A distributed accelerated gradient algorithm for distributed model predictive control of a hydro power valley

Research output: Contribution to journalArticle


A distributed model predictive control (DMPC) approach based on distributed optimization is applied to the power reference tracking problem of a hydro power valley (HPV) system. The applied optimization algorithm is based on accelerated gradient methods and achieves a convergence rate of O(1/k^2), where k is the iteration number. Major challenges in the control of the HPV include a nonlinear and large-scale model, non-smoothness in the power-production functions, and a globally
coupled cost function that prevents distributed schemes to be applied directly. We propose a linearization and approximation approach that accommodates the proposed the DMPC framework and provides very similar performance compared to a centralized solution in simulations. The provided numerical studies also suggest that for the sparsely interconnected system at hand, the distributed algorithm we propose is faster than a centralized state-of-the-art solver such as CPLEX.


Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Control Engineering


  • Distributed optimization, Hydro power control, Accelerated gradient algorithm, Distributed model predictive control, Model predictive control
Original languageEnglish
Pages (from-to)1594-1605
JournalControl Engineering Practice
Issue number11
Publication statusPublished - 2013
Publication categoryResearch

Related projects

Anders Holmqvist, Niklas Andersson, Anton Cervin, Anders Mannesson, Ather Gattami, Andrey Ghulchak, Alessandro Vittorio Papadopoulos, Anders Rantzer, Anders Robertsson, Aivar Sootla, ALFRED THEORIN, Bo Bernhardsson, Björn Olofsson, Björn Wittenmark, Christian Grussler, Charlotta Johnsson, Daria Madjidian, Erik Johannesson, Fredrik Magnusson, Fredrik Ståhl, Giacomo Como, Georgios Chasparis, Gabriel Turesson, Isolde Dressler, Johan Åkesson, Jang Ho Cho, Karl-Erik Årzén, Karl Johan Åström, Kin Cheong Sou, Karl Mårtensson, Karl Berntorp, Kristian Soltesz, Laurent Lessard, Martin Hast, Meike Rönn, Martin Ansbjerg Kjær, Martina Maggio, Maxim Kristalny, Olof Garpinger, Pål Johan From, Per-Ola Larsson, Pontus Giselsson, Rolf Johansson, Tore Hägglund, Vladimeros Vladimerou, Vanessa Romero Segovia, Andreas Aurelius, Gustav Cedersjö, Kaan Bür, Manfred Dellkrantz, Manxing Du, Payam Amani, Robin Larsson, William Tärneberg, Zheng Li, Lianhao Yin, Fredrik Tufvesson, Stefan Höst, Bernt Nilsson, Stig Stenström, Jens A Andersson, Stefan Diehl, Jonas Dürango, Mahdi Ghazaei Ardakani, Per-Ola Forsberg, Fredrik Bengtsson, Henrik Jörntell, Carmen Arévalo, Claus Führer, Christian Andersson, Fatemeh Mohammadi, Per Ödling, Mikael Andersson, Maria Kihl & Per Tunestål


Project: Research

View all (1)