Non-Intrusive Load Monitoring.

Non-Intrusive load monitoring (NILM) represents an emerging strategy based on the application of sevaral multidisciplinary topics [...].

Human Control Model Estimation in Physical Human-Machine Interaction: A Survey.

The study of human-machine interaction as a unique control system was one of the first research interests in the engineering field, with almost a century having passed since the first works appeared in this area. At the same time, it is a crucial aspect of the most recent technological developments made in application fields such as collaborative robotics and artificial intelligence. Learning the processes and dynamics underlying human control strategies when interacting with controlled elements or objects of a different nature has been the subject of research in neuroscience, aerospace, robotics, and artificial intelligence. The cross-domain nature of this field of study can cause difficulties in finding a guiding line that links motor control theory, modelling approaches in physiological control systems, and identifying human-machine general control models in manipulative tasks. The discussed models have varying levels of complexity, from the first quasi-linear model in the frequency domain to the successive optimal control model. These models include detailed descriptions of physiologic subsystems and biomechanics. The motivation behind this work is to provide a complete view of the linear models that could be easily handled both in the time domain and in the frequency domain by using a well-established methodology in the classical linear systems and control theory.

Remote recovery of audio signals from videos of optical speckle patterns: a comparative study of signal recovery algorithms.

Optical remote sensors are nowadays ubiquitously used, thanks to unprecedented advances in the last decade in photonics, machine learning and signal processing tools. In this work we study experimentally the remote recovery of audio signals from the silent videos of the movement of optical speckle patterns. This technique can be used even when in between the source and the receiver there is a medium that does not allow for the propagation of sound waves. We use a diode laser to generate a speckle pattern on the membrane of a loudspeaker and a low-cost CCD camera to record the video of the movement of the speckle pattern when the loudspeaker plays an audio signal. We perform a comparative analysis of six signal recovery algorithms. In spite of having different complexity and computational requirements, we find that the algorithms have (except for the simplest one) good performance in terms of the quality of the recovered signal. The best trade-off, in terms of computational costs and performance, is obtained with a new method that we propose, which recovers the signal from the weighted sum of the intensities of all the pixels, where the signs of the weights are determined by selecting a reference pixel and calculating the signs of the cross-correlations of the intensity of the reference pixel and the intensities of the other pixels.

Turing patterns via pinning control in the simplest memristive cellular nonlinear networks.

Complex patterns are commonly retrieved in spatially-extended systems formed by coupled nonlinear dynamical units. In particular, Turing patterns have been extensively studied investigating mathematical models pertaining to different fields, such as chemistry, physics, biology, mechanics, and electronics. In this paper, we focus on the emergence of Turing patterns in memristive cellular nonlinear networks by means of spatial pinning control. The circuit architecture is made by coupled units formed by only two elements, namely, a capacitor and a memristor. The analytical conditions for which Turing patterns can be derived in the proposed architecture are discussed in order to suitably design the circuit parameters. In particular, we derive the conditions on the density of the controlled nodes for which a Turing pattern is globally generated. Finally, it is worth to note that the proposed architecture can be considered as the simplest ideal electronic circuit able to undergo Turing instability and give rise to pattern formation.

Interaction between synchronization and motion in a system of mobile agents.

In this paper, we study synchronization in time-varying networks inherited by the Vicsek's model of self-propelled particles. In our model, each particle/agent moves in a two dimensional space according to the Vicsek's rules and is associated to a chaotic system. The dynamics of two oscillators are coupled with each other only when agents are at a distance less than an interaction radius. We investigate the system behavior with respect to some fundamental parameters, and, in particular, to the noise level, which for increasing intensity drives the system from an ordered motion to a disordered one. We show that the global dynamics is ruled by the interplay between motion characteristics and dynamical coupling with synchronization either favored or inhibited by a coordinated motion of the self-propelled particles. Finally, we provide semi-analytical estimation for the synchronization thresholds for interconnections occurring at a time-scale shorter than that of the associated dynamical systems.

Analysis of remote synchronization in complex networks.

