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This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This article appeared in: Tarigo, J. [et al.]. Basin entropy as an indicator of a bifurcation in a time-delayed system. "Chaos", Maig 2024, vol. 34, núm. 5, article 053113 and may be found at https://doi.org/10.1063/5.0201932, The basin entropy is a measure that quantifies, in a system that has two or more attractors, the predictability of a final state, as a function of the initial conditions. While the basin entropy has been demonstrated on a variety of multistable dynamical systems, to the best of our knowledge, it has not yet been tested in systems with a time delay, whose phase space is infinite dimensional because the initial conditions are functions defined in a time interval [-t,0], where t is the delay time. Here we consider a simple time delayed system consisting of a bistable system with a linear delayed feedback term. We show that the basin entropy captures relevant properties of the basins of attraction of the two coexisting attractors. Moreover, we show that the basin entropy can give an indication of the proximity of a Hopf bifurcation, but fails to capture the proximity of a pitchfork bifurcation. The Hopf bifurcation is detected because before the fixed points become unstable, a oscillatory, limit-cycle behavior appears that coexists with the fixed points. The new limit cycle modifies the structure of the basins of attraction, and this change is captured by basin entropy that reaches a maximum before the Hopf bifurcation. In contrast, the pitchfork bifurcation is not detected because the basins of attraction do not change as the bifurcation is approached. Our results suggest that the basin entropy can yield useful insights into the long-term predictability of time delayed systems, which often have coexisting attractors., J.P.T., C.S., and A.C.M. acknowledge support of PEDECIBA (MEC-Udelar, Uruguay); C.M. acknowledges support of ICREA ACADEMIA, AGAUR (2021 SGR 00606), and Ministerio de Ciencia e Innovación Spain (Project No. PID2021-123994NB-C21). The numerical experiments were performed at the ClusterUY (https://cluster.uy), Peer Reviewed, Postprint (author's final draft)

Aquest informe estudia l'aplicació de tècniques de reducció de models pel control predictiu no lineal (NMPC) dels reformadors d'etanol (ESR). S'estén el mètode de l'espai nul, tradicionalment utilitzat per a sistemes d'equacions diferencials ordinàries (ODEs) a sistemes d'equacions diferencials en derivades parcials (PDEs), proporcionant un marc sistemàtic per reduir la complexitat computacional d'aquests sistemes. L'estudi també proporciona una extensió del mètode de característiques mitjançant l'ús de tècniques numèriques de diferències finites, ampliant l'aplicabilitat del mètode a sistemes més complexos de PDEs hiperbòliques, com el reformador d'etanol (ESR). Mitjançant el mètode de l'espai nul, s'aconsegueix una reducció del temps computacional del sistema ESR d'aproximadament un 50%, mantenint una alta precisió, mentre que el mètode de característiques demostra una disminució del temps computacional de més del 90%. Cadascun dels dos mètodes es pot aplicar a diferents tipus de sistemes; si s'apliquen en paral·lel, les seves capacitats de millora de computació es superposen sense augmentar l'eficiència addicionalment. Els marcs matemàtics desenvolupats són versàtils i es poden aplicar al disseny de NMPCs per a diferents models descrits per equacions diferencials en derivades parcials (PDEs), amb un ampli ventall d'aplicacions en l'optimització de processos industrials., Este informe estudia la aplicación de técnicas de reducción de modelos para el control predictivo no lineal (NMPC) de reformadores de etanol (ESR). Se extiende el método del espacio nulo, tradicionalmente utilizado para sistemas de ecuaciones diferenciales ordinarias (ODEs), a sistemas de ecuaciones diferenciales en derivadas parciales (PDEs), proporcionando un marco sistemático para reducir la complejidad computacional de estos sistemas. El estudio también proporciona una extensión del método de características mediante el uso de técnicas numéricas de diferencias finitas, ampliando la aplicabilidad del método a sistemas más complejos de PDEs hiperbólicas, como el ESR. A través del método del espacio nulo, se consigue una reducción del tiempo de simulacion del sistema ESR de aproximadamente un 50%, manteniendo una alta precisión, mientras que el método de características demuestra una disminución del tiempo computacional de más del 90%. Cada uno de los dos métodos se puede aplicar a diferentes tipos de sistemas; si se aplican en paralelo, sus capacidades de mejora de computación se superponen sin aumentar la eficiencia adicionalmente. Los marcos matemáticos desarrollados son versátiles y se pueden aplicar al diseño de NMPCs para diferentes modelos descritos por sistemas de ecuaciones diferenciales en derivadas parciales (PDEs), con un amplio abanico de aplicaciones en la optimización de procesos industriales., This report explores the application of model reduction techniques to the nonlinear model predictive control (NMPC) of ethanol steam reformers (ESR). It extends the null-space method traditionally used for systems of ordinary differential equations (ODEs) to systems of partial differential equations (PDEs), providing a systematic framework for reducing the computational complexity of these systems. The study also provides an extension of the method of characteristics by using features from the finite differences method which broadens the applicability of the method to more complex systems of hyperbolic PDEs, such as the ethanol steam reformer (ESR). Through the null-space method, the reduction of computational time for simulations of the ESR system is approximately 50%, maintaining high accuracy, while the method of characteristics demonstrates over 90% computational time decrease. Each of the two methods can be applied to different types of systems; if applied in parallel, their computation-reducing capabilities overlap without further increase in efficiency. The mathematical frameworks developed are versatile and can be applied to produce real-time NMPC for different models described by systems of partial differential equations (PDEs), with a broad range of applications in industrial process optimization., Outgoing

