An algorithm for multi-parametric quadratic programming and explicit MPC solutions
By Petter Tøndel, T. A. Johansen, Alberto Bemporad. Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228), 2001
738 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Control and Systems Engineering
View Paper: https://www.semanticscholar.org/paper/384a8da29562cf13524fa2688e8d0fa7005de91f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Francesco Borrelli
- Manfred Morari
- Alessandro Alessio
- Pascal Grieder
- Stephen P. Boyd
- Brendan O'Donoghue
- Giorgos Stathopoulos
- Mato Baotic
In Control and Systems Engineering
- Manfred Morari
- Francesco Borrelli
- Alberto Bemporad
- Eric C. Kerrigan
- Brendan O'Donoghue
- Stephen P. Boyd
- Pascal Grieder
- Alessandro Alessio
Citations in the corpus
- A Splitting Method for Optimal Control (2013, methodology): “Explicit model predictive control is a technique for solving quadratic optimal control problems with polyhedral constraints [16,17], with all data fixed except the initial state.”
- A survey on explicit model predictive control (2009, methodology): “Conditions for the property to hold are provided in [68].”
- Constrained Optimal Control of Linear and Hybrid Systems (2003, methodology): “In our experience the solvers in [10, 147] are the most efficient.”
- Move blocking strategies in receding horizon control (2004, background): “…problem (3) depends on the current state x , it can be solved either by solving the quadratic program (3) for a given x , or as shown in [2], [10], by solving problem (3) for all x within a polyhedral set of values, i.e., by considering (3) as a multi-parametric Quadratic Program (mp-QP) [2].”
- Technical Communique: Evaluation of piecewise affine control via binary search tree (2003, neutral): “An algorithm to solve the mp-QP is also provided, however, a more efficient algorithm is developed in ( Tondel et al., 2001 ).”
- Predictive Control for Linear and Hybrid Systems (2017, methodology): “In [274] the authors explore the parameter space outside a given region CRi by examining its set of active constraints Ai.”
- Multi-Parametric Toolbox (MPT) (2004, methodology): “Both [1] and [35] give algorithms that are significantly more efficient than the original procedure proposed in [9].”
- Min-max control of constrained uncertain discrete-time linear systems (2003, background): “More details on multiparametric programming can be found in [14], [15] for linear programs, in [16] for nonlinear programs, and in [11], [ 17 ], and [18] for quadratic programs.”
- Current Management in a Hybrid Fuel Cell Power System: A Model-Predictive Control Approach (2006, background): “However analytical calculation of such a function becomes increasingly difficult as larger prediction horizons are used [31].”