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在稳定性约束模型预测控制中，稳定性约束可从一级传递到另一级来限制用可控结构形式表示的系统状态向量大小。本文探讨了把线性模型预测控制扩展到非线性稳定性约束模型预测的控制（ＳＣＭＰＣ）；在扩展的情况下，模型预测控制的最优化可直接用于非线性系统模型的控制，同时提供了稳定性约束模型预测控制用于带有输入和状态约束的非线性系统控制算法并将该算法用于仿真。仿真结果表明该算法是有效的。
In stability-constrained model predictive control, stability constraints can be passed from one stage to another to limit the size of the system state vector expressed in a controllable structure. In this paper, we extend the linear model predictive control to the nonlinear stability constrained model predictive control (SCMPC). In the extended case, the model predictive control optimization can be directly used to control the nonlinear system model and provide a stable Sex Constraint Model Predictive control is used for nonlinear system control algorithms with input and state constraints and used for simulation. Simulation results show that the algorithm is effective.