Fuel cells are electrochemical devices with some internal variables that cannot be measured, but have to be monitored in real-time. That is the case for the liquid water inside the fuel cell catalyst layer. This motivates the development of online algorithms, i.e., observers, able to estimate such variables. Nonetheless, fuel cell dynamics are strongly nonlinear, with significant parametric uncertainty and significant sensor noise. Therefore, typical observers, the extended Kalman filter (EKF), usually underperform or are unstable in such systems. To overcome such limitations, this work proposes a novel nonlinear observer to estimate the liquid water saturation in fuel cells based on an inherent differential detectability of the liquid water dynamics. The stability of the proposal is formally analyzed and it is validated through numerical simulations and in an experimental prototype, where noise and uncertainty are considered., This work has been partially funded by the Spanish Ministry of Universities funded by the European Union-Next Generation EU (2022UPC-MSC-93823). This work is part of the Project MAFALDA (PID2021-126001OB-C31) funded by MCIN/AEI /10.13039/501100011033 and by "ERDFA way of making Europe".This work is part of the project MASHED (TED2021-129927B-I00), funded by MCIN/AEI/10.13039/501100011033 and by the European Union Next Generation EU/PRTR., Peer Reviewed, Postprint (author's final draft)

Semiconductor lasers with optical feedback are stochastic nonlinear systems that can display complex dynamics and abrupt changes when their operation conditions change. Even very small changes can lead to large variations in the spatial and spectral properties of the laser emission. This makes a semiconductor laser with feedback an ideal system for conducting controlled experiments to test data analysis tools to detect and characterize transitions. Here, we identify feedback-induced transitions by analyzing speckle patterns that are generated after the laser light propagates in an optical fiber. Speckle patterns result from the interference of multiple modes, and their statistical properties are understood, but a direct mathematical model does not exist. Here we show the versatility of the correlation length and the permutation entropy as measures for characterizing speckle patterns. Combining entropy and correlation analysis with speckle contrast analysis, we uncover changes that occur when the laser current increases from below to well above the threshold, which unveils the effects of optical feedback on the coherence of the laser emission., Ministerio de Ciencia, Innovación y Universidades (Grant No. PID2021-123994NB-C21); Institució Catalana de Recerca i Estudis Avançats (ICREA Academia); Agencia de Gestió d’Ajuts Universitaris i de Recerca (Grant Nos. AGAUR, 2021 SGR 00606 and FI scholarship)., Peer Reviewed, Postprint (published version)

