出基于T - S模糊模型的预测函数控制新方法。
As the nonlinearity, time-varying parameters and large lag make the control difficult, a predictive functional control method based on T-S (Takagi-Sugeno) fuzzy model is presented.
基于复杂工艺过程的时变、非线性、大滞后的系统，很难用一个确定的数学模型去描述整个过程。
Based on a typical time varying and nonlinear system with large delay time, it is difficult to describe the whole process using a mathematical model.
无模型控制方法非常适用于实际的阶数难以知道或难以辨识，且是时变的非线性系统。
The model-free control is especially useful for real nonlinear systems whose orders and modeling are very difficult to be known and time varying.
多模型控制是解决系统时变、非线性、参数不确定性等复杂问题得一种有效方法。
Multiple model control is an effective way for solving complicated problems such as time varying, nonlinear and parameters uncertainty.
针对高速公路可变速度控制是一个非线性时变系统，难于用数学模型准确建模这一特点，提出了神经网络控制方法。
The variable speed control for freeway traffic is a nonlinear and time variable system, it is difficult to model with a mathematical model. A neural network control method is put forward.
在考虑齿轮时变啮合刚度的情况下，建立了齿轮耦合的转子-轴承系统的非线性动力学模型。
Considering the time varying meshing stiffness of gear pair, the nonlinear dynamic model of a geared rotor bearing system is established.
此无模型控制方法非常适用于实际的模型参数难以辨识，且是时变的非线性系统。
The model-free control is especially useful for real nonlinear systems whose model parameter are very difficult to be identified and time varying.
针对实际工业生产过程中的非线性、时变不确定性，提出了一种基于线性化误差模型的自适应控制系统。
In order to overcome the nonlinearity and time-varying uncertainty of actual industrial processes, an adaptive control system based on linearization error model is proposed.
有许多复杂的系统是无法用传统方法对它定义，特别是那些非线性的动态时变系统，还不能建立有效的数学模型和控制方法。
Many complicated systems, especially nonlinear dynamic time-variable system, can not be defined by conventional methods which haven't been built effective mathematic model and control method.
针对非线性时变系统在自适应控制过程中瞬态响应差的问题，提出了一种基于多模型自适应控制的模型切换算法。
A model switching algorithm based on multi-model adaptive control is presented to solve the problem of poor transient response in the adaptive control of nonlinear time-varying system.
针对非线性、时变的帆船航行系统，提出了一种基于T - S模糊模型的帆船模糊自适应控制新方法。
A new fuzzy adaptive control method based on a T-S fuzzy model is proposed for the nonlinear and time-variant navigation systems of sailboats.
针对高速公路限速控制是一个非线性时变系统、难以用数学模型准确建模这一特点，提出了R BF神经网络控制方法。
The control for speed limitation on freeway is a nonlinear and time variable system, it is difficult to model with a mathematical model. A control method based on RBF Neural Network is put forward.
针对非线性时变的发酵过程，建立了用于产物浓度预估的支持向量机(SVM)模型。
In accordance with the features of non-linear and time varying for ferment process, a support vector machines (SVM) model is established for estimating the concentration of product.
针对工业过程和实际控制对象的慢时变非线性的特点，设计了一种预测模型的单神经元PI控制器。
A single neuron PI controller with predictive model is designed according to nonlinear systems of many industry processes and practical plants.
针对火电厂锅炉过热系统的时变和非线性的特点，提出了模糊多模型的控制方法。
A fuzzy multi-model control method is proposed for the characteristics of the super-heated system with time varying and nonlinearity in the power plant.
研究表明，液压系统模型是多变量、慢时变和非线性的。
Study showed that the hydraulic control system model is multi-variable, slow time-varying and non-linear.
模糊控制适用于数学模型未知的，复杂的非线性、时变、滞后系统的控制。
Fuzzy control is suit for nonlinear and hysteretic system whose model is unknown.
系统模型考虑了时变时滞、参数摄动以及非线性等多重因素。
The system model contains multiple factors such as time-varying delay, parameter perturbation and nonlinear.
氧乐果合成过程具有非线性、时变和不确定性的特点，难以采用常规的建模方法建立模型。
Omethoate synthesis process has the characteristic of the time-variant, nonlinear and uncertainties. It is difficult to model using the conventional modeling methods.
高速公路限速控制是一个非线性时变系统，难于用数学模型准确建模，提出一种模糊神经网络实现限速控制。
The control for speed limit on expressway is a nonlinear and time variable system, it is difficult to simulate with a mathematical model. A neuro-fuzzy network is proposed to solve the problem.
针对液压弯辊系统数学模型的非线性、时变特性，本文设计了一种模糊神经网络模型参考自适应控制器。
In view of the time-variable and nonlinear characteristics of mathematical model of hydraulic bending roll system, this thesis design a new nonlinear adaptive controler based on fuzzy neural network.
由于T_S模糊模型每条规则的结论部分是一个线性模型，因此整个模糊模型可以看作一个线性时变系统，从而将模糊预测控制器中的非线性优化问题转化为一个线性二次寻优问题，以方便求解。
Since the conclusion part is linear, the T_S fuzzy model can be treated as a linear time_varying system, the nonlinear program in NMPC turns into a linear quadratic problem that can be easily solved.
由于宏观经济系统是一个大型复杂系统，存在着非线性、时滞和时变，因此建立一个实用的宏观经济模型并不容易。
Because macroeconomic system is a big complicated system and it exists nonlinear, time lag and time change, it is difficult to establish a applied macroeconomic model.
水轮机调速系统是典型的具有非最小相位、非线性、时变特性的复杂控制系统，难以建立精确的数学模型。
To the question of the hydraulic turbine regulating system, this paper discusses fuzzy neural network control (FNNC) based on the character of fuzzy logic and neural network theory.
高速公路交通流模型是一个高阶非线性时变系统，这使得该模型的辨识问题成为一个非常困难的问题。
The macro model of traffic flow in freeway is a high order, nonlinear and time variant system which makes the problem of its identification become very difficult.
对于像航空发动机这样复杂的非线性系统，基于对象精确数学模型的PID控制方法的自适应性较差，难以适应具有非线性、时变不确定性的被控对象。
Complicated nonlinear systems such as aircraft engines. PID control method which is based on precise mathematical model has poor adaptability and is not adaptive to nonlinear and time-variant plants.
建立了两级星型齿轮传动系统的非线性动力学分析模型，模型中考虑了系统的综合啮合误差、时变啮合刚度以及齿侧间隙。
A dynamic analysis model in which the gear error and the time-varying stiffness and backlash are included is established for a 2-stage star gear train.
论文第二章提出了一种非线性优化网络“时变步长”修正模型，并较优地实现格型结构的自适应预测。
Theory of the adaptive filter by ANN is analysed , then a bond network is built to implement stable alternate structure adaptive filters for high speed real-time applications.
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