323,414 research outputs found
A global adaptive learning control for robotic manipulators
No full textThis paper addresses the problem of designing a global adaptive learning control for robotic manipulators with revolute joints and unknown dynamics. The reference signals to be tracked are assumed to be smooth and periodic with known period. By developing in Fourier series expansion the
input reference signals of every joint, an adaptive learning PD control is designed which ’learns’ the input reference signals by
identifying their Fourier coefficients: global asymptotic tracking and local exponential tracking of both the input and the output reference signals is obtained when the Fourier series expansion of each input reference signal is finite, while arbitrary small tracking errors are achieved otherwise. The resulting control is not model based and depends only on the period of the reference signals and on some constant bounds on the robot dynamics
Global adaptive learning control of robotic manipulators by output error feedback
No full textThis paper addresses the problem of designing a global, output error feedback based, adaptive learning control for robotic manipulators with revolute joints and uncertain dynamics. The reference signals to be tracked are assumed to be smooth and periodic with known period. By developing in Fourier series expansion the input reference signals of every joint, an adaptive, output error feedback, learning control is designed which 'learns' the input reference signals by identifying their Fourier coefficients: global asymptotic and local exponential stability of the tracking error dynamics are obtained when the Fourier series expansion of each Input reference signal is finite, while arbitrary small tracking errors are achieved otherwise. The resulting control is not model based and depends only on the period of the reference signals and on some constant bounds on the robot dynamics. © 2006 IEEE
Etna CO2 Soil Flux during 2002-2010 (ECSF2002_2010)
No full textThe ETNAGAS network comprises 19 monitoring stations distributed across the flanks of Mount Etna, specifically designed for the continuous observation of soil-emitted carbon dioxide (CO₂). Each station is equipped with infrared (IR) sensors for the precise measurement of CO₂ concentrations, along with meteorological sensors that record key environmental parameters including air temperature, atmospheric pressure, wind speed and direction, and precipitation. These data enable the estimation of CO₂ soil fluxes through the application of the method proposed by Gurrieri and Valenza (1988) (see Methods for details). The ETNAGAS network represents a high-resolution geochemical surveillance system and constitutes an integral component of the national framework for monitoring volcanic gas emissions. Its primary objective is to contribute to the assessment of the volcanic activity state of Mount Etna through systematic and spatially distributed measurements of gaseous emissions.The monitoring stations of the ETNAGAS network were entirely developed by the Istituto Nazionale di Geofisica e Vulcanologia (INGV), Palermo section. These stations are capable of continuously measuring several environmental and geochemical parameters, including soil CO₂ concentration, atmospheric temperature, pressure, relative humidity, rainfall, wind speed, and wind direction. Data are acquired at hourly intervals and automatically transmitted to the monitoring center at INGV-Palermo. It should be noted that not all stations are equipped with the full suite of meteorological sensors.
CO₂ fluxes from the soil can be derived from the recorded data using the dynamic (or dilution) method described by Gurrieri and Valenza (1988). This method is based on measuring the CO₂ content in a mixture of soil gas and atmospheric air (Cd), obtained using a probe inserted approximately 50 cm into the ground. Soil gases enter the probe through its base and are mixed with ambient air; this mixture is then pumped into an infrared (IR) spectrophotometer, which measures the CO₂ concentration.
According to Gurrieri and Valenza, the measured diluted concentration (Cd) is empirically related to the actual soil CO₂ flux (ϕCO₂) through a relationship established under laboratory conditions, across a range of gas permeabilities (0.36–123 mm²) and pumping flow rates (0.4–4.0 L/min) [Camarda et al., 2006a, 2006b].
REFERENCE
• Camarda, M., S. Gurrieri, and M. Valenza (2006a), CO2 flux measurements in volcanic areas using the dynamic concentration method: Influence of soil permeability, J. Geophys. Res., 111, B05202, doi:10.1029/2005JB003898. Camarda, M., S. Gurrieri, and M. Valenza (2006b), In situ permeability measurements based on a radial gas advection model: Relationships between soil permeability and diffuse CO2 degassing in volcanic areas, Pure Appl. Geophys., 163(4), 897–914, doi:10.1007/s00024-006-0045-y.