In this paper we address the challenging problem of designing globally convergent estimators for the parameters of nonlinear systems containing a non-separable exponential nonlinearity. This class of terms appears in many practical applications, and none of the existing parameter estimators is able to deal with them in an efficient way. The proposed estimation procedure is illustrated with two modern applications: fuel cells and human musculoskeletal dynamics. The procedure does not assume that the parameters live in known compact sets, that the nonlinearities satisfy some Lipschitzian properties, nor rely on injection of high-gain or the use of complex, computationally demanding methodologies. Instead, we propose to design a classical on-line estimator whose dynamics is described by an ordinary differential equation given in a compact precise form. A further contribution of the paper is the proof that parameter convergence is guaranteed with the extremely weak interval excitation requirement., This paper is supported by the Ministry of Science and Higher Education of Russian Federation, passport of goszadanie no. 2019-0898. This work is part of the project MAFALDA (PID2021-126001OB-C31) and MASHED (TED2021-129927B-I00) funded by MCIN/ AEI/10.13039/501100011033 and by the European Union Next GenerationEU/PRTR., Peer Reviewed, Postprint (author's final draft)

In previous research on fault switching of redundant actuators using monitoring modules, the interference of sensor faults on monitoring results has not received enough attention. In this paper, a new fault-tolerant control (FTC) method combining adaptive compensation and active switching is proposed for a class of uncertain nonlinear systems with backup actuators against actuator and sensor faults. While using command filtered backstepping to reduce computational burden, a direct adaptive compensation scheme is designed to ensure that sensor faults within tolerable bounds do not trigger actuator switching. Based on this, a new lumped monitoring function (MF) containing prescribed performances and tolerable sensor fault bounds is designed to detect and isolate faulty actuators and ensure that the tracking error always satisfies prescribed transient and steady-state performances. Two simulation cases are used for illustrating the proposed method. It is proved that the proposed method can effectively reduce the interference of sensor faults on actuator fault detection and improve the accuracy of actuator switching., This work is supported by the National Key R&D Program of China (Grant No. 2021YFB 2011300), the National Natural Science Foundation of China (Grant No. 52275044), and the Zhejiang Provincial Natural Science Foundation of China (Grant No. Z23E050032)., Peer Reviewed, Postprint (author's final draft)

A novel nonlinear encryption–decryption system based on a joint transform correlator (JTC) and the Gyrator transform (GT) for the simultaneous encryption and decryption of multiple images in grayscale is proposed. This security system features a high level of security for the single real-valued encrypted image and a high image quality for the multiple decrypted images. The multispectral or color images are considered as a special case, taking each color component as a grayscale image. All multiple grayscale images (original images) to encrypt are encoded in phase and placed in the input plane of the JTC at the same time without overlapping. We introduce two random-phase masks (RPMs) keys for each image to encrypt at the input plane of the JTC-based encryption system. The total number of the RPM keys is given by the double of the total number of the grayscale images to be encrypted. The use of several RPMs as keys improves the security of the encrypted image. The joint Gyrator power distribution (JGPD) is the intensity of the GT of the input plane of the JTC. We obtain only a single real-valued encrypted image with a high level of security for all the multiple grayscale images to encrypt by introducing two new suitable nonlinear modifications on the JGPD. The security keys are given by the RPMs and the rotation angle of the GT. The decryption system is implemented by two successive GTs applied to the encrypted image and the security keys given by the RPMs and considering the rotation angle of the GT. We can simultaneously retrieve the various information of the original images at the output plane of the decryption system when all the security keys are correct. Another result due to the appropriate definition of the two nonlinear operations applied on the JGPD is the retrieval of the multiple decrypted images with a high image quality. The numerical simulations are computed with the purpose of demonstrating the validity and performance of the novel encryption–decrypti, This research has been funded by the Universidad de La Guajira (Riohacha), the Universidad Popular del Cesar (Valledupar) and the Universitat Politècnica de Catalunya · BarcelonaTech, SGR 2021 SGR 00388 and the Agencia Estatal de Investigación, Spanish Government (PID2020- 114582RB-I00/AEI/10.13039/501100011033)., Peer Reviewed, Postprint (published version)

