Here are some useful references for further reading.
[Boyd2011] | S. Boyd, N. Parikh, E. Chu, B. Peleato, and J. Eckstein, “Distributed optimization
and statistical learning via the alternating direction method of multipliers,” Found.
Trends Mach. Learn., vol. 3, no. 1, p. 1–122, Jan. 2011. |
[Stellato2020] | B. Stellato, G. Banjac, P. Goulart, A. Bemporad, and S. Boyd, “OSQP: an operator splitting
solver for quadratic programs,”Mathematical Programming Computation, vol. 12, no. 4,
pp. 637–672, 2020. |
[Stathopoulos2016] | G. Stathopoulos, H. Shukla, A. Szucs, Y. Pu, and C. N. Jones, Operator SplittingMethods
in Control. Now Foundations and Trends, 2016. |
[Goldfarb1983] | Goldfarb, Donald and Ashok U. Idnani. “A numerically stable dual method for solving strictly
convex quadratic programs.” Mathematical Programming 27 (1983): 1-33. |
[Nocedal2006] |
- Nocedal and S. J. Wright, Numerical Optimization, 2nd ed. New York, NY, USA: Springer, 2006.
|
[Ruiz2001] | D. Ruiz, “A scaling algorithmto equilibrate both rows and columns norms in matrices,”
Rutherford Appleton Lab, Tech. Rep., 2001. |
[Biegler1984] | L. T. Biegler, “Solution of dynamic optimization problems by successive quadratic
programming and orthogonal collocation,” Computers & Chemical Engineering, vol. 8,
no. 3, pp. 243–247, 1984. |
[Fahroo2003] | F. Fahroo,D. B.Doman, and A.D.Ngo, “Footprint generation for reusable launch vehicles
using a direct pseudospectral method,” ser. American Control Conference, vol. 3, 2003,
pp. 2163–2168. |
[Benson2005] | D. Benson, “A gauss pseudospectral transcription for optimal control,” Ph.D. dissertation,
Massachusetts Institute of Technology, 2005. |
[Huntington2007] | G. Huntington, “Advancement and analysis of gauss pseudospectral transcription for
optimal control problems,” Ph.D. dissertation,Massachusetts Institute of Technology, 2007. |
[Trefethen2000] |
- Trefethen "Spectral methods in MATLAB", Society for industrial and applied mathematics, 2000.
|
[Listov2020] | P. Listov, C. Jones "PolyMPC: An efficient and extensible tool for real‐time nonlinear
model predictive tracking and path following for fast mechatronic systems", Optimal Control Applications and Methods, 2020. |