On multi-parametric programming and its applications in process systems engineering
In multi-parametric programming, an optimization problem is solved for a range and as a
function of multiple parameters. In this review, we discuss the main developments of multi …
function of multiple parameters. In this review, we discuss the main developments of multi …
A survey on explicit model predictive control
A Alessio, A Bemporad - Nonlinear Model Predictive Control: Towards …, 2009 - Springer
Explicit model predictive control (MPC) addresses the problem of removing one of the main
drawbacks of MPC, namely the need to solve a mathematical program on line to compute …
drawbacks of MPC, namely the need to solve a mathematical program on line to compute …
Model predictive control allocation for stability improvement of four‐wheel drive electric vehicles in critical driving condition
To improve the vehicle stability of an electric vehicle (EV) with four in‐wheel motors, the
authors investigate the use of a non‐linear control allocation scheme based on model …
authors investigate the use of a non‐linear control allocation scheme based on model …
Simultaneous nonlinear model predictive control and state estimation
An output-feedback approach to model predictive control that combines state estimation and
control into a single min–max optimization is introduced for discrete-time nonlinear systems …
control into a single min–max optimization is introduced for discrete-time nonlinear systems …
Distributed tree-based model predictive control on a drainage water system
Open water systems are one of the most externally influenced systems due to their size and
continuous exposure to uncertain meteorological forces. The control of systems under …
continuous exposure to uncertain meteorological forces. The control of systems under …
Implementation of MPC in embedded systems using first order methods
P Krupa - arxiv preprint arxiv:2109.02140, 2021 - arxiv.org
This Ph. D. dissertation contains results in two different but related fields: the implementation
of model predictive control (MPC) in embedded systems using first order methods, and …
of model predictive control (MPC) in embedded systems using first order methods, and …
Computation, approximation and stability of explicit feedback min–max nonlinear model predictive control
A Grancharova, TA Johansen - Automatica, 2009 - Elsevier
This paper presents an approximate multi-parametric Nonlinear Programming (mp-NLP)
approach to explicit solution of feedback min–max NMPC problems for constrained …
approach to explicit solution of feedback min–max NMPC problems for constrained …
Model predictive control of nonlinear discrete time systems with guaranteed stability
This paper presents the design of a new robust model predictive control algorithm for
nonlinear systems represented by a linear model with unstructured uncertainty. The linear …
nonlinear systems represented by a linear model with unstructured uncertainty. The linear …
A flatness-based iterative method for reference trajectory generation in constrained NMPC
This paper proposes a novel methodology that combines the differential flatness formalism
for trajectory generation of nonlinear systems, and the use of a model predictive control …
for trajectory generation of nonlinear systems, and the use of a model predictive control …
Distributed predictive consensus control of uncertain linear multi-agent systems with heterogeneous dynamics
This paper investigates the consensus of distributed model predictive control for n-
dimensional linear multi-agent systems with uncertain and heterogeneous dynamics, with …
dimensional linear multi-agent systems with uncertain and heterogeneous dynamics, with …