کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
689266 | 889600 | 2013 | 9 صفحه PDF | دانلود رایگان |

This work considers enhancing the stability and improving the economic performance of nonlinear model predictive control in the presence of disturbances or model uncertainties. First, a robust control Lyapunov function (RCLF)-based predictive control strategy is proposed. Second, the approximate dynamic programming (ADP) is employed to further improve regulation performance. Finally, the ADP and RCLF-MPC are combined to provide a switching control scheme, which is illustrated on a CSTR example to show its effectiveness.
• Construction of robust control Lyapunov function for nonlinear affine system.
• Robust control Lyapunov function is embedded into model predictive control.
• Approximate dynamic programming improves regulation performance.
• The approach can regulate nonlinear affine systems under bounded uncertainties.
Journal: Journal of Process Control - Volume 23, Issue 6, July 2013, Pages 852–860