Theoretical and algorithmic advances in multi-parametric programming and control
This paper presents an overview of recent theoretical and algorithmic advances, and
applications in the areas of multi-parametric programming and explicit/multi-parametric …
applications in the areas of multi-parametric programming and explicit/multi-parametric …
Control of a laboratory 3-DOF helicopter: Explicit model predictive approach
J Zhang, X Cheng, J Zhu - International Journal of Control, Automation and …, 2016 - Springer
A helicopter flight control system is a typical multi-input, multi-output system with strong
channel-coupling and nonlinear characteristics. This paper presents an explicit model …
channel-coupling and nonlinear characteristics. This paper presents an explicit model …
Multi-parametric programming
A Grancharova, TA Johansen, A Grancharova… - Explicit nonlinear model …, 2012 - Springer
This chapter presents an overview of the approaches to solve multi-parametric programming
problems. It is organized as follows. In Section 1.1, a general multi-parametric nonlinear …
problems. It is organized as follows. In Section 1.1, a general multi-parametric nonlinear …
Automatic nonlinear MPC approximation with closed-loop guarantees
In this paper, we address the problem of automatically approximating nonlinear model
predictive control (MPC) schemes with closed-loop guarantees. First, we discuss how this …
predictive control (MPC) schemes with closed-loop guarantees. First, we discuss how this …
Min-Max MPC based on a computationally efficient upper bound of the worst case cost
Min-Max MPC (MMMPC) controllers [PJ Campo, M. Morari, Robust model predictive control,
in: Proc. American Control Conference, June 10–12, 1987, pp. 1021–1026] suffer from a …
in: Proc. American Control Conference, June 10–12, 1987, pp. 1021–1026] suffer from a …
Explicit machine learning-based model predictive control of nonlinear processes via multi-parametric programming
Abstract Machine learning-based model predictive control (ML-MPC) has been developed to
control nonlinear processes with unknown first-principles models. While ML models can …
control nonlinear processes with unknown first-principles models. While ML models can …
Novel programmable logic controller implementation of a predictive controller based on Laguerre functions and multiparametric solutions
G Valencia-Palomo, JA Rossiter - IET control theory & applications, 2012 - IET
This study presents a novel programmable logic controller (PLC) implementation of a
constrained predictive control (MPC) algorithm based on Laguerre functions and multi …
constrained predictive control (MPC) algorithm based on Laguerre functions and multi …
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 …
Globally robust explicit model predictive control of constrained systems exploiting SVM‐based approximation
This paper presents a systematic method to address the reduction of online computational
complexity and infeasibility problem of explicit model predictive control for constrained …
complexity and infeasibility problem of explicit model predictive control for constrained …
[PDF][PDF] Real-time model predictive control
MN Zeilinger - 2011 - research-collection.ethz.ch
The main theme of this thesis is the development of real-time and soft constrained Model
Predictive Control (MPC) methods for linear systems, providing the essential properties of …
Predictive Control (MPC) methods for linear systems, providing the essential properties of …