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This paper proposes a novel observer-based disturbance estimation method for high degree-of-freedom Euler-Lagrangian systems using an unknown input-output (UIO) sliding mode observer (SMO). Different from the previous SMO methods, this…

Robotics · Computer Science 2023-03-08 Zengjie Zhang , Dirk Wollherr

In this paper, we present a methodology to identify discrete-time state-space switched linear systems (SLSs) from input-output measurements. Continuous-state is not assumed to be measured. The key step is a deadbeat observer based…

Systems and Control · Electrical Eng. & Systems 2021-08-12 Fethi Bencherki , Semiha Türkay , Hüseyin Akçay

An event-based state estimation approach for reducing communication in a networked control system is proposed. Multiple distributed sensor-actuator-agents observe a dynamic process and sporadically exchange their measurements and inputs…

Systems and Control · Computer Science 2017-01-30 Sebastian Trimpe

Motivated by perception-based control problems in autonomous systems, this paper addresses the problem of developing feedback controllers to regulate the inputs and the states of a dynamical system to optimal solutions of an optimization…

Systems and Control · Electrical Eng. & Systems 2023-10-17 Liliaokeawawa Cothren , Gianluca Bianchin , Sarah Dean , Emiliano Dall'Anese

In this paper we propose a stochastic model predictive control (MPC) algorithm for linear discrete-time systems affected by possibly unbounded additive disturbances and subject to probabilistic constraints. Constraints are treated in…

Systems and Control · Computer Science 2019-02-15 Lukas Hewing , Melanie N. Zeilinger

Firstly, a new state feedback model reference adaptive control approach is developed for uncertain systems with gain scheduled reference models in a multi-input multi-output (MIMO) setting. Specifically, adaptive state feedback for output…

Optimization and Control · Mathematics 2014-03-18 Mehrdad Pakmehr , Tansel Yucelen

Model Predictive Control is an extremely effective control method for systems with input and state constraints. Model Predictive Control performance heavily depends on the accuracy of the open-loop prediction. For systems with uncertainty…

Optimization and Control · Mathematics 2022-07-27 Francesco Micheli , John Lygeros

This paper proposes Select-Data-driven Predictive Control (Select-DPC), a new method for controlling nonlinear systems using output-feedback for which data are available but an explicit model is not. At each timestep, Select-DPC employs…

Systems and Control · Electrical Eng. & Systems 2025-05-23 Joshua Näf , Keith Moffat , Jaap Eising , Florian Dörfler

One of the most important branches of nonlinear control theory is the so-called sliding-mode. Its aim is the design of a (nonlinear) feedback law that brings and maintains the state trajectory of a dynamic system on a given sliding surface.…

Systems and Control · Electrical Eng. & Systems 2021-09-14 Mauro Bisiacco , Gianluigi Pillonetto

In this work, sample-based observability of linear discrete-time systems is studied. That is, we consider the case where the system output measurements are not available at every time instance. It is shown that some discrete-time systems…

Systems and Control · Electrical Eng. & Systems 2023-04-26 Isabelle Krauss , Victor G. Lopez , Matthias A. Müller

This paper proposes a functional observer-based sliding mode control technique for position control of a single-link flexible manipulator. The proposed method considers the unmodelled system dynamics as uncertainty and aims to achieve…

Systems and Control · Electrical Eng. & Systems 2023-05-23 Atul Sharma , S. Janardhanan

The current paper presents a Sliding Mode Controller (SMC) for indirect field-oriented Cascaded Doubly Fed Induction Generator (CDFIG) powered through a Matrix Converter (MC). The proposed SMC employs a continuous control strategy to…

Systems and Control · Electrical Eng. & Systems 2022-08-25 A. Maafa , H. Mellah , K. Ghedamsi , D. Aouzellag

In this paper, we propose an adaptive data-driven min-max model predictive control (MPC) scheme for discrete-time linear time-varying (LTV) systems. We assume that prior knowledge of the system dynamics and bounds on the variations are…

Systems and Control · Electrical Eng. & Systems 2026-03-09 Yifan Xie , Julian Berberich , Frank Allgöwer

With the increasing ubiquity of networked control systems, various strategies for sampling constituent subsystems' outputs have emerged. In contrast with periodic sampling, event-triggered control provides a way to efficiently sample a…

Systems and Control · Electrical Eng. & Systems 2023-04-06 Daniel A. Williams , Airlie Chapman , Chris Manzie

We propose an on-line supervisory control scheme for discrete event systems (DESs), where a control specification is described by a fragment of linear temporal logic. On the product automaton of the DES and an acceptor for the…

Systems and Control · Electrical Eng. & Systems 2020-03-27 Ami Sakakibara , Toshimitsu Ushio

The guidance of a torpedo represents a hard task because of the smooth nonlinear aspect of this system and because of the extreme external disturbances. The torpedo guidance reposes on the speed and the position control. In fact, the…

Systems and Control · Computer Science 2013-01-15 Ahmed Rhif , Zohra Kardous , Naceur BenHadj Braiek

Cascading failures in power systems caused by sequential tripping of components are a serious concern as they can lead to complete or partial shutdowns, disrupting vital services and causing damage and inconvenience. In prior work, we…

Systems and Control · Electrical Eng. & Systems 2026-03-12 Wasseem Al-Rousan , Caisheng Wang , Feng Lin

This paper proposes an observer-based event-driven approach to decrease the overuse of communication networks. The suggested approach aims to estimate the required data for sharing between units in line with as much communication reduction…

Systems and Control · Electrical Eng. & Systems 2024-09-27 Shahabeddin Najafi , Yazdan Batmani , Pouya Shafiee , Charalambos Konstantinou

The second-order sub-optimal sliding mode control (SMC), known in the literature for the last two decades, is extended by a control-off mode which allows for saving energy during the finite time convergence. The systems with relative degree…

Optimization and Control · Mathematics 2023-05-16 Michael Ruderman , Alessandro Pisano , Elio Usai

Selective state space models (SSMs), such as Mamba, achieve strong per-token expressivity by making the time discretization step $\Tilde{\Delta}$ a learned function of the input. However, in doing so, $\Tilde{\Delta}$ ceases to represent a…

Machine Learning · Computer Science 2026-05-12 Taylan Soydan , Miguel A. Bessa , Dirk Mohr , Rui Barreira