# Felice Andrea PellegrinoUniversity of Trieste | UNITS · Department of Engineering and Architecture

Felice Andrea Pellegrino

PhD

## About

75

Publications

8,029

Reads

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771

Citations

Citations since 2017

Introduction

Felice Andrea Pellegrino currently works at the Department of Engineering and Architecture, University of Trieste. Felice Andrea does research in Control Systems Engineering. His most recent publication is 'Model-free tuning of plants with parasitic dynamics.'

Additional affiliations

November 2006 - present

June 2000 - February 2001

## Publications

Publications (75)

In Late-Medieval panel paintings from the Tuscan area, mechanical tools called
punches
were used to impress repeated motifs on gold foils to create decorative patterns. Such patterns can be used as clues to objectively support the attribution of the paintings, as proposed by art historian Erling S. Skaug in his decades-long study on punches. We i...

Most collaborative robots (cobots) can be taught by hand guiding: essentially, by manually jogging the robot, an operator teaches some configurations to be employed as via points. Based on those via points, Cartesian end-effector trajectories such as straight lines, circular arcs or splines are then constructed. Such methods can, in principle, be e...

Artificial neural networks (ANNs) can be employed as controllers for robotic agents. Their structure is often complex, with many neurons and connections, especially when the robots have many sensors and actuators distributed across their bodies and/or when high expressive power is desirable. Pruning (removing neurons or connections) reduces the com...

Biomonitoring plays a crucial role in the assessment of air quality, as it allows to estimate the presence of pollutants, by measuring deviations from normality of the components of an ecosystem. Lichens are among the organisms most commonly used as bioindicators. The present study deals with the classification of lichen taxa from images, by means...

The growing demand for robots able to act autonomously in complex scenarios has widely accelerated the introduction of Reinforcement Learning (RL) in robots control applications. However, the trial and error intrinsic nature of RL may result in long training time on real robots and, moreover, it may lead to dangerous outcomes. While simulators are...

Estimating the wear of the single electrical parts of a home appliance without resorting to a large number of sensors is desirable for ensuring a proper level of maintenance by the manufacturers. Deep learning techniques can be effective tools for such estimation from relatively poor measurements, but their computational demands must be carefully c...

The attainment of a satisfactory operating point is one of the main problems in the tuning of particle accelerators. These are extremely complex facilities, characterized by the absence of a model that accurately describes their dynamics, and by an often persistent noise which, along with machine drifts, affects their behaviour in unpredictable way...

Deep Neural Networks (DNNs) are essential tools of modern science and technology. The current lack of explainability of their inner workings and of principled ways to tame their architectural complexity triggered a lot of research in recent years. There is hope that, by making sense of representations in their hidden layers, we could collect insigh...

The glycemia regulation is a significant challenge in the Artificial Pancreas (AP) scenario. Several control systems have been developed in the last years, many of them requiring meal announcements. Therefore, if the patients skip the meal announcement or make a mistake in the estimation of the amount of carbohydrates, the control performance will...

Optimal tuning of particle accelerators is a challenging task. Many different approaches have been proposed in the past to solve two main problems—attainment of an optimal working point and performance recovery after machine drifts. The most classical model-free techniques (e.g., Gradient Ascent or Extremum Seeking algorithms) have some intrinsic l...

Machine learning techniques have been widely applied to production processes with the aim of improving product quality, supporting decision-making, or implementing process diagnostics. These techniques proved particularly useful in the investment casting manufacturing industry, where huge variety of heterogeneous data, related to different producti...

Cavitation is a well-known phenomenon that may occur, among other turbo-machines, in centrifugal pumps and can result in severe damage of both the pump and the whole hydraulic system. There are situations in which, in principle, the cavitation could be avoided by detecting the condition of incipient cavitation, and changing slightly the working poi...

Purpose:
To objectively evaluate the image quality obtained with toric intraocular lenses (IOLs) when misaligned from the intended axis.
Setting:
University Eye Clinic and the Department of Industrial and Information Engineering, University of Trieste, Trieste, Italy.
Design:
Experimental study.
Methods:
An experimental optoelectronic test b...

We have recently considered the problem of tuning a static plant described by a differentiable input-output function, which is completely unknown, but whose Jacobian takes values in a known polytope of matrices: to drive the output to a given desired value, we have suggested an integral feedback scheme, whose convergence is ensured if the polytope...

Preservation and restoration of ancient mosaics is a crucial activity for the perpetuation of cultural heritage of many countries. Such an activity is usually based on manual procedures which are typically lengthy and costly. Digital imaging technologies have a great potential in this important application domain, from a number of points of view in...

