一类带有输入和状态约束的非线性稳定性约束模型预测控制的研究

Nonlinear Stability-Constrained Model Predictive Control with Input and State Constraints

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 a stability constraint is propagated from stage to stage to limit magnitude of the state vector in a controllable form. This paper concerns extensions of linear model predictive control to the nonlinear stability-constrained model predictive control in which the nonlinear system model is used directly in the Model Predictive Control optimization and presents algorithm about SCMPC which is applied to nonlinear systems with arbitrary constraints on the control and state. Simulation results proves it much effective.