This paper presents the utilization of robust nonlinear control schemes for a single-rotor unmanned aerial vehicle (SR-UAV) mathematical model. The nonlinear dynamics of the vehicle are modeled according to the translational and rotational motions. The general structure is based on a translation controller connected in cascade with a P-PI attitude controller. Three different control approaches (classical PID, Super Twisting, and Adaptive Sliding Mode) are compared for the translation control. The parameters of such controllers are hard to tune by using a trial-and-error procedure, so we use an automated tuning procedure based on the Particle Swarm Optimization (PSO) method. The controllers were simulated in scenarios with wind gust disturbances, and a performance comparison was made between the different controllers with and without optimized gains. The results show a significant improvement in the performance of the PSO-tuned controllers., Peer Reviewed, Postprint (published version)

Constant power loading is an effect that appears in multiple-stage energy conversion systems with individually regulated switching power converters. In a two-stage system, an upstream or source converter drives one or more downstream or load converters. The downstream converters in a two-stage power conversion system are designed to provide the fastest transient response in stand-alone operation. Consequently, they behave as a constant power load (CPL) to the upstream converter within their control bandwidth. In the past, open-loop power converters feeding CPLs and operating in discontinuous conduction mode (DCM) were considered to be stable. In this paper, it is shown that these systems can undergo instabilities, which have been so far overlooked. First, numerical simulations from the switched model of an open-loop boost converter under DCM operation and loaded with a tightly regulated buck converter and the same converter loaded by an ideal CPL are presented to show that they exhibit similar nonlinear behavior and bifurcation phenomena. Then, the three elementary open-loop DC–DC converters operating in the DCM were considered and their bifurcation phenomena were revealed. It is shown that the period-doubling route to chaos in the DC–DC boost converter is interrupted by a sudden appearance of dangerous destructive dynamics due to the excessively unlimited load current in the CPL. For the buck converter, only the first period-doubling bifurcation is observed before the destructive behavior appears. The open-loop buck–boost converter under DCM and feeding a CPL is always unstable and exhibits no periodic orbit. Based on the observed phenomena, approximate discrete-time models were derived, which despite their simplicity, were seen to display the most-important and -essential features of the corresponding switching converters before destructive dynamics occurs., Postprint (published version)

In 2002, in a seminal article, Bandt and Pompe proposed a new methodology for the analysis of complex time series, now known as Ordinal Analysis. The ordinal methodology is based on the computation of symbols (known as ordinal patters) which are defined in terms of the temporal ordering of data points in a time series, and whose probabilities are known as ordinal probabilities. With the ordinal probabilities the Shannon entropy can be calculated, which is the permutation entropy. Since it was proposed, the ordinal method has found applications in fields as diverse as biomedicine and climatology. However, some properties of ordinal probabilities are still not fully understood, and how to combine the ordinal approach of feature extraction with machine learning techniques for model identification, time series classification or forecasting, remains a challenge. The objective of this perspective article is to present some recent advances and to discuss some open problems., The authors acknowledge hospitality of the Max Planck Institute for the Physics of Complex Systems, where a collaboration was established and this work started. C.M. acknowledges funding from the ICREA ACADEMIA pro- gram, Generalitat de Catalunya; M.Z. from the Euro- pean Research Council (ERC) under grant agreement No 851255; MZ and JHM. from the Spanish State Re- search Agency through Grant MDM-2017-0711 funded by MCIN/AEI/10.13039/501100011033; I.L. from the Spanish State Research Agency through Grant PID2020- 113737GB-I00. JHM acknowledges J. M. Buldú for valu- able comments and J. J. Ramasco for his assistance., Peer Reviewed, Postprint (author's final draft)

