Title :
Robust stability analysis of GPC and CRHPC using the theory of extreme point results
Author :
Mañoso, C. ; de Madrid, A.P. ; Hernández, R. ; Dormido, S.
Author_Institution :
Dept. de Inf. y Autom., UNED, Madrid, Spain
Abstract :
Most stability results in model predictive control (MPC) are based on the assumption that the model describes the real plant perfectly. But in reality, the model is always different to the process. In this paper it is shown how the nominal stability results (mean level, constrained receding horizon predictive control, CRHPC, etc.) fail due to the presence of uncertainties, making it necessary to analyse the robust stability. This work provides tools which are easy to use and with low computational cost in order to study the robust stability of the systems under structured uncertainties. These tools are the extreme point results
Keywords :
control system analysis; predictive control; robust control; GPC; constrained receding horizon predictive control; extreme point results; generalised predictive control; mean level; model predictive control; nominal stability results; robust stability analysis; structured uncertainties; Electronic mail; Equations; Finite impulse response filter; Paramagnetic resonance; Polynomials; Predictive control; Predictive models; Robust stability; Stability analysis; Uncertainty;
Conference_Titel :
American Control Conference, 1999. Proceedings of the 1999
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-4990-3
DOI :
10.1109/ACC.1999.786472
