The multi - objective and layered steady - optimization method of model predictive control for stable and integrating systems is proposed from the application background of optimization and control for complex industrial processes . firstly , the meanings of multi - objective and layered optimization is explained in detail and the steady - state optimization based on quadratic programming is presented to solve the multi - objective and layered optimization in the context of two - stage model predictive control formulation . 2 作者系统地阐述复杂工业过程多目标分层优化要求的含义，针对包含积分对象与稳定对象的多变量系统，在预测控制两级分层优化结构的基础上，提出了基于二次规划的多目标稳态优化方法。
It will make the huge computation , especially in the multiple systems and real time systems , so that the virtue of predictive control will not be embodiment . in order to cope with these basic problems , a new fast generalized predictive control ( fgpc ) algorithm is proposed in this paper , which is particularly effective for the typical industrial processes that can be regarded as the first - or second - order process model with a time - delay . the algorithm has good adaptive ability and robustness with low - cost computation , simple control structure , and pid - like formulation 但是，推广到实际工业过程系统，对于一般的典型工业系统，其结构并不复杂，大多数可以描述为一阶或二阶系统加纯滞后环节，对于这种情况，以预测控制的分支之一广义预测控制考虑，其矩阵的计算量将很大，特别是矩阵的求逆运算，如果是多变量系统，计算量更大，因此，很不适合工业过程中一些要求快速，实时的系统，针对这种情况，提出一种快速的广义预测控制算法是很有必要的，该在保证稳定性的同时，也需要使系统具有强鲁棒性。