• Gurrieri, S., and M. Valenza (1988), Gas transport in natural porous mediums: A method for measuring CO2 flows from the ground in volcanic and geothermal areas, Rend. Soc. Ital. Mineral. Petrol., 43, 1151–1158.
• Gurrieri, S., M. Liuzzo, and G. Giudice, (2008), Continuous monitoring of soil CO2 flux on Mt. Etna: The 2004–2005 eruption and the role of regional tectonics and volcano tectonics, J. Geophys. Res., 113, B09206, doi:10.1029/2007JB005003, 2008.
• Liuzzo M., Gurrieri S., Giudice G. & Giuffrida G. (2013) - Ten years of soil CO2 continuous monitoring on Mt. Etna: Exploring the relationship between processes of soil degassing and volcanic activity. Geochem. Geophys. Geosyst., 14, 2886-2899. https://doi. org/10.1002/ggge.2019
The components of microbiological risk analysis
No full textThe paper describes the process of risk analysis in a food safety perspective. The steps of risk analysis defined as a process consisting of three interconnected components (risk assessment, risk management, and risk communication) are analysed. The different components of the risk assessment, risk management and risk communication are further described
Global adaptive learning control of robotic manipulators by output error feedback
No full textThis paper addresses the problem of designing a global, output error feedback based, adaptive learning control for robotic manipulators with revolute joints and uncertain dynamics. The reference signals to be tracked are assumed to be smooth and periodic with known period. By developing in Fourier series expansion the input reference signals of every joint, an adaptive, output error feedback, learning control is designed, which ‘learns’ the input reference signals by identifying their Fourier coefficients: global asymptotic and local exponential stability of the tracking error dynamics are obtained when the Fourier series expansion of each input reference signal is finite, while arbitrary small tracking errors are achieved otherwise. The resulting control is not model based and depends only on the period of the reference signals and on some constant bounds on the robot dynamics
A global adaptive learning control for robotic manipulators
No full textThis paper addresses the problem of designing a global adaptive learning control for robotic manipulators with revolute joints and uncertain dynamics. The reference signals to be tracked are assumed to be smooth and periodic with known period. By developing in Fourier series expansion the input reference signals of every joint, an adaptive learning PD control is designed which ‘learns’ the input reference signals by identifying their Fourier coefficients: global asymptotic and local exponential stability of the tracking error dynamics are obtained when the Fourier series expansion of each input reference signal is finite, while arbitrary small tracking errors are achieved otherwise. The resulting control is not model based and depends only on the period of the reference signals and on some constant bounds on the robot dynamics
Understanding the Accelerating Effect of - Caprolactam on the Formation of Urethane Linkages
No full textThe accelerating role of -caprolactam on the formation of urethane linkages is studied in
the case of the reaction between toluene 2,4-diisocyanate and n-propanol in carbon tetrachloride at room
temperature. FT-IR spectroscopy is exploited to follow the consumption of the isocyanate groups. The
comparison between the rate of the reactions carried out in the presence and absence of a catalytic amount
of -caprolactam shows its accelerating effect. The acylurea-like derivative 1-methyl-2,4-[(2-oxoazepane-
1-carbonyl)amino]benzene has been prepared and identified as the real catalytic species formed in situ
as a result of the reaction between toluene 2,4-diisocyanate and -caprolactam. A kinetic model is proposed
to analyze the experimental data, and B3LYP/6-31+G* calculations are exploited to investigate the
structure of 1-methyl-2,4-[(2-oxoazepane-1-carbonyl)amino]benzene and clarify the structural features
leading the catalytic activity
Adaptive learning control of nonlinear systems with applications to robot manipulators
