Luigi Fortuna

Chaotic sequences to improve the performance of evolutionary algorithms

This paper proposes an experimental analysis on the convergence of evolutionary algorithms (EAs). The effect of introducing chaotic sequences instead of random ones during all the phases of the evolution process is investigated. The approach is based on the substitution of the random number generator (RNG) with chaotic sequences. Several numerical examples are reported in order to compare the performance of the EA using random and chaotic generators as regards to both the results and the convergence speed. The results obtained show that some chaotic sequences are always able to increase the value of some measured algorithm-performance indexes with respect to random sequences. Moreover, it is shown that EAs can be extremely sensitive to different RNGs. Some t-tests were performed to confirm the improvements introduced by the proposed strategy.

Fractional order systems : modeling and control applications

Fractional Order Systems Fractional Order PID Controller Chaotic Fractional Order Systems Field Programmable Gate Array, Microcontroller and Field Programmable Analog Array Implementation Switched Capacitor and Integrated Circuit Design Modeling of Ionic Polymeric Metal Composite

A nonlinear model for ionic polymer metal composites as actuators

This paper introduces a comprehensive nonlinear dynamic model of motion actuators based on ionic polymer metal composites (IPMCs) working in air. Significant quantities ruling the acting properties of IPMC-based actuators are taken into account. The model is organized as follows. As a first step, the dependence of the IPMC absorbed current on the voltage applied across its thickness is taken into account; a nonlinear circuit model is proposed to describe this relationship. In a second step the transduction of the absorbed current into the IPMC mechanical reaction is modelled. The model resulting from the cascade of both the electrical and the electromechanical stages represents a novel contribution in the field of IPMCs, capable of describing the electromechanical behaviour of these materials and predicting relevant quantities in a large range of applied signals. The effect of actuator scaling is also investigated, giving interesting support to the activities involved in the design of actuating devices based on these novel materials. Evidence of the excellent agreement between the estimations obtained by using the proposed model and experimental signals is given.

Effects of mobility in a population of prisoner's dilemma players.

We address the problem of how the survival of cooperation in a social system depends on the motion of the individuals. Specifically, we study a model in which prisoners dilemma players are allowed to move in a two-dimensional plane. Our results show that cooperation can survive in such a system provided that both the temptation to defect and the velocity at which agents move are not too high. Moreover, we show that when these conditions are fulfilled, the only asymptotic state of the system is that in which all players are cooperators. Our results might have implications for the design of cooperative strategies in motion coordination and other applications including wireless networks.

Bifurcation and Chaos in Noninteger Order Cellular Neural Networks

In this paper a new class of Cellular Neural Networks (CNNs) is introduced. The peculiarity of the new CNN model consists in replacing the traditional first order cell with a noninteger order one. The introduction of fractional order cells, with a suitable choice of the coupling parameters, leads to the onset of chaos in a two-cell system of a total order of less than three. A theoretical approach, based on the interaction between equilibrium points and limit cycles, is used to discover chaotic motions in fractional CNNs.

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.

Chua's circuit can be generated by CNN cells

A new realization for the unfolded Chuas circuit is introduced. It has been derived from the connection of three simple generalized cellular neural network (CNN) cells. The main theoretical implication of this result is that the CNN cell represents the primitive for realizing high complex dynamics. The circuit implementation of the introduced system and experimental results referring to the double scroll attractor are reported. >

A Tactile Sensor for Biomedical Applications Based on IPMCs

In this paper, a first prototype of a multifunctional tactile sensor using ionic polymer metal composites (IPMCs) is proposed, designed, and tested. Two IPMC strips are used, one as an actuator and one as a sensor, both positioned in a cantilever configuration; working together they enable the system to detect the presence of a material in contact with it and to measure its stiffness. These sensing capabilities can be exploited in various biomedical applications, such as catheterism, laparoscopy and the surgical resection of tumors. Moreover, the simple structure of the proposed tactile sensor can easily be extended to devices in which a sensing tip for exploration of the surrounding environment is required. Compared with other similar tools, the one proposed works with a very low-power supply (the order of magnitude being a few volts), it needs very simple electronics, it is very lightweight and has a low cost.

A model for ionic polymer metal composites as sensors

This paper introduces a comprehensive model of sensors based on ionic polymer metal composites (IPMCs) working in air. Significant quantities ruling the sensing properties of IPMC-based sensors are taken into account and the dynamics of the sensors are modelled. A large amount of experimental evidence is given for the excellent agreement between estimations obtained using the proposed model and the observed signals. Furthermore, the effect of sensor scaling is investigated, giving interesting support to the activities involved in the design of sensing devices based on these novel materials. We observed that the need for a wet environment is not a key issue for IPMC-based sensors to work well. This fact allows us to put IPMC-based sensors in a totally different light to the corresponding actuators, showing that sensors do not suffer from the same drawbacks.

A model of ionic polymer-metal composite actuators in underwater operations

Ionic polymer metal composites (IPMCs) are active materials that exhibit a bi-directional electromechanical coupling: a voltage produces membrane bending, while by bending an IPMC membrane a voltage output is obtained. IPMCs are of increasing interest in a number of application fields. More specifically, IPMCs can work in wet environments, even in water, and this represents a valuable capability in a number of applications fields such as underwater robotics, surveillance, and biomedical applications. In this work a totally new model of an active IPMC beam, solicited by a voltage signal and immersed in water, is introduced. The model estimates the moment produced by the applied voltage. Therefore, the classical Euler–Bernoulli cantilever beam theory and the concept of hydrodynamic function are used to describe the interaction between the beam and the water. Knowledge of this interaction allows estimation of the IPMC active beam motion in water.