REFERENCES
1. Camacho EF, Bordons C. Model predictive control. Springer Science & Business Media; 2013.
2. Mayne DQ, Rawlings JB, Rao CV, Scokaert POM. Constrained model predictive control: Stability and optimality. Automatica, 2000;36:789-814.
3. Allgöwer F, Zheng A. Nonlinear model predictive control, volume 26. Birkhäuser; 2012.
4. Camacho EF, Bordons C. Nonlinear model predictive control: An introductory review. In Assessment and future directions of nonlinear model predictive control. Springer; 2007. pp. 1-16.
5. Gros S, Zanon M, Quirynen R, Bemporad A, Diehl M. From linear to nonlinear MPC: bridging the gap via the real-time iteration. International Journal of Control 2020;93:62-80.
6. Quirynen R, Vukov M, Zanon M, Diehl M. Autogenerating microsecond solvers for nonlinear MPC: a tutorial using ACADO integrators. Optimal Control Applications and Methods 2015;36:685-704.
7. Englert T, Völz A, Mesmer F, Rhein S, Graichen K. A software framework for embedded nonlinear model predictive control using a gradient-based augmented lagrangian approach (GRAMPC). Optimization and Engineering 2019;20:769-809.
8. Ohyama S, Date H. Parallelized nonlinear model predictive control on GPU. In 11th Asian Control Conference, pages 1620–1625. IEEE; 2017.
9. Rathai KMM, Sename O, Alamir M. GPU-based parameterized nmpc scheme for control of half car vehicle with semi-active suspension system. IEEE Control Systems Letters 2019;3:631-6.
10. Hoffmann C, Werner H. A survey of linear parameter-varying control applications validated by experiments or high- fidelity simulations. IEEE Transactions on Control Systems Technology 2014;23:416-33.
11. Morato MM, Normey-Rico JE, Sename O. Model predictive control design for linear parameter varying systems: A survey. Annual Reviews in Control 2020;49:64-80.
12. Boyd S, El Ghaoui L, Feron E, Balakrishnan V. Linear matrix inequalities in system and control theory, volume 15. Siam; 1994.
13. Abbas HS, Toth R, Petreczky M, Meskin N, Mohammadpour J. Embedding of nonlinear systems in a linear parameter-varying representation. IFAC Proceedings Volumes 2014;47:6907-13.
14. Kunz K, Huck SM, Summers TH. Fast model predictive control of miniature helicopters. In 2013 European Control Conference (ECC), pages 1377–1382. IEEE; 2013.
15. Cisneros Pablo SG, Werner Herbert. Wide range stabilization of a pendubot using quasi-LPV predictive control. IFAC-PapersOnLine 2019;52:164-9.
16. Alcalá E, Puig V, Quevedo J. LPV-MPC control for autonomous vehicles. IFAC-PapersOnLine 2019;52:106-13.
17. Mate S, Kodamana H, Bhartiya S, Nataraj PSV. A stabilizing sub-optimal model predictive control for quasi-linear parameter varying systems. IEEE Control Systems Letters 2019; doi: 10.1109/LCSYS.2019.2937921.
18. Morato MM, Normey-Rico JE, Sename O. Novel qLPV MPC design with least-squares scheduling prediction. IFAC-PapersOnLine 2019;52:158-63.
19. Morato MM, Normey-Rico JE, Sename O. Sub-optimal recursively feasible linear parameter-varying predictive algorithm for semi-active suspension control. IET Control Theory & Applications 2020;14:2764-75.
20. Cisneros PSG, Voss S, Werner H. Efficient nonlinear model predictive control via quasi-LPV representation. In IEEE Conference on Decision and Control IEEE; 2016. pp. 3216-21.
21. Cisneros PG, Werner H. Fast nonlinear MPC for reference tracking subject to nonlinear constraints via quasi-LPV representations. IFAC-PapersOnLine 2017;50:11601-6.
22. Cisneros PS, Werner H. Nonlinear model predictive control for models in quasi-linear parameter varying form. International Journal of Robust and Nonlinear Control 2020; doi: 10.1002/rnc.4973.
23. Jungers M, Caun RP, Oliveira RCLF, Peres PLD. Model predictive control for linear parameter varying systems using path-dependent lyapunov functions. IFAC Proceedings Volumes 2009;42:97-102.
24. Limon D, Ferramosca A, Alvarado I, Alamo T, Camacho EF. MPC for tracking of constrained nonlinear systems. In Nonlinear model predictive control Springer; 2009. pp. 315-23.
25. Limon D, Ferramosca A, Alvarado I, Alamo T. Nonlinear MPC for tracking piece-wise constant reference signals. IEEE Transactions on Automatic Control 2018;63:3735-50.
27. Köhler J, Müller MA, Allgöwer F. A nonlinear tracking model predictive control scheme for dynamic target signals. Automatica 2020;118:109030.
28. Qi L. Superlinearly convergent approximate newton methods for lc1 optimization problems. Mathematical programming 1994;64:277-94.
29. Wei Z, Liu L, Yao S. The superlinear convergence of a new quasi-newton-sqp method for constrained optimization. Applied mathematics and computation 2008;196:791-801.
30. Izmailov AF, Solodov MV. On attraction of linearly constrained lagrangian methods and of stabilized and quasi-newton sqp methods to critical multipliers. Mathematical programming 2011;126:231-57.
31. Boggs PT, Tolle JW, Kearsley AJ. On the convergence of a trust region SQP algorithm for nonlinearly constrained optimization problems. In System Modelling and Optimization Springer; 1996. pp. 3-12.
32. Boggs PT, Tolle JW. Sequential quadratic programming for large-scale nonlinear optimization. Journal of computational and applied mathematics 2000;124:123-137.
33. Diehl M, Bock HG, Schlöder JP. A real-time iteration scheme for nonlinear optimization in optimal feedback control. SIAM Journal on control and optimization 2005;43:1714-36.
34. Houska B, Ferreau HJ, Diehl M. An auto-generated real-time iteration algorithm for nonlinear MPC in the microsecond range. Automatica 2011;47:2279-85.
35. Michalska H, Mayne DQ. Robust receding horizon control of constrained nonlinear systems. IEEE transactions on automatic control 1993;38:1623-33.
36. Duan GR, Yu HH. LMIs in control systems: analysis, design and applications. CRC press; 2013.
37. Morato MM, Normey-Rico J, Sename O. Short-sighted robust lpv model predictive control: Application to semi-active suspension systems. In European Control Conference 2021 (ECC21), pages 1–7 2021.
38. Wu F. A generalized LPV system analysis and control synthesis framework. International Journal of Control 2001;74:745-59.
39. Chen H, Kremling A, Allgöwer F. Nonlinear predictive control of a benchmark CSTR. In Proceedings of 3rd European control conference, pages 3247–3252 1995.