document

Input design and data-driven approaches based on convex optimization for fault diagnosis in linear systems

Noom, J. (author)

The complexity of automated systems has grown considerably during the past decades. This convolutes the observation of possible faults in these systems. If not being revealed timely, such faults can lead to catastrophic failures. As a result, there is a continuous interest in sophisticated fault diagnosis techniques. Since it is generally...

doctoral thesis 2024

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Kernel-based identification using Lebesgue-sampled data

González, Rodrigo A. (author), Tiels, Koen (author), Oomen, T.A.E. (author)

Sampling in control applications is increasingly done non-equidistantly in time. This includes applications in motion control, networked control, resource-aware control, and event-based control. Some of these applications, like the ones where displacement is tracked using incremental encoders, are driven by signals that are only measured when...

journal article 2024

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An identification algorithm of switched Box-Jenkins systems in the presence of bounded disturbances: An approach for approximating complex biological wastewater treatment models

Moradvandi, A. (author), Abraham, E. (author), Goudjil, Abdelhak (author), De Schutter, B.H.K. (author), Lindeboom, R.E.F. (author)

This paper focuses on the development of linear Switched Box–Jenkins (SBJ) models for approximating complex dynamical models of biological wastewater treatment processes. We discuss the adaptation of these processes to the SBJ framework, showing the model's generality and flexibility as a class of switched systems that can offer accurate...

journal article 2024

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Proximal-based recursive implementation for model-free data-driven fault diagnosis

Noom, J. (author), Soloviev, O.A. (author), Verhaegen, M.H.G. (author)

We present a novel problem formulation for model-free data-driven fault diagnosis, in which possible faults are diagnosed simultaneously to identifying the linear time-invariant system. This problem is practically relevant for systems whose model cannot be identified reliably prior to diagnosing possible faults, for instance when operating...

journal article 2024

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Physics enhanced sparse identification of dynamical systems with discontinuous nonlinearities

Lathourakis, C.L. (author), Cicirello, A. (author)

A method is introduced for the identification of the nonlinear governing equations of dynamical systems in the presence of discontinuous and nonsmooth nonlinear forces, such as the ones generated by frictional contacts, based on noisy measurements. The so-called Physics Encoded Sparse Identification of Nonlinear Dynamics (PhI-SINDy) builds...

journal article 2024

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Free Energy Principle Based Precision Modulation for Robot Attention: Towards brain inspired robot intelligence

Anil Meera, A. (author)

The potential impact of a grand unified theory of the brain on the robotics community might be immense, as it might hold the key to the general artificial intelligence. Such a theory might make revolutionary leaps in robot intelligence by improving the quality of our lives. The last two decades have witnessed the rise of one such brain theory -...

doctoral thesis 2023

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Identifying Lebesgue-sampled Continuous-time Impulse Response Models: A Kernel-based Approach

González, Rodrigo A. (author), Tiels, Koen (author), Oomen, T.A.E. (author)

Control applications are increasingly sampled non-equidistantly in time, including in motion control, networked control, resource-aware control, and event-triggered control. Some of these applications use measurement devices that sample equidistantly in the amplitude domain. The aim of this paper is to develop a non-parametric estimator of...

journal article 2023

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The existence and uniqueness of solutions for kernel-based system identification

Khosravi, M. (author), Smith, Roy S. (author)

The notion of reproducing kernel Hilbert space (RKHS) has emerged in system identification during the past decade. In the resulting framework, the impulse response estimation problem is formulated as a regularized optimization defined on an infinite-dimensional RKHS consisting of stable impulse responses. The consequent estimation problem is...

journal article 2023

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Signal selection for local module identification in linear dynamic networks: A graphical approach

Shi, S. (author), Cheng, Xiaodong (author), De Schutter, B.H.K. (author), Van den Hof, Paul M.J. (author)

In a dynamic network of interconnected transfer functions, it is not necessary to use all the node signals for estimating a local transfer function. Given the network topology, detailed conditions are available for selecting inputs and outputs in a (MIMO) predictor model that warrants consistent and minimum variance estimation of a target...

journal article 2023

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Examining the role of intrinsic and reflexive contributions to ankle joint hyper-resistance treated with botulinum toxin-A

van’t Veld, Ronald C. (author), Flux, Eline (author), van Oorschot, Wieneke (author), Schouten, A.C. (author), van der Krogt, Marjolein M. (author), van der Kooij, H. (author), Vos-van der Hulst, Marije (author), Keijsers, Noël L.W. (author), van Asseldonk, Edwin H.F. (author)

Background: Spasticity, i.e. stretch hyperreflexia, increases joint resistance similar to symptoms like hypertonia and contractures. Botulinum neurotoxin-A (BoNT-A) injections are a widely used intervention to reduce spasticity. BoNT-A effects on spasticity are poorly understood, because clinical measures, e.g. modified Ashworth scale (MAS),...

journal article 2023

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Kernel-based identification with frequency domain side-information