The Nobel Prize in Physics 2021 was awarded to Syukuro Manabe, Klaus Hasselmann, and Giorgio Parisi for their “groundbreaking contributions to our understanding of complex systems,” including major advances in the understanding of our climate and climate change. In this Perspective article, we review their key contributions and discuss their relevance in relation to the present understanding of our climate. We conclude by outlining some promising research directions and open questions in climate science., All authors received funding from the European Union’s Horizon 2020 research and innovation program under Marie Sklodowska Curie Grant Agreement No. 813844. C.M. also acknowledges funding from the Spanish Ministerio de Ciencia, Innovación y Universidades (No. PGC2018-099443-B-I00) and the ICREA ACADEMIA program of Generalitat de Catalunya. J.K. was supported by the Russian Ministry of Science and Education (Agreement No. 075-15-2020-808)., Peer Reviewed, Postprint (published version)

Despite time-dependent boundary conditions being ubiquitous in natural and industrial flows, to date the influence of such temporal modulations (e.g. with driving frequency O_H) has been given minor attention. The present problem addresses ferrofluidic Couette flow in between counter-rotating cylinders in a spatially homogeneous magnetic field subject to time-periodic modulation. Such a modulation can lead to a significant inner Reynolds number (Re_i) enhancement for both, either helical and toroidal flow structures. Using a modified Niklas approximation, the effect of low- and high-frequency modulation onto the primary instabilities, stability boundaries as well as on the non-linear oscillations that may occur is investigated. Focusing on bi-stable co-existing solutions, around their stability thresholds quite complex non-linear system response and flow dynamics is detected. For the system remaining supercritical always a single solution is selected by O_H, while crossing the bifurcation thresholds within a modulation period the triggered system response is more complex, reaching from alternation between different solutions towards the appearance of intermittent behavior., Peer Reviewed, Postprint (published version)

Behavioral contagion and the presence of behavioral cascades are natural features in groups of animals showing collective motion, such as schooling fish or grazing herbivores. Here we study empirical behavioral cascades observed in fish schools defined as avalanches of consecutive large changes in the heading direction of the trajectory of fish. In terms of a minimum turning angle introduced to define a large change, avalanches are characterized by distributions of size and duration showing scale-free signatures, reminiscent of self-organized critical behavior. We observe that avalanches are generally triggered by a small number of fish, which act as effective leaders that induce large rearrangements of the group’s trajectory. This observation motivates the proposal of a simple model, based in the classical Vicsek model of collective motion, in which a given individual acts as a leader subject to random heading reorientations. The model reproduces qualitatively the empirical avalanche behavior observed in real schools, and hints towards a connection between effective leadership, long range interactions and avalanche behavior in collective movement., Peer Reviewed, Award-winning, Postprint (published version)

Representing a complex fluid, the field of ferrofluid research developed quickly in different branches of Physics, Chemistry and Engineering since the first successful production of stable ferrofluids in the early 1960s. Their complexity, rich variety of parameters, properties and especially the controllability make them both, very interesting for engineering and medical applications, but at the same time challenging in numerical simulations. Ferrofluids, in absence of an applied magnetic field, behave like an “ordinary fluid”but when a sufficiently strong magnetic field is applied, the ferrofluid flows toward regions of the magnetic field, properties of the fluid such as the viscosity are altered, and the system hydrodynamics can be significantly changed. In this presentation, I will present the results of numerical simulations considering the Taylor-Couette system as prototypical model system to study pattern formation and bifurcation theory. I will provide an overview of the non-linear system response for different applied magnetic field configurations and magnetic field strengths which lead to very rich dynamics, time-dependent states and multiplicity of solutions. General observation is the fact that any external applied magnetic field (static or time-dependent), regardless it’s orientation stabilizes the basic state, i.e. the bifurcation thresholds of the primary instabilities are moved to larger control parameters. Additional symmetry breaking magnetic fields, e.g. transversely oriented, render the flow to become intrinsic three dimensional and thus significantly modify and increase the flow complexity. The observation of flow pattern reversal with variation in strength of the magnetic field highlights only one of such an effect and the potential to manipulate the underlying flow dynamics. Eventually, moving from static to time-dependent, i.e. alternating magnetic fields, allows to address the huge number of natural and industrial flows, which are subjected t, Peer Reviewed, Postprint (published version)

