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。
The nonlinear plant is approximated by a Takagi-Sugeno fuzzy linear model using local linearization method.
采用局部线性化方法，用T-S模糊线性模型逼近非线性系统。
Combining fuzzy Takagi-Sugeno (T-S) model with adaptive fuzzy logic systems, we present a tracking control scheme for a class of complex 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 fuzzy Takagi-Sugeno (T-S) model with adaptive fuzzy logic systems, we present a tracking control scheme for a class of complex 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。
The problem of fuzzy optimal control for nonlinear time-delay system was considered based on the framework2 of T-S( Takagi-Sugeno) fuzzy model and parallel distributed compensation(PDC) controller.
基于T S模糊模型和平行分布补偿器（PDC） ，讨论了非线性时滞系统的模糊最优问题。
Combining fuzzy Takagi-Sugeno (T-S) model with adaptive fuzzy logic systems, we present a tracking control scheme for a class of complex 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。
The prediction model has very strong self-adaptability because of using adaptive fuzzy neural network based on Sugeno-Tanaka fuzzy model, and the forecast result is also satisfactory.
由于预测中使用了一种基于高木-关野模糊模型的自适应模糊神经网络，从而使预测模型具有很强的自适应能力，预测结果也比较令人满意。
For the inverted pendulum system with multi-variable and nonlinear characteristic, a double closed-loop cascade fuzzy control approach was put forward based on Takagi-Sugeno fuzzy model.
在对火电厂过热汽温控制对象特点分析基础上，保留串级控制抗内扰的性能，结合模糊控制动态特性好的特点，提出了一种复合模糊串级控制设计。
For the inverted pendulum system with multi-variable and nonlinear characteristic, a double closed-loop cascade fuzzy control approach was put forward based on Takagi-Sugeno fuzzy model.
在对火电厂过热汽温控制对象特点分析基础上，保留串级控制抗内扰的性能，结合模糊控制动态特性好的特点，提出了一种复合模糊串级控制设计。
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