Khosravi, M. (author), Smith, Roy S. (author)

This paper discusses the problem of system identification when frequency domain side-information is available. We mainly consider the case where the side-information is provided as the H_∞-norm of the system being bounded by a given scalar. This framework allows considering different forms of frequency domain side-information, such...

journal article 2023

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Single module identifiability in linear dynamic networks with partial excitation and measurement

Shi, S. (author), Cheng, Xiaodong (author), Van den Hof, Paul M.J. (author)

Identifiability of a single module in a network of transfer functions is determined by whether a particular transfer function in the network can be uniquely distinguished within a network model set, on the basis of data. Whereas previous research has focused on the situations that all network signals are either excited or measured, we develop...

journal article 2023

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Design and Validation of a 3-DoF Wrist Perturbator Based on an Inverted Spatial Redundant 4-RUU Parallel Manipulator

Koene, Robbert (author), Meijaard, J.P. (author), van de Ruit, M.L. (author), Mugge, W. (author), van der Wijk, V. (author)

Humans vary the stiffness in their joints depending on tasks and circumstances. For posture control a high joint stiffness is required to withstand perturbations, whereas for force control a low joint stiffness is required. To investigate how humans vary their joint stiffness precisely for moving an arm, a wearable device is needed that can...

conference paper 2023

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Bayesian deep learning for system identification

Zhou, H. (author)

Applying deep neural networks (DNNs) for system identification (SYSID) has attracted more andmore attention in recent years. The DNNs, which have universal approximation capabilities for any measurable function, have been successfully implemented in SYSID tasks with typical network structures, e.g., feed-forward neural networks and recurrent...

doctoral thesis 2022

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An experimental validation of the polynomial curvature model: identification and optimal control of a soft underwater tentacle

Stella, F. (author), Obayashi, Nana (author), Della Santina, C. (author), Hughes, Josie (author)

The control possibilities for soft robots have long been hindered by the lack of accurate yet computationally treatable dynamic models of soft structures. Polynomial curvature models propose a solution to this quest for continuum slender structures. Nevertheless, the results produced with this class of models have been so far essentially...

journal article 2022

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System Parameter Identification of Thermal Generation Unit in the Mongolian Electrical Grid: Real-Life Frequency Response Test

Adiyabazar, Choidorj (author), Gonzalez-Longatt, F. (author), Acosta, Martha N. (author), Rueda, José L. (author), Bolor, Erkhemzaya (author)

Mongolian power grid (MPG) is becoming more eco-friendly as the power system is continuously integrating renewable energy, which reached 20% of the total installed capacity of Mongolia in 2020. The daily operation and the safety of the MPG have become very challenging because of increased levels of energy in the system. Therefore, the dynamic...

conference paper 2021

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Quantitative comparison of time-varying system identification methods to describe human joint impedance

van de Ruit, M.L. (author), Mugge, W. (author), Cavallo, Gaia (author), Lataire, John (author), Ludvig, Daniel (author), Schouten, A.C. (author)

Accurate and swift tuning of joint impedance is crucial to perform movement and interaction with our environment. Time-varying system identification enables quantification of joint impedance during movement. Many methods have been developed over the years, each with their own mathematical approach and underlying assumptions. Yet, for the...

journal article 2021

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Unifying system identification and biomechanical formulations for the estimation of muscle, tendon and joint stiffness during human movement

Cop, Christopher P. (author), Cavallo, Gaia (author), van'T Veld, Ronald C. (author), Koopman, Bart F.J.M. (author), Lataire, John (author), Schouten, A.C. (author), Sartori, Massimo (author)

In vivo joint stiffness estimation during time-varying conditions remains an open challenge. Multiple communities, e.g. system identification and biomechanics, have tackled the problem from different perspectives and using different methods, each of which entailing advantages and limitations, often complementary. System identification...

review 2021

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Neurophysiological validation of simultaneous intrinsic and reflexive joint impedance estimates

van ’t Veld, Ronald C. (author), Schouten, A.C. (author), van der Kooij, H. (author), van Asseldonk, Edwin H.F. (author)

Background: People with brain or neural injuries, such as cerebral palsy or spinal cord injury, commonly have joint hyper-resistance. Diagnosis and treatment of joint hyper-resistance is challenging due to a mix of tonic and phasic contributions. The parallel-cascade (PC) system identification technique offers a potential solution to...

journal article 2021

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Multisine frequency modulation of intra-epidermal electric pulse sequences: A novel tool to study nociceptive processing

van den Berg, Boudewijn (author), Manoochehri, M. (author), Kasting, Mindy (author), Schouten, A.C. (author), van der Helm, F.C.T. (author), Buitenweg, Jan R. (author)

A sustained sensory stimulus with a periodic variation of intensity creates an electrophysiological brain response at associated frequencies, referred to as the steady-state evoked potential (SSEP). The SSEPs elicited by the periodic stimulation of nociceptors in the skin may represent activity of a brain network that is primarily involved in...

journal article 2021