1,720,976 research outputs found
The pseudo-kufic ornament and the problem o cross-cultural relationships between Byzantium and Islam
No full textThe aim of the paper is to analyze pseudo-kufic ornament in Byzantine art and the reception of the topic in Byzantine Studies. The pseudo-kufic ornamental motifs seem to occupy a middle position between the purely formal
abstractness and freedom of arabesque and the purely symbolic form of a semantic and referential mean, borrowed from an alien language, moreover. This double nature (that is also a double negation) makes of pseudo-kufic decoration a very interesting liminal object, an object of “transition”, as it were, at the crossroad of different domains. Starting from an assessment of the theoretical questions raised by
the aesthetic peculiarities of this kind of ornament, we consider, from this specific point of view, the problem of the cross-cultural impact of Islamic and islamicizing formal repertory on Byzantine ornament, focusing in particular on a hitherto unpublished illuminated manuscript dated to the 10th century and held by the Marciana Library in Venice
Linear unknown input-state observer for nonlinear dynamic models
Full text linkThis paper proposes an unknown input observer for nonlinear systems with input decoupling via system invertibility. Starting from a suitable reformulation of the model of a generic nonlinear system, obtained by merging all system uncertainties with respect to an appropriate nominal linear model into a disturbance vector, the proposed observer can asymptotically copy both the system state and unknown inputs, even in the presence of measurement noise. Formal proof of the estimate convergence is demonstrated analytically. A comparison of the proposed method with existing solutions is shown in simulation, and the method’s effectiveness in real-world scenarios is demonstrated by experimental results on a soft articulated robot
Racecar Longitudinal Control in Unknown and Highly-Varying Driving Conditions
Full text linkThis paper focuses on racecar longitudinal control with highly-varying driving conditions. The main factors affecting the dynamic behavior of a vehicle, including aerodynamic forces, wheel rolling resistance, traction force resulting from changing tire-road interaction as well as the occurrence of sudden wind gusts or the presence of persistent winds, are considered and assumed to have unknown models. By exploiting the theory on delayed input-state observers and using measurement data about the vehicle and wheel speeds, a dynamic filter that allows the online reconstruction of the above-mentioned unknown time-varying quantities is derived. Moreover, by exploiting the notion of effective tire radius, a reduced-degree-of-freedom model for the longitudinal vehicle dynamics is obtained, which is independent of the traction force and that enables, when used with the observer filter described above, an accurate speed control compensating for the resistance forces. One appealing feature of the proposed estimation and control method is that it requires no model information about such forces, for which, at the state-of-the-art, only heuristic approximations to be a-priori identified are available. Its effectiveness is shown via the simulation of scenarios where the car is required to execute aggressive maneuvers and the asphalt road surface abruptly changes from dry to wet, snowy, and icy. The evaluation also reveals that the proposed estimation technique outperforms standard solutions even in the presence of measurement noise
Mosaici e sectilia medievali nelle illustrazioni di Andrea Terzi: pavimenti e arredi cosmateschi delle chiese di Roma
No full textMosaici e sectilia medievali nelle illustrazioni di Andrea Terzi (1842-1918): i monumenti della Sicilia normanna
No full text
Lateral Wind Estimation and Backstepping Compensation for Safer Self-Driving Racecars
Full text linkThis paper addresses the lateral wind gust estimation and compensation problem for racecar models. A wind-sensorless solution, i.e. a solution not using direct wind measures, is proposed. More precisely, by modeling the wind disturbance as a fully unknown input signal, an input-state observer is derived using only information about the vehicle’s longitudinal speed and lateral pose relative to the road. The observer is characterized by a simple structure, explicit closed-form, direct implementability on a micro-controller, and dead-beat property, i.e. it ensures the convergence of the estimation error in a finite time. Moreover, leveraging on the reconstructed wind data, a backstepping wind-compensation controller is also proposed, allowing asymptotic tracking of a path with desired curvature and providing the end-user with a free control parameter specifying the desired tracking speed. Formal proofs of the estimation error and tracking error convergence are given. Performance evaluation of the proposed solution is obtained in simulation by closing in the loop the full nonlinear model of a real racecar, the Robocar system, with the proposed estimation and control method. Both the estimator and the controller are shown to outperform existing solutions, even in the presence of noisy measurements
Robust Time-delayed Control of Nonlinear Discrete-time Systems
No full textWith the mass production of robotic systems and an
emerging new generation of collaborative robots, the requirements
are increasing for robust and efficient control strategies, that
can successfully deal with disturbances. This paper proposes
a robust and time-delayed control formulated for discrete-time
systems, leaning on the theory of Luenberger observers and
disturbance-observer-based strategies. The bounded convergence
both of the proposed estimator and the tracking error to are
proved analytically. Validation is performed in the simulation on
a single-link robot manipulator in the presence of structural and
significant parametric uncertainty
St. Sophia Museum Project 2007: The marble sculptures of St. John Studius (Imrahor Camii)
No full textRobust Discrete-Time Lateral Control of Racecars by Unknown Input Observers
Full text linkThis brief addresses the robust lateral control problem for self-driving racecars. It proposes a discrete-time estimation and control solution consisting of a delayed unknown input-state observer (UIO) and a robust tracking controller. Based on a nominal vehicle model, describing its motion with respect to a generic desired trajectory and requiring no information about the surrounding environment, the observer reconstructs the total force disturbance signal, resulting from imperfect knowledge of the time-varying tire-road interface characteristics, presence of other vehicles nearby, wind gusts, and other model uncertainty. Then, the controller actively compensates the estimated force and asymptotically steers the tracking error to zero. The brief also presents a closed-loop stability proof of the method, ensuring perfect asymptotic estimation and tracking by the controlled vehicle. The proposed solution advantageously needs no a-priori information about the total disturbance boundedness, additional variables to model uncertainty, or observer parameters to be tuned. Its effectiveness and superiority to existing methods are studied in theory and shown in simulations where a full racecar model, based on the vehicle dynamics blockset, is required to track aggressive maneuvers. Through a faster and more accurate disturbance estimation, the solution robustly ensures better dynamic responses even with measurement noise
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