MPT

The Multi-Parametric Toolbox (MPT) is a free Matlab toolbox for design, analysis and deployment of optimal controllers for constrained linear, nonlinear and hybrid systems. Efficiency of the code is guaranteed by the extensive library of algorithms from the field of computational geometry and multi-parametric optimization. The toolbox offers a broad spectrum of algorithms compiled in a user friendly and accessible format: starting from different performance objectives (linear, quadratic, minimum time) to the handling of systems with persistent additive and polytopic uncertainties. Users can add custom constraints, such as polytopic, contraction, or collision avoidance constraints, or create custom objective functions. Resulting optimal control laws can either be embedded into your applications in a form of a C code, or deployed to target platforms using Real Time Workshop.


References in zbMATH (referenced in 199 articles , 1 standard article )

Showing results 1 to 20 of 199.
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  1. Pavlov, Andrei; Shames, Iman; Manzie, Chris: Minimax strategy in approximate model predictive control (2020)
  2. Brunner, Florian David; Heemels, W. P. M. H.; Allgöwer, Frank: Event-triggered and self-triggered control for linear systems based on reachable sets (2019)
  3. Ciripoi, Daniel; Löhne, Andreas; Weißing, Benjamin: Calculus of convex polyhedra and polyhedral convex functions by utilizing a multiple objective linear programming solver (2019)
  4. Ferranti, Laura; Pu, Ye; Jones, Colin N.; Keviczky, Tamás: SVR-AMA: an asynchronous alternating minimization algorithm with variance reduction for model predictive control applications (2019)
  5. Fonseca, Daniel Guerra Vale da; Dantas, André Felipe O. de A.; Dórea, Carlos Eduardo Trabuco; Maitelli, André Laurindo; Shah, Umer H.: Explicit GPC control applied to an approximated linearized crane system (2019)
  6. Frick, Damian; Georghiou, Angelos; Jerez, Juan L.; Domahidi, Alexander; Morari, Manfred: Low-complexity method for hybrid MPC with local guarantees (2019)
  7. Kvasnica, Michal; Bakaráč, Peter; Klaučo, Martin: Complexity reduction in explicit MPC: a reachability approach (2019)
  8. Maddalena, Emilio Tanowe; Galvão, Roberto Kawakami Harrop; Afonso, Rubens Junqueira Magalhães: Robust region elimination for piecewise affine control laws (2019)
  9. Oravec, Juraj; Holaza, Juraj; Horváthová, Michaela; Nguyen, Ngoc A.; Kvasnica, Michal; Bakošová, Monika: Convex-lifting-based robust control design using the tunable robust invariant sets (2019)
  10. Robin Verschueren, Gianluca Frison, Dimitris Kouzoupis, Niels van Duijkeren, Andrea Zanelli, Branimir Novoselnik, Jonathan Frey, Thivaharan Albin, Rien Quirynen, Moritz Diehl: acados: a modular open-source framework for fast embedded optimal control (2019) arXiv
  11. Vinod, Abraham P.; Gleason, Joseph D.; Oishi, Meeko M. K.: SReachTools: a MATLAB stochastic reachability toolbox (2019)
  12. Vinod, Abraham P.; Gleason, Joseph D.; Oishi, Meeko M. K.: Demo abstract: SReachTools: a MATLAB stochastic reachability toolbox. (2019)
  13. Yadbantung, Rungroj; Bumroongsri, Pornchai: Tube-based robust output feedback MPC for constrained LTV systems with applications in chemical processes (2019)
  14. Akbari, Amir; Barton, Paul I.: An improved multi-parametric programming algorithm for flux balance analysis of metabolic networks (2018)
  15. Dantas, Amanda Danielle O. da S.; Dantas, André Felipe O. de A.; Campos, João Tiago L. S.; de Almeida Neto, Domingos L.; Dórea, Carlos Eduardo T.: PID control for electric vehicles subject to control and speed signal constraints (2018)
  16. Falconì, Guillermo P.; Angelov, Jorg; Holzapfel, Florian: Adaptive fault-tolerant position control of a hexacopter subject to an unknown motor failure (2018)
  17. Ghaffarinasab, Nader; Van Woensel, Tom; Minner, Stefan: A continuous approximation approach to the planar hub location-routing problem: modeling and solution algorithms (2018)
  18. Ghasemi, Mohammad S.; Afzalian, Ali A.: Invariant convex approximations of the minimal robust invariant set for linear difference inclusions (2018)
  19. Hill, Robin; Luo, Yousong; Schwerdtfeger, Uwe: Exact recursive updating of state uncertainty sets for linear SISO systems (2018)
  20. Lv, Jianfeng; Gao, Yan: The computation of the viability kernel for switched systems (2018)

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Further publications can be found at: http://control.ee.ethz.ch/index.cgi?page=publications