Embedded optimization methods for industrial automatic control
Starting in the late 1970s, optimization-based control has built up an impressive track record
of successful industrial applications, in particular in the petrochemical and process …
of successful industrial applications, in particular in the petrochemical and process …
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 neural network architecture to learn explicit MPC controllers from data
We present a methodology to learn explicit Model Predictive Control (eMPC) laws from
sample data points with tunable complexity. The learning process is cast in a special Neural …
sample data points with tunable complexity. The learning process is cast in a special Neural …
Performance evaluation of the fast model predictive control scheme on a CO2 capture plant through absorption/stripping system
Abstract The Classical Model Predictive Control (CMPC) has the drawback of slow response
in complex dynamic systems. In this work, the Fast Model Predictive Control (FMPC), which …
in complex dynamic systems. In this work, the Fast Model Predictive Control (FMPC), which …
[PDF][PDF] Time-optimal nonlinear model predictive control
C Rösmann - 2019 - eldorado.tu-dortmund.de
This thesis was written during my work at the Institute of Control Theory and Systems
Engineering of the Faculty of Electrical Engineering and Information Technology at the …
Engineering of the Faculty of Electrical Engineering and Information Technology at the …
Online constraint removal: Accelerating MPC with a Lyapunov function
We show how to use a Lyapunov function to accelerate MPC for linear discrete-time systems
with linear constraints and quadratic cost. Our method predicts, in the current time step …
with linear constraints and quadratic cost. Our method predicts, in the current time step …
Parallel implementations of the fast gradient method for high-speed MPC
The potential of the fast gradient method for solving linear quadratic model predictive control
(MPC) problems in the sub-millisecond range was only recently recognised by Richter et al …
(MPC) problems in the sub-millisecond range was only recently recognised by Richter et al …
High-speed and low-cost implementation of explicit model predictive controllers
This paper presents a new form of piecewise-affine (PWA) solution, referred to as PWA
hierarchical (PWAH), to approximate the explicit model predictive control (MPC) law …
hierarchical (PWAH), to approximate the explicit model predictive control (MPC) law …
The integration of explicit MPC and ReLU based neural networks
Using neural networks to capture complex dynamics of highly nonlinear systems is a
promising feature for advanced control applications. Recently it has been shown that ReLU …
promising feature for advanced control applications. Recently it has been shown that ReLU …
Fast FPGA prototyping toolbox for embedded optimization
A Suardi, EC Kerrigan… - 2015 European Control …, 2015 - ieeexplore.ieee.org
Traditionally compute-intensive optimisation algorithms have been implemented on CPU
based machines, primarily in order to reduce development time, but sacrificing computing …
based machines, primarily in order to reduce development time, but sacrificing computing …