Search

In this paper, a new class of systems with nonclassical jump resonance behavior is presented. Although jump resonance has been widely studied in the literature, this contribution refers to systems presenting a multiple hysteresis jump resonance phenomenon, meaning that the frequency response of the system presents more hysteresis windows nested within the same range of frequency. The analytical conditions for observing this type of behavior are derived and a design strategy to obtain multiple hysteresis jump resonance in circuits and systems presented.

Chaos was historically discovered with the Lorenz attractor in 1963. Several artworks, created before that date, by post-war artists such as Fontana, Crippa, Mathieu and Tobey, seem to anticipate forms and shapes typically shown by chaotic systems. In this paper, we juxtapose these masterpieces with some strange attractors of dynamical system theory in a timeline leading to the question whether artists discovered chaos before scientists.

The study of social networks, and in particular those aspects related to disease spreading, has recently attracted considerable attention in the scientific community. In this paper, we investigate the effect of motion on the spread of diseases in dynamical networks of mobile agents. In order to simulate the long distance displacements empirically observed in real human movements, we consider different motion rules, such as random walks with the addition of jumps or Lévy flights. We compare the epidemic thresholds found in dynamical networks of mobile agents with the analogous expressions for static networks. We discuss the existing relations between dynamical networks of random walkers with jumps and static small-world networks, and those between systems of Lévy walkers and scale-free networks.

In this communication, synchronization of two diffusively coupled Chua's circuit is studied from the analytical and experimental points of view. The conditions under which complete synchronization is ensured are derived by applying a strategy based on the Master Stability Function. The experimental realization, that makes use of the State-Controlled Cellular Nonlinear Network based implementation of Chua's circuit, shows the synchronized behavior of two circuits coupled with a passive resistor as diffusion coefficient. The results obtained indicates diffusive coupling as a mutually reduced order state observer, in the sense that one circuit observes the other and vice versa. Moreover, the concept of synchronization by using passive elements can be extended to spatially extended reaction–diffusion systems.

In this brief letter new results regarding the discovery of jump resonance in driven Chua's circuit are given. Moreover, a parametric diagram characterizing this phenomenon is reported.

In this brief communication, we introduce a Chua's circuit based on a photoresistor nonlinear device and experimentally investigate the effects of controlling it by a light source. Light control affects the dynamics of the circuit in several ways, and the circuit can be controlled to exhibit periodicity, period-doubling bifurcations and chaotic attractors. The dynamics of the circuit that operates at frequencies up to kilohertz is strongly influenced by using periodic driving signals at low frequencies. In particular, experimental results have shown that an unstable intermittent behavior can be observed and that this can be stabilized by using feedback. Synchronization of two circuits has also been investigated.

In this communication the emergent behavior of clusters of robots with chaotic kinematics attractors is shown. Even if the aim of the research started from the study of the cooperative behavior of inspection robots, the reported results (including also the role of chaotic synchronization in the generation of the kinematics trajectory), show new aesthetic features of the motion in mechanical control systems.

This work consists in the realization and control of a walking microrobot actuated by piezoelectric materials. Usually, the actuation of robot legs is controlled by square wave signals characterized by fixed amplitude and frequency. In this work the control signals are generated performing a frequency modulation driven by the chaotic evolution of Chua's circuit state variables. The smooth changes of the actuation signal frequency, performed by our chaotic system, enhance the microrobot walking capabilities especially when walking on given surfaces.

In this paper, an entire organic Chua's circuit is presented. The adopted technology is one of the most advanced in the post-silicon era and extends the applications of classical silicon devices. The electronic circuit design is based on Organic Thin-Film Transistors (OTFTs). New electronic blocks based on OTFT are designed to be suitable with the organic technology features. Typical dynamics of the Chua's circuit have been reproduced.

Behavior-based robotics considers perception as a holistic process, strongly connected to behavioral needs of the robot. We present a bio-inspired framework for sensing-perception-action, applied to a roving robot in a random foraging task. Perception is here considered as a complex and emergent phenomenon where a huge amount of information coming from sensors is used to form an abstract and concise representation of the environment, useful to take a suitable action or sequence of actions. In this work a model for perceptual representation is formalized by means of RD-CNNs showing Turing patterns. They are used as attractive states for particular set of environmental conditions in order to associate, via a reinforcement learning, a proper action. Learning is also introduced at the afferent stage to shape the environment information according to the particular emerging pattern. The basins of attraction for the Turing patterns are so dynamically tuned by an unsupervised learning in order to form an internal, abstract and plastic representation of the environment, as recorded by the sensors.

The Local Activity Lemma establishes that "A homogeneous nonconservative medium cannot exhibit complexity unless it is locally active". In this communication, starting from the previous remark we report examples that prove systems with complex local active behavior like Reaction–Diffusion Cellular Nonlinear Networks (RD-CNNs) can work as image processors also in the 3D domain.

