A nonlinear model predictive control (NMPC) strategy based on T_S fuzzy model is proposed.
提出了一种新的基于T_S模糊模型的非线性预测控制策略。
A neural network model is used to predict the dynamic response of the turboshaft engine and generate the predictive model of the NMPC;
利用神经元网络模型预测涡轴发动机动态响应过程，得到预测模型；
Develop a nonlinear model predictive control (NMPC) for SOFC application. NMPC is well suited in the nonlinear control environment with specified constraints.
建立了基于模型方程的SOFC非线性模型预测控制算法(NMPC)应用。
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。
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