© 2222 Optica Publishing Group. Users may use, reuse, and build upon the article, or use the article for text or data mining, so long as such uses are for non-commercial purposes and appropriate attribution is maintained. All other rights are reserved., We study experimentally and numerically the dynamics of a semiconductor laser near threshold, subject to optical feedback and sinusoidal current modulation. The laser operates in the low frequency fluctuation (LFF) regime where, without modulation, the intensity shows sudden spikes at irregular times. Under particular modulation conditions the spikes lock to the modulation and their timing becomes highly regular. While the modulated LFF dynamics has received a lot of attention, an in-depth comparison with the predictions of the Lang-Kobayashi (LK) model has not yet been performed. Here we use the LK model to simulate the laser dynamics and use the Fano factor to quantify the regularity of the timing of the spikes. The Fano factor is calculated by counting the number of spikes in successive segments of the intensity time-series and keeps information about temporal order in the spike sequence that is lost when the analysis is based on the distribution of inter-spike intervals. Here we compare the spike timing regularity in experimental and in simulated spike sequences as a function of the modulation amplitude and frequency and find a good qualitative agreement. We find that in both experiments and simulation for appropriate conditions the spike timing can be highly regular, as revealed by very small values of the Fano factor., Institució Catalana de Recerca i Estudis Avançats (Academia); Ministerio de Ciencia, Innovación y Universidades (PGC2018-099443-B-I00)., Peer Reviewed, Postprint (published version)

© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works, A number of physical systems allow a complex-valued representation. This article extends the theory of sliding modes to a class of nonlinear systems described by complex-valued variables. Hence, states, parameters, control actions, and sliding manifolds belong, in general, to the complex field. In this article, it is also shown that the proposed design in the complex-valued framework provides shorter reaching times to the sliding manifold than the standard sliding-mode design at equal initial condition and control effort. Different implementation approaches are also evaluated, and numerical examples illustrate the proposal., Peer Reviewed, Postprint (author's final draft)

In this paper, we present an effective online planning solution for autonomous vehicles that aims at improving the computational load while preserving high levels of performance in racing scenarios. The method follows the structure of the model predictive (MP) optimal strategy where the main objective is to maximize the velocity while smoothing the dynamic behavior and fulfilling varying constraints. We focus on reformulating the non-linear original problem into a pseudo-linear problem by convexifying the objective function and reformulating the non-linear vehicle equations to be expressed in a Linear Parameter Varying (LPV) form. In addition, the ability of avoiding obstacles is introduced in a simple way and with reduced computational cost. We test and compare the performance of the proposed strategy against its non-linear approach through simulations. We focus on testing the performance of the trajectory planning approach in a racing scenario. First, the case of free obstacles track and afterwards a scenario including static obstacles. Simulation results show the effectiveness of the proposed strategy by reducing the algorithm elapsed time while finding appropriate trajectories under several input/state constraints., Peer Reviewed, Postprint (author's final draft)

We study a two-dimensional low-dissipation nonautonomous dynamical system, with a control parameter that is swept linearly in time across a transcritical bifurcation. We investigate the relaxation time of a perturbation applied to a variable of the system and we show that critical slowing down may occur at a parameter value well above the bifurcation point. We test experimentally the occurrence of critical slowing down by applying a perturbation to the accessible control parameter and we find that this perturbation leaves the system behavior unaltered, thus providing no useful information on the occurrence of critical slowing down. The theoretical analysis reveals the reasons why these tests fail in predicting an incoming bifurcation., JRT thanks the program ECOS-Sud A14E03 Evénements extr^emes en dynamique non linéaire for granting support to this research. MG and MM acknowledge ANR Blason (ANR-18-CE24-0002). CM acknowledges partial support from Spanish MINECO (PGC2018-099443-B-I00) and from the program ICREA ACADEMIA of Generalitat de Catalunya., Peer Reviewed, Postprint (author's final draft)

