1 |
MAYNE D Q Model predictive control: recent developments and future promise. Automatica, 2014, 50 (12): 2967- 2986.
doi: 10.1016/j.automatica.2014.10.128
|
2 |
GUAY M, ADETOLA V, DEHAAN D. Robust and adaptive model predictive control of nonlinear systems. London: Institution of Engineering and Technology, 2015.
|
3 |
MAYNE D Q, RAWLINGS J B, RAO C V, et al Constrained model predictive control: stability and optimality. Automatica, 2000, 36 (6): 789- 814.
doi: 10.1016/S0005-1098(99)00214-9
|
4 |
MAYNE D Q, SERON M M, RAKOVI S V Robust model predictive control of constrained linear systems with bounded disturbances. Automatica, 2005, 41 (2): 219- 224.
doi: 10.1016/j.automatica.2004.08.019
|
5 |
MAYNE D Q, KERRIGAN E C. Tube-based robust nonlinear model predictive control. Proc. of the 7th IFAC Symposium on Nonlinear Control Systems, 2007: 110−115.
|
6 |
FALUGI P, MAYNE D Q Getting robustness against unstructured uncertainty: a tube-based MPC approach. IEEE Trans. on Automatic Control, 2014, 59 (5): 1290- 1295.
doi: 10.1109/TAC.2013.2287727
|
7 |
BRUNNER F D, HEEMELS M, ALLGOWER F Robust self-triggered MPC for constrained linear systems: a tube-based approach. Automatica, 2016, 72, 73- 83.
doi: 10.1016/j.automatica.2016.05.004
|
8 |
SUBRAMANIAN S, LUCIA S, ENGELL S. A novel tube-based output feedback MPC for constrained linear systems. Proc. of the American Control Conference, 2017: 3060−3065.
|
9 |
FESHARAKI S J, KAMALI M, SHEIKHOLESLAM F Adaptive tube-based model predictive control for linear systems with parametric uncertainty. IET Control Theory & Applications, 2017, 11 (17): 2947- 2953.
|
10 |
GONZALEZ R, FIACCHINI M, ALAMO T, et al Online robust tube-based MPC for time-varying systems: a practical approach. International Journal of Control, 2011, 84 (6): 1157- 1170.
doi: 10.1080/00207179.2011.594093
|
11 |
BUMROONGSRI P, KHEAWHOM S Robust model predictive control with time-varying tubes. International Journal of Control, Automation and Systems, 2017, 15, 1479- 1484.
doi: 10.1007/s12555-016-0227-z
|
12 |
RAKOVIC S V, KERRIGAN E C, KOURAMAS K I, et al Invariant approximations of the minimal robust positively invariant set. IEEE Trans. on Automatic Control, 2005, 50 (3): 406- 410.
doi: 10.1109/TAC.2005.843854
|
13 |
AGHAEI S, SHEIKHOLESLAM F, FARINA M, et al An MPC-based reference governor approach for offset-free control of constrained linear systems. International Journal of Control, 2013, 86 (9): 1534- 1539.
doi: 10.1080/00207179.2013.789142
|
14 |
GARONE E, NICOTRA M M Explicit reference governor for constrained nonlinear systems. IEEE Trans. on Automatic Control, 2016, 61 (5): 1379- 1384.
doi: 10.1109/TAC.2015.2476195
|
15 |
KLAUCO M, KALUZ M, KVASNICA M Real-time implementation of an explicit MPC-based reference governor for control of a magnetic levitation system. Control Engineering Practice, 2017, 60, 99- 105.
doi: 10.1016/j.conengprac.2017.01.001
|
16 |
ZHOU J, CANOVA M, SERRANI A Non-intrusive reference governors for over-actuated linear systems. IEEE Trans. on Automatic Control, 2017, 62 (9): 4734- 4740.
doi: 10.1109/TAC.2016.2628167
|
17 |
TEDESCO F, OCAMPO-MARTINEZ C, CASAVOLA A, et al Centralized and distributed command governor approaches for water supply systems management. IEEE Trans. on Systems, Man, and Cybernetics: Systems, 2018, 48 (4): 586- 595.
doi: 10.1109/TSMC.2016.2612361
|
18 |
GARONE E, NICOTRA M, NTOGRAMATZIDIS L Explicit reference governor for linear systems. International Journal of Control, 2018, 91 (6): 1415- 1430.
doi: 10.1080/00207179.2017.1317832
|
19 |
GARONE E, D C CAIRANO S, KOLMANOVSKY I Reference and command governors for systems with constraints: a survey on theory and applications. Automatica, 2017, 75, 306- 328.
doi: 10.1016/j.automatica.2016.08.013
|
20 |
TATJEWSKI P Advanced control and on-line process optimization in multilayer structures. Annual Review in Control, 2008, 32 (1): 71- 85.
doi: 10.1016/j.arcontrol.2008.03.003
|
21 |
HUANG G S, WANG S W Two-loop robust model predictive control for the temperature control of air-handling units. HVAC & R Research, 2008, 14 (4): 565- 580.
|
22 |
FERRARA A, INCREMONA G P, MAGNI L. A robust MPC/ISM hierarchical multi-loop control scheme for robot manipulators. Proc. of the 52nd IEEE Conference on Decision and Control, 2013: 3560−3565.
|
23 |
ALBIN T, RITTER D, LIBERDA N, et al In-vehicle realization of nonlinear MPC for gasoline two-stage turbocharging airpath control. IEEE Trans. on Control Systems Technology, 2018, 26 (5): 1606- 1618.
doi: 10.1109/TCST.2017.2724020
|
24 |
INCREMONA G P, FERRARA A, MAGNI L MPC for robot manipulators with integral sliding modes generation. IEEE/ASME Trans. on Mechatronics, 2017, 22 (3): 1299- 1307.
doi: 10.1109/TMECH.2017.2674701
|
25 |
GAO J, WU P G, LI T R, et al Optimization-based model reference adaptive control for dynamic positioning of a fully actuated underwater vehicle. Nonlinear Dynamics, 2017, 87 (4): 2611- 2623.
doi: 10.1007/s11071-016-3214-2
|
26 |
RAWLINGS J B, MAYNE D Q, DIEHL M M. Model predictive control: theory, computation, and design. Madison: Nob Hill Publishing, LLC, 2012.
|
27 |
FARAJZADEH-D M G, HOSSEINI SANI S K, AKBARZADEH A. Performance enhancement of model reference adaptive control through normalized Lyapunov design. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 2019. DOI: 10.1177/0959651818822925.
|
28 |
GILBERT E G, KOLMANOVSKY I. Discrete-time reference governors for systems with state and control constraints and disturbance inputs. Proc. of the 34th IEEE Conference on Decision and Control, 1994: 1189−1194.
|
29 |
KOLMANOVSKY I, GILBERT E G Theory and computaion of disturbance invariant sets for discrete-time linear systems. Mathematical Problems in Engineering, 1998, 4 (4): 317- 367.
doi: 10.1155/S1024123X98000866
|
30 |
ZACCARIAN L. DC motors: dynamic model and control techniques. http://homepages.laas.fr/lzaccari/seminars/DCmotors.pdf.
|