• Research on offline identification of T-S model.

    模糊模型离线辨识方法研究。

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  • 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。

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  • A model identification approach of nonlinear systems is presented based on T-S model.

    基于T - S模型,提出一种非线性系统的模型辨识方法。

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  • 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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  • The T-S model is used to extend the fully-decoupled parity equations to fuzzy parity equations for nonlinear systems.

    引入T-S模型将全解耦奇偶方程推广到非线性系统中得到了模糊奇偶方程。

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  • 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。

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  • A novel fuzzy logic controller based on T-S model is proposed for automatic generation control (AGC) system after deregulation.

    本文针对解除管制后的自动发电控制系统(agc)提出了一种新颖的基于T - S模型的模糊逻辑控制器。

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  • 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;

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  • 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。

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  • Moreover, T-S model is used to adjust the dynamic fuzzy rules by the latter neural network, which can improve the adaptability of the control system.

    采用T - S模型,由后件网络动态调整模糊规则,提高控制系统的适应性。

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  • 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。

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  • The paper introduces a kind of adaptive neural-fuzzy inference systems (ANFIS) based on T-S model to deal with the modeling problem of the complex soda carbonization process.

    针对纯碱碳化过程的复杂建模问题,提出基于T-S模型的自适应神经模糊推理系统(ANFIS)的建模方法。

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  • 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;

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  • In the paper online identification based on time window and least square support vector machine (LSSVM) for T-S model is proposed, including structure and parameter identification.

    本文提出了基于时间窗的最小二乘支持向量机t - S模型在线辨识算法,包括结构辨识和参数辨识。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • For nonlinear discrete systems, the T-S model is constructed and the parametric uncertainty and time-delay terms are introduced to make the fuzzy model approach to the original system more exactly.

    针对非线性离散系统,构造t - S模型,引入参数不确定项和时滞项,使得模糊模型能够更精确逼近原系统。

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  • In the U. S., federal funds for repairing water infrastructure-most of which was built around the same time that Henry Ford built the first Model t-are sorely lacking.

    在美国,用于修理供水基础设施(大多建于亨利·福特推出第一辆T型车的时期)的联邦资金极度缺乏。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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