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This paper describes an inverse shape design method for thermoelastic bodies. With a known equilibrium shape as input, the focus of this paper is the determination of the corresponding initial shape of a body undergoing thermal expansion or…

Numerical Analysis · Mathematics 2019-08-26 Florian Zwicke , Stefanie Elgeti

Shared Control methods often use impedance control to track target poses in a robotic manipulator. The guidance behavior of such controllers is shaped by the used stiffness gains, which can be varying over time to achieve an adaptive…

Standard model predictive control strategies imply the online computation of control inputs at each sampling instance, which traditionally limits this type of control scheme to systems with slow dynamics. This paper focuses on distributed…

Optimization and Control · Mathematics 2013-02-26 Ion Necoara , Dragos N. Clipici , Sorin Olaru

A distributed parameter model of pipeline transmission line behaviour is presented, based on a Galerkin method incorporating frequency-dependent friction. This is readily interfaced to an existing model of the pumping dynamics of a plunger…

Fluid Dynamics · Physics 2014-10-06 Jian-Jun Shu , Clifford R. Burrows , Kevin A. Edge

In contemporary magnetic confinement devices, the density distribution is sensed with interferometers and actuated with feedback controlled gas injection and open-loop pellet injection. This is at variance with the density control for ITER…

Plasma Physics · Physics 2021-10-29 T. O. S. J. Bosman , M. van Berkel , M. R. de Baar

Model Predictive Control (MPC) offers a versatile framework for constraint handling and multi-objective optimisation, yet practical application faces challenges regarding initial and recursive feasibility, robustness against model…

Optimization and Control · Mathematics 2026-02-27 Dario Dennstädt

In this paper, we tackle the problem of pushing piles of small objects into a desired target set using visual feedback. Unlike conventional single-object manipulation pipelines, which estimate the state of the system parametrized by pose,…

Robotics · Computer Science 2020-06-17 H. J. Terry Suh , Russ Tedrake

The ability to robustly and efficiently control the dynamics of nonlinear systems lies at the heart of many current technological challenges, ranging from drug delivery systems to ensuring flight safety. Most such scenarios are too complex…

Fluid Dynamics · Physics 2021-02-16 Radu Cimpeanu , Susana N. Gomes , Demetrios T. Papageorgiou

Through the method of Learning Feedback Linearization, we seek to learn a linearizing controller to simplify the process of controlling a car to race autonomously. A soft actor-critic approach is used to learn a decoupling matrix and drift…

Optimization and Control · Mathematics 2021-10-22 Michael Estrada , Sida Li , Xiangyu Cai

In course of this work, we examine the process of plastic profile extrusion, where a polymer melt is shaped inside the so-called extrusion die and fixed in its shape by solidification in the downstream calibration unit. More precise, we…

Numerical Analysis · Mathematics 2022-09-08 Daniel Hilger , Norbert Hosters

With the advantages of high modeling accuracy and large bandwidth, recurrent neural network (RNN) based inversion model control has been proposed for output tracking. However, some issues still need to be addressed when using the RNN-based…

Systems and Control · Electrical Eng. & Systems 2020-01-03 Shengwen Xie , Juan Ren

We present a robust model predictive control (MPC) framework for linear systems facing bounded parametric uncertainty and bounded disturbances. Our approach deviates from standard MPC formulations by integrating multi-step predictors, which…

Optimization and Control · Mathematics 2023-11-21 Danilo Saccani , Giancarlo Ferrari-Trecate , Melanie N. Zeilinger , Johannes Köhler

In model predictive control (MPC), preview information can greatly improve tracking. Including preview information does, however, increase the parameter dimension linearly with the preview horizon, which increases online cost and, more…

Optimization and Control · Mathematics 2026-04-21 Daniel Arnström

This paper addresses the problem of obtaining low-order models of fluid flows for the purpose of designing robust feedback controllers. This is challenging since whilst many flows are governed by a set of nonlinear, partial…

Growing demands in the semiconductor industry necessitate increasingly stringent requirements on throughput and positioning accuracy of lithographic equipment. Meeting these demands involves employing highly aggressive motion profiles,…

Systems and Control · Electrical Eng. & Systems 2024-08-08 Yorick Broens , Hans Butler , Ramidin Kamidi , Koen Verkerk , Siep Weiland

We propose a novel feedback controller for a class of uncertain higher-order nonlinear systems, subject to delays in both state measurement and control input signals. Building on the prescribed performance control framework, a…

Optimization and Control · Mathematics 2025-09-11 Thomas Berger , Lampros N. Bikas , Jan Hachmeister , George A. Rovithakis

This tutorial shows an overview of Model Predictive Control with a linear discrete-time system and constrained states and inputs. The focus is on the implementation of the method under consideration of stability and recursive feasibility.…

Systems and Control · Electrical Eng. & Systems 2021-09-27 Michael Fink

This technical report presents a method for designing a constrained output-feedback model predictive controller (MPC) that behaves in the same way as an existing baseline stabilising linear time invariant output-feedback controller when…

Optimization and Control · Mathematics 2011-09-14 Edward N. Hartley , Jan M. Maciejowski

Falling liquid films become unstable due to inertial effects when the fluid layer is sufficiently thick or the slope sufficiently steep. This free surface flow of a single fluid layer has industrial applications including coating and heat…

This paper presents a low-complexity, model-free, output-feedback controller for a class of unknown time-varying nonlinear systems with unknown input constraints. The controller achieves the preset control accuracy when the actuator is not…

Systems and Control · Electrical Eng. & Systems 2026-05-21 Dianrui Mu , Changchun Hua , Yafeng Li , Jiannan Chen , Rao Wei