A complete geometric classification of symmetries of autonomous Hamiltonian systems is established; explaining how to obtain their associated conserved quantities in all cases. In particular, first we review well-known results and properties about the symmetries of the Hamiltonian and of the symplectic form and then some new kinds of non-symplectic symmetries and their conserved quantities are introduced and studied., I acknowledge the financial support from the Spanish Ministerio de Econom´ıa y Competitividad project MTM2014–54855–P, the Ministerio de Ciencia, Innovaci´on y Universidades project PGC2018-098265-BC33, and the Secretary of University and Research of the Ministry of Business and Knowledge of the Catalan Government project 2017–SGR–932. I also greatly appreciate the comments and suggestions of Prof. Mikhail S. Plyushchay. Finally, my thanks to the referees for their extensive and valuable comments that have allowed me to significantly improve the final version of the work., Postprint (author's final draft)

Base (seismic) isolation is a promising technology for seismic protection of buildings and other constructions. Nowadays, it is accepted that such a technique is efficient and reliable; however, it has two major limitations: soft foundation soil, and tall buildings. The first issue restrains the seismic isolation spreading, given that soft soil is frequent in densely populated areas, and usually such a soil type concentrates the highest seismicity levels. This paper aims to contribute to demonstrating that base isolation, if properly implemented, can be suitable for soft soil. A representative case study is analyzed: a 6-story reinforced concrete (RC) building with base isolation that has recently been built in Shanghai. Since the building is founded on soft soil, concern regarding base isolation suitability arose; even the Chinese design code does not recommend this solution for soft soil. To clarify this issue, non-linear time-history analyses are carried out for a number of natural and artificial seismic inputs that represent the site seismicity; the superstructure behavior is linear, while nonlinearities are concentrated in the isolation layer. The adequacy of base isolation is assessed in the superstructure (in terms of reduction of interstory drift, absolute acceleration and shear force) and in the isolation layer (in terms of axial force, torsion angle and shear strain). The relevance of soil–structure interaction is discussed. The behavior when the mechanical parameters of the isolation units have experienced important changes is also analyzed. The major conclusion is that base isolation of ordinary mid-height RC buildings founded on soft soil can perform satisfactorily in medium seismicity regions., Peer Reviewed, Postprint (published version)

Standard state estimation techniques, either for linear or nonlinear systems, typically assume a perfect knowledge of the system, i.e., known process and measurement functions, and the corresponding noise statistics. The filter performance strongly depends on such knowledge and a possible model mismatch may lead to a significant performance degradation, but closed-form expressions for the resulting bias and covariance are not available. In this contribution, we explore the impact in extended Kalman filter approximations of a parametric model mismatch on both system functions and provide expressions for the estimator bias and covariance error induced by the mismatch. An illustrative example is shown to support the discussion., Peer Reviewed, Postprint (published version)

This paper introduces a new Takagi–Sugeno (TS) reconfiguration block structure for control reconfiguration of nonlinear systems with sensor and actuator faults represented by TS models and provides conditions for the existence of such blocks that ensures the stability recovery by fault hiding. The proposed reconfiguration block structure consists of a convex sum of linear transformations of the control signals and the sensor measurements hiding the fault occurrence from the nominal controller. Similar static reconfiguration blocks were previously proposed in the literature, however the conditions for their feasibility are more restrictive. This paper presents novel conditions based on the Lyapunov stability theory for obtaining those TS reconfiguration blocks for stability recovery after actuator and sensor faults. These conditions are obtained by assuming that the Lyapunov function that ensures the stability of fault-free closed-loop TS system is a valid Lyapunov candidate for the reconfigured TS system under faulty conditions. In particular, stability recovery conditions for nonlinear systems represented by TS models with nonlinear consequent and networked TS models are provided. Simulation results for a power system and a network of pendulum systems are used to illustrate the effectiveness of the proposed reconfiguration block., Peer Reviewed, Postprint (author's final draft)

