A robust adaptive tracking control method is presented based on the fuzzy T-S model.
提出了一种基于T - S模糊模型和自适应神经网络的跟踪控制方法。
Robust model predictive control is proposed for a class of nonlinear systems with constraint inputs based on fuzzy T-S model.
针对一类基于模糊T-S模型的输入受限非线性系统提出了鲁棒模型预测控制。
The problem of fuzzy modeling for a class of nonlinear time-delay systems with constraint inputs by fuzzy T-S model is addressed.
利用模糊T-S模型对一类输入受限的非线性时滞系统进行建模；
Based on fuzzy T-S model, a fuzzy method with self-learning capability for batch process modeling and optimal control is presented.
基于模糊t - S模型，提出一种具有自学习能力的模糊方法用于批过程建模和最优控制。
The fuzzy T-S model is used to approximate the nonlinear systems, and the fuzzy control law of the fuzzy model is derived from the linear matrix inequality.
首先，采用模糊T-S模型来对非线性系统建模，由线性矩阵不等式得到模糊模型的控制律。
Combining both kinds of fuzzy logic forms including fuzzy T-S model and adaptive fuzzy logic systems, this paper presents an adaptive control scheme for a class of nonlinear systems.
针对一类非线性系统，把模糊t - S模型和自适应模糊逻辑系统这两种模糊逻辑方式结合起来，提出了一种自适应控制方案。
Combining both kinds of fuzzy logic forms including fuzzy T-S model and adaptive fuzzy logic systems, this paper presents an adaptive control scheme for a class of nonlinear systems.
针对一类复杂非线性系统，把模糊t - S模型和自适应模糊逻辑系统结合起来，提出了一种跟踪控制方案。
Combining both kinds of fuzzy logic forms including fuzzy T-S model and adaptive fuzzy logic systems, this paper presents an adaptive control scheme for a class of nonlinear systems.
针对一类非线性系统，把模糊t - S模型和自适应模糊逻辑系统两种模糊逻辑方式结合起来，提出了一种基于观测器的跟踪控制方案。
The stabilization criteria for nonlinear time-delay system described by fuzzy T-S model are proposed on (condition) that the time-delay is precisely available via memory state feedback strategy.
基于记忆型状态反馈策略，首先给出由T - S模糊模型描述的非线性时滞系统在时滞精确已知情况下的鲁棒镇定准则；然后给出非线性时滞系统在时滞未知情况下的鲁棒自适应控制策略。
Combining both kinds of fuzzy logic forms including fuzzy T-S model and adaptive fuzzy logic systems, this paper presents an observer-based tracking control scheme for a class of nonlinear systems.
针对一类非线性系统，把模糊t - S模型和自适应模糊逻辑系统两种模糊逻辑方式结合起来，提出了一种基于观测器的跟踪控制方案。
Combining both kinds of fuzzy logic forms including fuzzy T-S model and adaptive fuzzy logic systems, this paper presents an observer-based tracking control scheme for a class of nonlinear systems.
针对一类非线性系统，把模糊t - S模型和自适应模糊逻辑系统这两种模糊逻辑方式结合起来，提出了一种自适应控制方案。
Combining both kinds of fuzzy logic forms including fuzzy T-S model and adaptive fuzzy logic systems, this paper presents an observer-based tracking control scheme for a class of nonlinear systems.
针对一类复杂非线性系统，把模糊t - S模型和自适应模糊逻辑系统结合起来，提出了一种跟踪控制方案。
Using T-S fuzzy model as an approximation, the nonlinear chaotic system is fuzzy and translated into local linear model.
采用模糊动态模型逼近混沌非线性系统，将混沌非线性系统模糊化为局部线性模型。
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.
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。
By approximating the nonlinear chaotic system with a t s fuzzy model, the nonlinear chaotic system is fuzzed into a local linear model.
采用模糊动态模型逼近非线性混沌系统，将非线性混沌系统模糊化为局部线性模型。
Nonlinear system is described based on T-S fuzzy dynamical model, and the nonlinear system is translated into local linear model by fuzzy method.
采用T - S模糊动态模型描述非线性系统，并将非线性系统模糊化为局部线性模型。
Combining both kinds of fuzzy logic forms including fuzzy t s model and adaptive fuzzy logic systems, this paper presents an observer based control scheme for a class of nonlinear systems.
针对一类非线性系统，把模糊t S模型和自适应模糊逻辑系统两类模糊逻辑方式结合起来，提出了一种基于观测器的控制方案。
On the basis of a evolving clustering method (ECM), a new modeling approach of T-S type dynamic fuzzy inference model is proposed.
以一种进化聚类算法(ecm)为基础，提出了一种新的T - S型动态模糊推理模型的建模算法。
Variable parameter PID control for the controlled object is designed by the method of segment linearization. Furthermore, T-S model based fuzzy PID control strategy is put forward.
通过分析被控对象的特性，采用分段线性化的方法设计变参数PID控制器，进而给出基于T-S模型的模糊PID控制策略；
In order to solve the difficult modeling problem of the lithopone calcination process, this paper proposes an adaptive neural fuzzy inference systems (ANFIS) modeling method based on t s model.
针对锌钡白干燥煅烧过程建模难的问题，提出了一种基于T S模型的自适应神经模糊推理系统(ANFIS)建模方法。
T s fuzzy control model is established. It has gained favorable control effect for the hydraulic pressure set with nonlinear characteristic.
建立了T - S模糊控制模型，对于具有非线性特性的液压执行机构，控制效果良好。
Based on T-S fuzzy model, the guaranteed cost control problem of a class of uncertain nonlinear systems with input and state time delay is discussed.
针对一类具有输入与状态时滞的参数不确定非线性系统，基于T - S模糊模型，讨论该系统的保性能控制问题。
Aiming at the strong nonlinear multiple variable coupling system, a new multivariable internal model control based on T-S fuzzy model was proposed.
针对强非线性、多变量耦合系统，提出了一种基于动态t - S模糊模型的约束内模控制策略。
Kalman filter of the kind of equations was calculated with T-SFIMMA algorithm based on adaptive Kalman filter algorithm of T-S fuzzy model, realize the tracking and automatic switchover of models.
对各方程序卡尔曼滤波，通过T - SFIMMA算法进行基于T - S模糊模型的自适应卡尔曼滤波计算，实现系统模型的实时跟踪与自动转换。
Using T-S fuzzy model as an approximation for nonlinear chaotic system, the nonlinear chaotic system has been fuzzy into local linear model.
采用模糊动态模型逼近非线性混沌系统，将非线性混沌系统模糊化为局部线性模型。
Fuzzy basis function network (FBFN) based on t s fuzzy model is given. A general approach for fault information detection in unknown systems using FBFN is present.
给出了基于T S模型的模糊基函数网络(FBFN)，并提出了一种基于FBFN的未知系统故障信息检测通用方法。
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。
Noise canceling by using fuzzy inference system is studied. A kind of nonlinear noise cancellation algorithm based on T-S fuzzy model is proposed.
对模糊推理系统在噪声消除中的应用进行了研究，提出了一种基于T - S模糊模型的模糊非线性噪声消除算法。
A design of T-S model based fuzzy controller for nonlinear system with uncertain time-delay was proposed.
讨论了一类由T - S模糊模型表示的不确定时滞非线性系统的模糊控制器设计问题。
A design of T-S model based fuzzy controller for nonlinear system with uncertain time-delay was proposed.
讨论了一类由T - S模糊模型表示的不确定时滞非线性系统的模糊控制器设计问题。
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