No full textThe goal of the proposed work is the design of adaptive learning controls for nonlinear systems with output dependent nonlinearities and for robot manipulators. At first, we address the problem of designing an output error feedback control for single input, single output nonlinear systems with uncertain, smooth, output dependent nonlinearities whose local Lipschitz constants are known. The considered systems are required to be observable, minimum phase with known relative degree and known high frequency gain sign: linear systems are included. The reference output signal is assumed to be smooth and periodic with known period. By developing in Fourier series expansion a suitable periodic input reference signal, an output error feedback adaptive learning control is designed which 'learns' the input reference signal by identifying its Fourier coefficients: bounded closed loop signals and exponential tracking of both input and output reference signals are obtained when the Fourier series expansion is finite, while arbitrary small tracking errors are exponentially achieved otherwise. The resulting control is not model based, is independent of the system order and depends only on the relative degree, the reference signal period and the high frequency gain sign. Then, the properties of the designed adaptive learning controllers are studied with reference to robotic manipulators. Global adaptive learning controls are designed for robotic manipulators with revolute joints and uncertain dynamics: state feedback and output feedback tracking controllers are designed. The reference signals to be tracked are assumed to be smooth and either constant or periodic with known period. Two adaptive learning controllers are designed which 'learn' the torque reference signals of each manipulator's joint by identifying their Fourier coefficients: global asymptotic and local exponential tracking of the input and output reference signals is obtained when the Fourier series expansion of each input reference signal is finite, while arbitrary small steady state tracking errors are achieved otherwise. The resulting controls are not model based and depend only on the period of the reference signals and on some constant bounds on the robot dynamics.
L’obiettivo di questa tesi è quello di progettare controllori adattativi ad apprendimento per sistemi non lineari, con non linearità dipendenti dall’uscita, e per manipolatori robotici. Inizialmente è stato progettato un controllore, in retroazione dall’errore di uscita, per sistemi non lineari (con non linearità regolari, incerte, dipendenti solo dal segnale di uscita e le cui costanti locali di Lipschitz siano note). I sistemi dinamici presi in considerazione devono essere osservabili, a fase minima, di grado relativo noto e con guadagno ad alta frequenza noto: i sistemi lineari sono compresi. Il segnale di riferimento di uscita deve essere regolare e periodico, con periodo noto. Sviluppando in serie di Fourier un opportuno segnale di riferimento periodico di ingresso, viene progettato un controllore adattativo ad apprendimento, in retroazione dall’errore di uscita, che apprende il riferimento di ingresso identificando i suoi coefficienti di Fourier. Quando l’espansione in serie di Fourier è finita, il controllore progettato garantisce che i segnali del sistema a ciclo chiuso siano limitati oltre ad un inseguimento esponenziale dei riferimenti di ingresso e di uscita. Invece quando l’espansione in serie di Fourier è infinita, vengono ottenuti errori di inseguimento asintotici arbitrariamente piccoli. Il controllore risultante non è basato sul modello, è indipendente dall’ordine del sistema e dipende solo dal grado relativo del sistema da controllare, dal periodo del segnale di riferimento e dal segno del guadagno ad alta frequenza. Le proprietà dei controlli adattativi ad apprendimento sono quindi studiate in riferimento ai manipolatori robotici, con giunti rotazionali e dinamica incerta, per i quali sono stati progettati un controllore in retroazione dallo stato ed uno in retroazione dall’errore di uscita. I segnali di riferimento da inseguire devono essere regolari e periodici (con periodo noto) oppure costanti. I due controllori, che sono stati progettati per i manipolatori robotica, apprendono la coppia di riferimento di ciascun giunto del manipolatore tramite l’identificazione dei loro coefficienti di Fourier. Quando l’espansione in serie di Fourier è finita, i due controllori garantiscono l’inseguimento globalmente asintotico e localmente esponenziale dei riferimenti di ingresso ed uscita. Quando invece l’espansione in serie di Fourier è infinita, vengono garantiti errori di inseguimento asintotici arbitrariamente limitati. Anche nel caso dei manipolatori robotici i controllori progettati non sono basati sul modello del sistema da controllare e dipendono solamente dal periodo del segnale di riferimento e da alcuni limiti costanti sulla dinamica del manipolatore robotico da controllare
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