paolo arena - Academia.edu (original) (raw)

Papers by paolo arena

IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, 2001

Robotics

In this paper, the locomotion and steering control of a simulated Mini Cheetah quadruped robot wa... more In this paper, the locomotion and steering control of a simulated Mini Cheetah quadruped robot was investigated in the presence of terrain characterised by low friction. Low-level locomotion and steering control were implemented via a central pattern generator approach, whereas high-level steering control manoeuvres were implemented by comparing a neural network and a linear model predictive controller in a dynamic simulation environment. A data-driven approach was adopted to identify the robot model using both a linear transfer function and a shallow artificial neural network. The results demonstrate that, whereas the linear approach showed good performance in high-friction terrain, in the presence of slippery conditions, the application of a neural network predictive controller improved trajectory accuracy and preserved robot safety with different steering manoeuvres. A comparative analysis was carried out using several performance indices.

Energies

Considering the importance of lithium-ion (Li-ion) batteries and the attention that the study of ... more Considering the importance of lithium-ion (Li-ion) batteries and the attention that the study of their degradation deserves, this work provides a review of the most important battery state of health (SOH) estimation methods. The different approaches proposed in the literature were analyzed, highlighting theoretical aspects, strengths, weaknesses and performance indices. In particular, three main categories were identified: experimental methods that include electrochemical impedance spectroscopy (EIS) and incremental capacity analysis (ICA), model-based methods that exploit equivalent electric circuit models (ECMs) and aging models (AMs) and, finally, data-driven approaches ranging from neural networks (NNs) to support vector regression (SVR). This work aims to depict a complete picture of the available techniques for SOH estimation, comparing the results obtained for different engineering applications.

2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob), 2018

SpringerBriefs in Applied Sciences and Technology, 2018

1996 8th European Signal Processing Conference (EUSIPCO 1996), 1996

In this paper a novel approach, based on a neural network structure, is introduced in order to fa... more In this paper a novel approach, based on a neural network structure, is introduced in order to face with the problem of pollutant estimation in an industrial area. In particular a short-term prediction (six hours ahead) of the O3 pollutant mean value has been performed. The results obtained show the capability of such structures to model complex chemical reactions heavily dependent on the meteorological conditions and on the typical geographical characteristics.

Frontiers in Physics, 2021

In this contribution, the main guidelines that, in the opinion of the authors, will address bioin... more In this contribution, the main guidelines that, in the opinion of the authors, will address bioinspired technologies in the next future are discussed. The topics are related to some specific subjects. The presented perspectives could be useful to remark how bioinspired technologies can be applied to solve every day problems in a low cost and sustainable way. Moreover, all the considerations reported hallmark the need of changing the paradigm to design innovative bionspired systems. Efficient and alternative bioinspired systems cannot be designed by only looking at macroscopic scale as observed in nature. The efforts of this paper are oriented towards providing a wide perspective on bioinspired technologies as complex systems where nonlinear phenomena are fundamental elements.

Journal of Instrumentation, 2019

56th International Astronautical Congress of the International Astronautical Federation, the International Academy of Astronautics, and the International Institute of Space Law, 2005

Fusion Science and Technology, 2010

International Journal of Advanced Robotic Systems, 2015

Learning capabilities, often guided by competition/cooperation, play a fundamental and ubiquitous... more Learning capabilities, often guided by competition/cooperation, play a fundamental and ubiquitous role in living beings. Moreover, several behaviours, such as feeding and courtship, involve environmental exploration and exploitation, including local competition, and lead to a global benefit for the colony. This can be considered as a form of global cooperation, even if the individual agent is not aware of the overall effect. This paper aims to demonstrate that identical biorobots, endowed with simple neural controllers, can evolve diversified behaviours and roles when competing for the same resources in the same arena. These behaviours also produce a benefit in terms of time and energy spent by the whole group. The robots are tasked with a classical foraging task structured through the cyclic activation of resources. The result is that each individual robot, while competing to reach the maximum number of available targets, tends to prefer a specific sequence of subtasks. This indire...

CISM International Centre for Mechanical Sciences, 2008

Nonlinear biomedical physics, Jan 15, 2011

Recent studies on the medical treatment of Parkinson's disease (PD) led to the introduction o... more Recent studies on the medical treatment of Parkinson's disease (PD) led to the introduction of the so called Deep Brain Stimulation (DBS) technique. This particular therapy allows to contrast actively the pathological activity of various Deep Brain structures, responsible for the well known PD symptoms. This technique, frequently joined to dopaminergic drugs administration, replaces the surgical interventions implemented to contrast the activity of specific brain nuclei, called Basal Ganglia (BG). This clinical protocol gave the possibility to analyse and inspect signals measured from the electrodes implanted into the deep brain regions. The analysis of these signals led to the possibility to study the PD as a specific case of dynamical synchronization in biological neural networks, with the advantage to apply the theoretical analysis developed in such scientific field to find efficient treatments to face with this important disease. Experimental results in fact show that the PD...

Disaster Management and Human Health Risk, 2009

Proceedings of IEEE International Symposium on Circuits and Systems - ISCAS '94

IEEE International Symposium on Industrial Electronics, 2010

The 2010 International Joint Conference on Neural Networks (IJCNN), 2010

Nuclear Fusion, 2008

Disruptions remain one of the most hazardous events in the operation of a tokamak device, since t... more Disruptions remain one of the most hazardous events in the operation of a tokamak device, since they can cause damage to the vacuum vessel and surrounding structures. Their potential danger increases with the plasma volume and energy content and therefore they will constitute an even more serious issue for the next generation of machines. For these reasons, in the recent years a lot of attention has been devoted to devise predictors, capable of foreseeing the imminence of a disruption sufficiently in advance, to allow time for undertaking remedial actions. In this paper, the results of applying fuzzy logic and classification and regression trees (CART) to the problem of predicting disruptions at JET are reported. The conceptual tools of fuzzy logic, in addition to being well suited to accommodate the opinion of experts even if not formulated in mathematical but linguistic terms, are also fully transparent, since their governing rules are human defined. They can therefore help not on...