When dealing with real control experimentation, the designer has to take into account several uncertainties, such as: time variation of the system parameters, exogenous perturbation and the presence of time delay in the feedback line. In the later case, this time delay behaviour may be random, or chaotic. Hence, the control block has to be robust. In this work, a robust delay-dependent controller based on H8 theory is presented by employing the linear matrix inequalities techniques to design an efficient output feedback control. This approach is carefully tuned to face with random time-varying measurement feedback and applied to the Furuta pendulum subject to an exogenous ground perturbation. Therefore, a recent experimental platform is described. Here, the ground perturbation is realised using an Hexapod robotic system. According to experimental data, the proposed control approach is robust and the control objective is completely satisfied., Peer Reviewed, Postprint (published version)

The West African Monsoon (WAM) system is the main source of rainfall in the agriculturally based region of the Sahel. Understanding transport across the WAM is of crucial importance due to the strong impact of humidity and dust pathways on local cloud formation. However, the description of this transport is challenging due to its 3D complex nature. Lagrangian Coherent Structures (LCS) simplify transport description across the WAM by providing a geometrical partition of the troposphere into domains. Air parcels within each domain have similar dynamical characteristics. LCS make it possible to achieve an integrated vision of transport pathways across this system. Using this approach we unveil new connections in the WAM system. In particular, we identify transport pathways between the Tropical Easterly Jet (TEJ) and the African Easterly Jet (AEJ). Furthermore, the clockwise circulation associated with the divergent upper part of the Sahara heat low is clearly delimitated. Additionally, we show the presence of mixing regions in the AEJ and the lower part of the TEJ that are linked to pathways to sources of dust and humidity., Peer Reviewed, Postprint (published version)

This paper considers fault detection of uncertain linear parameter varying systems that have polynomial dependence on parametric uncertainties. A conventional set-membership (SM) approach is able to ensure zero false alarm rate (FAR) by using conservative threshold sets, but usually results in a high missed detection rate (MDR) due to equally treating all uncertainty realizations without distinguishing between high and low probability of occurrence. To address this limitation, a probabilistic SM parity relation approach is proposed to exploit probabilistic information on the parametric uncertainties, which results in a reduced MDR by admitting an acceptable FAR. The parity relation is first polynomially parameterized with respect to uncertain parameters. Then, Gaussian mixtures are adopted to efficiently compute uncertainty propagation from stochastic uncertainties to the residual distribution. To achieve an acceptable FAR, a non-convex confidence set of residuals – represented by a union of ellipsoids – is determined for the consistency test. The effectiveness of the proposed approach is illustrated using a continuous stirred tank reactor example including performance comparisons with a deterministic zonotope-based method., Peer Reviewed, Postprint (author's final draft)

This paper deals with the analysis of numerically obtained spatio-temporal data for thermal convection in a two-dimensional circular annulus. These data are post-processed using a recent method called the spatio-temporal Koopman decomposition, which applies to the frequent case in which the underlying dynamics exhibit oscillatory (possibly growing or decaying) behavior in both time and one of the spatial directions (the azimuthal coordinate for the present problem). When this holds, the method decomposes the data into Fourier-like series in both the distinguished spatial direction and time. In the general case, the obtained series account for, not only the involved temporal frequencies and spatial wavenumbers, but also the spatial and temporal growth rates. In the simpler situation of attractors showing spatially periodic behavior, the spatial and temporal growth rates vanish (or are very small). In this case, the analysis of the wavenumber–frequency pairs that are present allows for uncovering the spatio-temporal structure of the flow in the circular annulus. The analysis focuses on periodic and quasi-periodic attractors, which exhibit spatio-temporal symmetries that are identified by the method. In addition, for quasi-periodic attractors, the method gives semi-analytic descriptions for the tori densely covered by particular trajectories. Although the paper concentrates on the thermal convection problem in an annulus, it will become clear that the method applies to other related dynamics as well., Postprint (author's final draft)