Structured computation of optimal controls for constrained cascade systems

References

• Bevilacqua, R. , Codenotti, B. , & Romani, F. (1988). Parallel solution of block tridiagonal linear systems. Linear Algebra and its Applications, 104 , 39–57.
   Web of Science ®Google Scholar
• Diehl, M. , Ferreau, H. J. , & Haverbeke, N. (2009). Efficient numerical methods for nonlinear MPC and moving horizon estimation. In Nonlinear Model Predictive Control (pp. 391–417). Berlin: Springer.
   Google Scholar
• Disney, S. M. , & Towill, D. R. (2003). The effect of vendor managed inventory (VMI) dynamics on the Bullwhip Effect in supply chains. International Journal of Production Economics, 85 (2), 199–215.
   Web of Science ®Google Scholar
• Domahidi, A. , Zgraggen, A. U. , Zeilinger, M. N. , Morari, M. , & Jones, C. N. (2012). Efficient interior point methods for multistage problems arising in receding horizon control. In Proceedings of the 51st IEEE Conference on Decision and Control (pp. 668–674). New York: IEEE.
   Google Scholar
• Labadie, J. W. (2004). Optimal operation of multireservoir systems: State-of-the-art review. Journal of Water Resources Planning and Management, 130 (2), 93–111.
   Web of Science ®Google Scholar
• Li, Y. , Cantoni, M. , & Weyer, E. (2005). On water-level error propagation in controlled irrigation channels. In Proceedings of the 44th IEEE Conference on Decision and Control (pp. 2101–2106). New York: IEEE.
   Google Scholar
• Maciejowski, J. M. (2002). Predictive control: With constraints . Pearson: Prentice-Hall.
   Google Scholar
• Meurant, G. (1992). A review on the inverse of symmetric tridiagonal and block tridiagonal matrices. SIAM Journal on Matrix Analysis and Applications, 13 (3), 707–728.
   Web of Science ®Google Scholar
• Neshastehriz, A. R. , Cantoni, M. , & Shames, I. (2014). Water-level reference planning for automated irrigation channels via robust MPC. In Proceedings of the 13th European Control Conference (pp. 1331–1336).New York: IEEE.
   Google Scholar
• Nielsen, I. , & Axehill, D. (2014). An O(log N) parallel algorithm for Newton step computation in model predictive control. IFAC Proceedings Volumes, 47 (3), 10505–10511.
   Google Scholar
• Puig, V. , Cembrano, G. , Romera, J. , Quevedo, J. , Aznar, B. , Ramón, G. , & Cabot, J. (2009). Predictive optimal control of sewer networks using CORAL tool: Application to Riera Blanca catchment in Barcelona. Water Science and Technology, 60 (4), 869–878.
   PubMed Web of Science ®Google Scholar
• Rao, C. V. , Wright, S. J. , & Rawlings, J. B. (1998). Application of interior-point methods to model predictive control. Journal of Optimization Theory and Applications, 99 (3), 723–757.
   Web of Science ®Google Scholar
• Rawlings, J. B. , & Mayne, D. Q. (2009). Model predictive control: Theory and design . Madison, Wisconsin: Nob Hill Pub.
   Google Scholar
• Şahin, A. , & Morari, M. (2010). Decentralized model predictive control for a cascade of river power plants. In Intelligent Infrastructures (pp. 463–485). Berlin: Springer.
   Google Scholar
• Seiler, P. , Pant, A. , & Hedrick, K. (2004). Disturbance propagation in vehicle strings. IEEE Transactions on Automatic Control, 49 (10), 1835–1841.
   Web of Science ®Google Scholar
• Soltanian, L. , & Cantoni, M. (2015). Decentralized string-stability analysis for heterogeneous cascades subject to load-matching requirements. Multidimensional Systems and Signal Processing, 26 (4), 985–999.
   Web of Science ®Google Scholar
• Wang, Y. , & Boyd, S. (2010). Fast model predictive control using online optimization. IEEE Transactions on Control Systems Technology, 18 (2), 267–278.
   Web of Science ®Google Scholar
• Wills, A. G. , & Heath, W. P. (2003). Interior-point methods for linear model predictive control ( Report EE03016). University of Newcastle, NSW, 2308.
   Google Scholar
• Wright, S. J. (1993). Interior point methods for optimal control of discrete time systems. Journal of Optimization Theory and Applications, 77 (1), 161–187.
   Web of Science ®Google Scholar
• Wright, S. J. (1997). Primal-dual interior-point methods . Philadelphia: SIAM.
   Google Scholar