A novel regime of synchronization, called remote synchronization, where the peripheral nodes form a phase synchronized cluster not including the hub, was recently observed in star motifs [Bergner et al., Phys. Rev. E 85, 026208 (2012)]. We show the existence of a more general dynamical state of remote synchronization in arbitrary networks of coupled oscillators. This state is characterized by the synchronization of pairs of nodes that are not directly connected via a physical link or any sequence of synchronized nodes. This phenomenon is almost negligible in networks of phase oscillators as its underlying mechanism is the modulation of the amplitude of those intermediary nodes between the remotely synchronized units. Our findings thus show the ubiquity and robustness of these states and bridge the gap from their recent observation in simple toy graphs to complex networks.

Spiking Neuron Mathematical Models: A Compact Overview.

The features of the main models of spiking neurons are discussed in this review. We focus on the dynamical behaviors of five paradigmatic spiking neuron models and present recent literature studies on the topic, classifying the contributions based on the most-studied items. The aim of this review is to provide the reader with fundamental details related to spiking neurons from a dynamical systems point-of-view.

Spatial pinning control.

In this Letter, we introduce the concept of spatial pinning control for a network of mobile chaotic agents. In a planar space, N agents move as random walkers and interact according to a time-varying r-disk proximity graph. A control input is applied only to those agents which enter a given area, called control region. The control is effective in driving all the agents to a reference evolution and has better performance than pinning control on a fixed set of agents. We derive analytical conditions on the relative size of the control region and the agent density for the global convergence of the system to the reference evolution and study the system under different regimes inherited by the velocity.

A chaotic circuit based on Hewlett-Packard memristor.

Memristors are gaining increasing attention as next generation electronic devices. They are also becoming commonly used as fundamental blocks for building chaotic circuits, although often arbitrary (typically piece-wise linear or cubic) flux-charge characteristics are assumed. In this paper, a chaotic circuit based on the mathematical realistic model of the HP memristor is introduced. The circuit makes use of two HP memristors in antiparallel. Numerical results showing some of the chaotic attractors generated by this circuit and the behavior with respect to changes in its component values are described.

Robustness to noise in synchronization of network motifs: experimental results.

In this work, we experimentally investigate the robustness to noise of synchronization in all the four-nodes network motifs. The experimental setup consists of four Chua's circuits diffusively coupled in order to implement the six different undirected network motifs that can be obtained with four nodes. In this experimental setup, synchronization in the presence of noise injected in one of the network nodes is investigated and network motifs are compared in terms of the synchronization error obtained. The analysis has been then extended to some selected case studies of networks with five and six nodes. Numerical simulations have been also performed and results in agreement with experiments have been obtained. A correlation between node degree and robustness to noise has been found also in these networks.

Microrobots in Micromachines.

Robotics and micromachines are challenging topics in engineering [...].

Smart Materials.

The future of engineering systems is based on the capability of integrating sensors, actuators, control systems and materials [...].

Remote Ultrasound Scan Procedures with Medical Robots: Towards New Perspectives between Medicine and Engineering.

BACKGROUND: This review explores state-of-the-art teleoperated robots for medical ultrasound scan procedures, providing a comprehensive look including the recent trends arising from the COVID-19 pandemic. METHODS: Physicians' experience is included to indicate the importance of their role in the design of improved medical robots. From this perspective, novel classes of equipment for remote diagnostics based on medical robotics are discussed in terms of innovative engineering technologies. RESULTS: Relevant literature is reviewed under the system engineering point of view, organizing the discussion on the basis of the main technological focus of each contribution. CONCLUSIONS: This contribution is aimed at stimulating new research to obtain faster results on teleoperated robotics for ultrasound diagnostics in response to the high demand raised by the ongoing pandemic.

Lyapunov approach to synchronization of chaotic systems with vanishing nonlinear perturbations: From static to dynamic couplings.

Synchronization of chaotic dynamics can be pursued by means of different coupling strategies. Definitely, master-slave coupling represents one of the most adopted solutions, even if it presents some limitations due to the coupling term's selection strategy. In this paper, we investigate the role of different structures of coupling terms on the synchronization properties of master-slave chaotic system configurations. Here, Lyapunov theory for linear systems with nonlinear vanishing perturbations is exploited. The obtained results allow to determine the capability of a static, dynamic, or mixed coupling connection in stabilizing the synchronization manifold, using linear techniques based on the root locus. This knowledge allows to design the coupling structure considering also the synchronization error transient features, which are, here, shown to improve in the presence of higher-order dynamic couplings. A number of cases of study, involving classical chaotic nonlinear systems, show the efficacy and simplicity of the application of the strategy proposed.

