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In several model-based system maintenance problems, parameters are used to represent unknown characteristics of a component, equipment degradation, etc. This allows for modelling constant, slow-varying terms. The identifiability of these…

Optimization and Control · Mathematics 2020-03-24 Krishnan Srinivasarengan , José Ragot , Christophe Aubrun , Didier Maquin

Multirotor aerial robots are becoming widely used for the inspection of powerlines. To enable continuous, robust inspection without human intervention, the robots must be able to perch on the powerlines to recharge their batteries. Highly…

Path tracking (PT) controllers capable of replicating race driving techniques, such as drifting beyond the limits of handling, have the potential of enhancing active safety in critical conditions. This paper presents a nonlinear model…

Systems and Control · Electrical Eng. & Systems 2024-10-10 Gaetano Tavolo , Pietro Stano , Davide Tavernini , Umberto Montanaro , Manuela Tufo , Giovanni Fiengo , Pietro Perlo , Aldo Sorniotti

We present initial results regarding the existence, stability and interaction of linear and nonlinear vibrational modes in a system of two coupled, one dimensional lattices with unequal numbers of masses. The effects on these nonlinear…

Biological Physics · Physics 2007-05-23 Kyle Forinash

We present a data-driven nonlinear predictive control approach for the class of discrete-time multi-input multi-output feedback linearizable nonlinear systems. The scheme uses a non-parametric predictive model based only on input and noisy…

Systems and Control · Electrical Eng. & Systems 2023-03-28 Mohammad Alsalti , Victor G. Lopez , Julian Berberich , Frank Allgöwer , Matthias A. Müller

Electric Vertical Takeoff and Landing (eVTOL) vehicles will open new opportunities in aviation. This paper describes the design and wind tunnel analysis of an eVTOL uncrewed aircraft system (UAS) prototype with a traditional aircraft wing,…

Robotics · Computer Science 2023-01-31 Akshay Mathur , Ella Atkins

Recent works have demonstrated how Linear Parameter Varying Model Predictive Control (LPV MPC) algorithms are able to control nonlinear systems with precision and reduced computational load. Specifically, these schemes achieve comparable…

Systems and Control · Electrical Eng. & Systems 2023-05-01 Marcelo Menezes Morato , Amir Naspolini , Julio Elias Normey-Rico

A method for nonlinear topology identification is proposed, based on the assumption that a collection of time series are generated in two steps: i) a vector autoregressive process in a latent space, and ii) a nonlinear, component-wise,…

Signal Processing · Electrical Eng. & Systems 2021-07-02 Luis Miguel Lopez-Ramos , Kevin Roy , Baltasar Beferull-Lozano

A nonlinear model relating the imposed motion of a circular cylinder, submerged in a fluid flow, to the transverse force coefficient is presented. The nonlinear fluid system, featuring vortex shedding patterns, limit cycle oscillations and…

Fluid Dynamics · Physics 2020-06-11 Jan Decuyper , Tim De Troyer , Koen Tiels , Johan Schoukens , Mark C. Runacres

In this study, we use a wavelet neural network with a feedforward component and a model predictive controller for online nonlinear system identification over a communication network. The wavelet neural network (WNN) performs the online…

Signal Processing · Electrical Eng. & Systems 2018-05-15 H. Khodabandehlou , M. Sami Fadali

The increase in system complexity paired with a growing availability of operational data has motivated a change in the traditional control design paradigm. Instead of modeling the system by first principles and then proceeding with a…

Optimization and Control · Mathematics 2020-10-06 Juan G. Rueda-Escobedo , Johannes Schiffer

Modeling dynamical systems is important in many disciplines, e.g., control, robotics, or neurotechnology. Commonly the state of these systems is not directly observed, but only available through noisy and potentially high-dimensional…

Machine Learning · Statistics 2014-10-29 Niklas Wahlström , Thomas B. Schön , Marc Peter Deisenroth

This paper addresses the offset-free tracking problem for nonlinear systems described by a class of recurrent neural networks (RNNs). To compensate for constant disturbances and guarantee offset-free tracking in the presence of model-plant…

Systems and Control · Electrical Eng. & Systems 2025-11-21 Daniele Ravasio , Bestem Abdulaziz , Marcello Farina , Andrea Ballarino

Time-domain simulations are crucial for ensuring power system stability and avoiding critical scenarios that could lead to blackouts. The next-generation power systems require a significant increase in the computational cost and complexity…

Systems and Control · Electrical Eng. & Systems 2025-06-26 Ignasi Ventura Nadal , Jochen Stiasny , Spyros Chatzivasileiadis

This is a demonstration of the PNLSS Toolbox 1.0. The toolbox is designed to identify polynomial nonlinear state-space models from data. Nonlinear state-space models can describe a wide range of nonlinear systems. An illustration is…

Systems and Control · Electrical Eng. & Systems 2021-05-19 Jan Decuyper , Koen Tiels , Johan Schoukens

Estimation of cardiovascular model parameters from electronic health records (EHR) poses a significant challenge primarily due to lack of identifiability. Structural non-identifiability arises when a manifold in the space of parameters is…

Numerical Analysis · Mathematics 2024-08-16 Guoxiang Grayson Tong , Carlos A. Sing Long , Daniele E. Schiavazzi

Agile quadrotor flight in challenging environments has the potential to revolutionize shipping, transportation, and search and rescue applications. Nonlinear model predictive control (NMPC) has recently shown promising results for agile…

Robotics · Computer Science 2021-12-06 Drew Hanover , Philipp Foehn , Sihao Sun , Elia Kaufmann , Davide Scaramuzza

The conventional Wien filter is a device with orthogonal static magnetic and electric fields, often used for velocity separation of charged particles. Here we describe the electromagnetic design calculations for a novel waveguide RF Wien…

We propose a computationally tractable, tube-based robust nonlinear model predictive control (MPC) framework using difference-of-convex (DC) functions and sequential convex programming. For systems with differentiable discrete time…

Optimization and Control · Mathematics 2026-02-03 Martin Doff-Sotta , Zaheen A-Rahman , Mark Cannon

We present a nonlinear equivalent resistance tracking method to optimize the power output for solar arrays. Tracking an equivalent resistance results in nonlinear voltage step sizes in the gradient descent search loop. We introduce a new…

Systems and Control · Electrical Eng. & Systems 2024-09-23 Chaitanya Poolla , Abraham K. Ishihara
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