Model Predictive Control of Nonlinear Systems
Model Predictive Control of Nonlinear Systems
复制标题
非线性系统的模型预测控制
DOI：
10.1109/acc.1991.4174827
复制
发表时间：
1991
期刊：
影响因子：
--
通讯作者：
H. Michalska
中科院分区：
文献类型：
--
作者：
D. Mayne;H. Michalska
模型预测控制（MPC）具有稳定具有状态和控制约束的线性和非线性系统的潜力，这是其他方法所不容易提供的。在过程控制文献中，使用的是一个简单的、有限范围的目标函数，它本身并不能保证稳定性；这是通过适当选择目标函数中的一些参数来实现的。另一方面，“系统理论”文献关注稳定性问题，并表明通过在有限视界目标函数中添加适当的稳定性约束，可以保证稳定性。本文探讨了将两种方法的优点结合起来的可能性。
Model Predictive Control (MPC) has the potential, not easily provided by other methods, to stabilize linear and nonlinear systems with state and control constraints. In the process control literature a simple, finite horizon, objective function is employed which does not, per se, guarantee stability; this is obtained by a suitable choice of some parameters in the objective function. The 'system theory' literature, on the other hand, focusses on the stability issue, and shows that by adding an appropriate stability constraint to the finite horizon objective function, stability can be insured. This paper explores the possibility of combining the virtues of both approaches.