【摘要】 通过对系统的信号约束，构成有约束多变量广义预测控制问题，并运用T－H优化神经网络来求解这一复杂的优化问题．在求解过程中，有约束广义预测控制的求解被转化为一个T－H优化电路网络的稳态解．因此可以通过硬件电路或龙格-库塔数值方法进行求取．在一个工业过程模型上的仿真研究证明了这一方法是非常有效的．更多还原

【Abstract】 Through the constrain of the signals of system,this paper drives the constrained multivariablegeneralized predictive control,and solves the complicate optimizing problem with T-H neural network. It istransformed into the solving of a stable state of a T-H optimizing neural networks for the constrained generalized predictive controller. Hence,the solution can be obtained through hardware electricity circuit or RungeKutta numerical algorithm. The simulation research on a process verifies that the method is very effective.更多还原