An incomplete gallery: machines, cognition, and nonlinearities.

In this communication, some issues related to the old but still open question, on how far the development of cognitive processing in artificial machines can go, are discussed. A selected gallery of images derived from laboratory experiments are presented. The incompleteness of the gallery is as that in the definition of what we mean as cognitive processing.

Master-slave synchronization of hyperchaotic systems through a linear dynamic coupling.

The development of synchronization strategies for dynamical systems is an important research activity that can be applied in several different fields from locomotion control of multilimbed structures to secure communication. In the presence of chaotic systems, synchronization is more difficult to accomplish and there are different techniques that can be adopted. In this paper we considered a master-slave topology where the coupling mechanism is realized through a second-order linear dynamical system. This control scheme, recently applied to chaotic systems, is here analyzed in the presence of hyperchaotic dynamics that represent a more challenging scenario. The possibility to reach a complete synchronization and the range of allowable coupling strength is investigated comparing the effects of the dynamical coupling with a standard configuration characterized by a static gain. This methodology is also applied to weighted networks to reach synchronization regimes otherwise not obtainable with a static coupling.

Inferring connectivity of interacting phase oscillators.

The question as to how network topology properties influence network dynamical behavior has been extensively investigated. Here we treat the inverse problem, i.e., how to infer network connection topology from the dynamic evolution, and suggest a control based topology identification method. This method includes two steps: (i) driving the network to a steady state and (ii) inferring all elements of the connectivity matrix by exploiting information obtained from the observed steady state response of each node. We adopt different strategies for model-dependent (i.e., each local phase dynamics and coupling functions are known) and model-free (i.e., each local phase dynamics and coupling functions are unknown) cases and give detailed conditions for both cases under which network topology can be identified correctly. The influence of noise on topology identification is discussed as well. All proposed approaches are motivated and illustrated with networks of phase oscillators. We argue that these topology identification methods can be extended to general dynamical networks and are not restricted to only networks of phase oscillators.

Perception-action map learning in controlled multiscroll systems applied to robot navigation.

In this paper a new technique for action-oriented perception in robots is presented. The paper starts from exploiting the successful implementation of the basic idea that perceptual states can be embedded into chaotic attractors whose dynamical evolution can be associated with sensorial stimuli. In this way, it can be possible to encode, into the chaotic dynamics, environment-dependent patterns. These have to be suitably linked to an action, executed by the robot, to fulfill an assigned mission. This task is addressed here: the action-oriented perception loop is closed by introducing a simple unsupervised learning stage, implemented via a bio-inspired structure based on the motor map paradigm. In this way, perceptual meanings, useful for solving a given task, can be autonomously learned, based on the environment-dependent patterns embedded into the controlled chaotic dynamics. The presented framework has been tested on a simulated robot and the performance have been successfully compared with other traditional navigation control paradigms. Moreover an implementation of the proposed architecture on a Field Programmable Gate Array is briefly outlined and preliminary experimental results on a roving robot are also reported.

Separation and synchronization of chaotic signals by optimization.

In this paper synchronization of multiplexed chaotic systems with smooth nonlinearities is studied. The strategy to establish if such synchronization is achievable is based on the master stability function approach and on the optimization of the coupling parameters. With this approach we are able to show that systems formed by three independent canonical chaotic circuits (i.e., a Lorenz system, a Rössler oscillator, and a Chua's circuit) can be synchronized through a unique scalar signal.

Separation and synchronization of piecewise linear chaotic systems.

In this paper a topic regarding the synchronization of chaotic systems is dealt with: the case of separation and synchronization of many chaotic signals generated by different chaotic circuits and combined together is examined. In particular, an observer based strategy has been adopted, and an approach for the simultaneous stabilization of many Luenberger observers has been investigated to face the problem of separation and synchronization. The design strategy is based on linear matrix inequalities (LMIs). Indeed, the LMI problem is referred to have a solution if a dual optimization problem admits a solution. In our case the feasibility condition, if it does exist, allows us to establish that the separation and synchronization problem for the chosen circuit admits a solution. Some numerical simulations are reported. Further results refer to an experimental circuit showing the suitability of the approach. Furthermore, the use of the proposed scheme to transmit two or more information masked into two or more multiplexed chaotic signals and the design of suitable parameters through the introduced technique based on LMIs are discussed.