In this work a project which aims at the construction of LampBot II, an autonomous biologically-inspired swimming robot, is presented. LampBot II is capable of mimicking the undulatory swimming of a sea lamprey. The system used to generate locomotion is based on the paradigm of the Central Pattern Generator (CPG) and is implemented on a chip based on a Cellular Nonlinear Network (CNN). Two prototype structures have been developed in order to evaluate the feasibility of the actuation by means of Shape Memory Alloy (SMA) wires or servo motors.

This paper introduces a new application of the Field Programmable Analog Array. Ease of design and reprogrammability are the advantages offered by this class of analog circuits, making them an ideal environment for the implementation of chaotic circuits and their experimental characterization. Chua's circuit, a well-known paradigm of nonlinear circuits, has been used as an example of application. Experimental results show the suitability of the approach, highlighting the features of the new implementation: a fully on the fly programmable Chua's circuit has been obtained.

Central Pattern Generators (CPGs) are a suitable paradigm to solve the problem of locomotion control in walking robots. CPGs are able to generate feed-forward signals to achieve a proper coordination among the robot legs. In literature they are often modelled as networks of coupled nonlinear systems. However the topic of feedback in these systems is rarely addressed. On the other hand feedback is essential for locomotion. In this paper the CPG for a hexapod robot is implemented through Cellular Neural Networks (CNNs). Feedback is included in the CPG controller by exploiting the dynamic properties of the CPG motor-neurons, such as synchronization issue and local bifurcations. These universal paradigms provide the essential issues to include sensory feedback in CPG architectures based on coupled nonlinear systems. Experiments on a dynamic model of a hexapod robot are presented to validate the approach introduced.

In this letter the so-called frequency switched Chua's circuit is presented. Its realization is based on the introduction of a switch device into the Chua's circuit, realized by using three State-Controlled CNN cells. The dynamics of this system has been investigated both numerically and experimentally with respect to the frequency of the switch enabling signal. It exhibits different strange attractors, according to the variation of the frequency of the switching signal. Moreover, very strange frequency hysteresis phenomena demonstrating the peculiarity of the introduced circuit have been revealed.

In this paper, systems formed by networks of simple nonlinear cells are studied. Using lattice models, some of the fundamental features of complex systems such as self-organization and pattern formation are illustrated. In the first part of this work, a lattice of identical Chua's circuit is used to experimentally study its global spatiotemporal dynamics, according to the variation of some macroparameters, like the coupling coefficient or the neighboring dimension. The second part of the paper deals with the remarkable improvements regarding regularization and pattern formation, obtained in networks of nonlinear systems by introducing some spatial diversity, especially generated by deterministic, unpredictable dynamics. Simulation results show that synchronization and self-organization occur in networks with a few nonlocally connected cells, with irregular topology and small spatial diversity.

This letter deals with the remarkable effects observed in arrays of circuits and systems when parameter spatial diversity is induced by using chaos, leading to pattern formation and regularization. The communication emphasizes the fact that generating spatial dissymmetries by using chaos enhances regularity and pattern formation capability with respect to the case in which diversity is generated by random processes. Several examples are reported showing the previous conjecture. A further aim of the paper is to emphasize that the introduction of a small amplitude chaotic spatial diversity could control chaos in both 1D and 2D large scale connected arrays of nonlinear circuits like Cellular Neural Network (CNN).

In this paper, experimental results showing that the dynamics of Chua's circuit can be controlled by using water electrolytic cell based devices are reported. A Chua's circuit where one of the electrical components is replaced by an electrolytic cell device has been realized and its dynamics has been studied showing how different regimes appear when the parameters of the cell (in particular, the level of immersion of the electrode plates and the distance between them) are changed. The results obtained pave the way to the possibility of coupling nonlinear electronic components with electrochemical devices so as to develop a new hybrid technology for implementing a new class of nonlinear circuits.

In this paper, the dynamics of Chua's circuit in jerk form is presented. It is proved that two forms of Chua's circuit in jerk dynamics can be derived. The electronic circuit of the simpler dynamics has been implemented. The link between Chua's circuit and the search for simple jerk circuits has been established, therefore, proposing complex dynamics (like that of Chua's circuit) in jerk form.

In this paper, a dynamical model based on Kuramoto-like oscillators is used to represent the Italian high-voltage power grid. Nodes of the network are generators/substations, while links are the physical connections between generators/substations. The normal operating regime of the power grid corresponds to the regime in which the oscillations of all the nodes are synchronized. We studied the conditions for synchronization and the effect of dynamical perturbations on the nodes. The analysis allows to define several dynamical parameters assessing the dynamical robustness of the network.

In this paper, we analytically study a star motif of Stuart–Landau oscillators, derive the bifurcation diagram and discuss the different forms of synchronization arising in such a system. Despite the parameter mismatch between the central node and the peripheral ones, an analytical approach independent of the number of units in the system has been proposed. The approach allows to calculate the separatrices between the regions with distinct dynamical behavior and to determine the nature of the different transitions to synchronization appearing in the system. The theoretical analysis is supported by numerical results.