Motivated by the aim of developing a vision-based system to assist the social interaction of blind persons, the performance of some face detectors are evaluated. The detectors are applied to manually annotated video sequences acquired by blind persons with a glass-mounted camera and a necklace-mounted one. The sequences are relevant to the specific...

The radiation generated by a seeded free-electron laser (FEL) is characterized by a high temporal coherence, which is close to the Fourier limit in the ideal case. The setup and optimization of a FEL is a non-trivial and challenging operation. This is due to the plethora of highly sensitive machine parameters and to the complex correlations between...

Given a static plant described by a differentiable input-output function, which is completely unknown, but whose Jacobian takes values in a known polytope in the matrix space, we consider the problem of tuning the output (i.e., driving the output to a desired value), by suitably choosing the input. To this aim, we assume to have at our disposal a d...

Given a static plant described by a differentiable input-output function, which is completely unknown, but whose Jacobian takes values in a known polytope in the matrix space, we consider the problem of tuning the output (i.e., driving the output to a desired value), by suitably choosing the input. To this aim, we assume to have at our disposal a d...

We propose a novel approach to the problem of inverse kinematics for possibly redundant planar manipulators. We show that, by considering the joints as point masses in a fictitious gravity field, and by adding proper constraints to take into account the length of the links, the kinematic inversion may be cast as a convex programming problem. Convex...

Given a static plant described by a differentiable input-output function, which is completely unknown, but whose Jacobian takes values in a known polytope in the matrix space, this paper considers the problem of tuning (i.e., driving to a desired value) the output, by suitably choosing the input. It is shown that, if the polytope is robustly non-si...

A methodology to plan the trajectories of robots that move in an n-dimensional Euclidean space, have to reach a target avoiding obstacles and are constrained to move in a region of the space is described. It is shown that if the positions of the obstacles are known then a Hamiltonian function can be constructed and used to define a collision-free t...

We consider the problem of tuning the output of a static plant whose model is unknown, under the only information that the input-output function is monotonic in each component or, more in general, that its Jacobian belongs to a known polytope of matrices.
As a main result, we show that, if the polytope is robustly non-singular (or has full rank, in...

We review recent computer vision techniques with reference to the specific goal of assisting the social interactions of a person affected by very severe visual impairment or by total blindness. We consider a scenario in which a sequence of images is acquired and processed by a wearable device, and we focus on the basic tasks of detecting and recogn...

A novel approach to the problem of inverse kinematics for redundant manipulators has been recently introduced: by considering the joints as point masses in a fictitious gravity field, and by adding proper constraints to take into account the length of the links, the kinematic inversion may be cast as a convex programming problem. Such a problem can...

This paper presents a continuous time solution to the problem of designing a relatively optimal control, precisely, a dynamic control which is optimal with respect to a given initial condition and is stabilizing for any other initial state. This technique provides a drastic reduction of the complexity of the controller and successfully applies to s...

The present paper deals with automatic segmentation of mosaics, whose aim is obtaining a digital representation of the mosaic where the shape of each tile is recovered. This is an important step, for instance, for preserving ancient mosaics. By using a ground-truth consisting of a set of manually annotated mosaics, we objectively compare the perfor...

We describe a methodology to plan the trajectories of a robotic manipulator moving in an n-dimensional Euclidean space. The robot has to reach the target avoiding obstacles and is constrained to move in a region of the space. We show that if the positions of the target and of the obstacles are known a priori then a Hamiltonian function can be const...

Intraocular lenses (IOLs) are widely used in cataract surgery. There is a variety of IOLs depending on lens material, optical and mechanical design. Evaluation of the visual performance obtainable with intraocular lenses is important for objective comparison between IOL models. Indeed, the visual performance of implanted lenses has a deep impact on...

The problem of detecting cell nuclei in fluorescence images may be faced by means of a segmentation step, to get the neighbourhood of candidate nuclei, followed by a binary classification step. Important for the latter step is the choice of the descriptors (features) to be extracted from the neighbourhood and used by the classifier. In the present...

The objective of this work consists in the offline approximation of possibly discontinuous model predictive control laws for nonlinear discrete-time systems, while enforcing hard constraints on state and input variables. Obtaining an offline approximation of the receding horizon control law may lead to a very significant reduction of the online com...

Motivated by applications such as drainage canal control, where the disturbance acting on a system can be predicted on the basis of weather forecast, we propose a model predictive control technique consisting in the online tuning of a Youla–Kučera parameter. Essentially, the optimal control sequence is supplied to the system by properly setting the...

We describe a methodology to plan the trajectory of a robot moving in a two-dimensional space. The robot has to reach a target avoiding obstacles. We show that if the position of the target and of the obstacles in known a priori, then a Hamiltonian function can be constructed and used to define the trajectory. We consider both the static case, name...

Support Vector Machines (SVMs) are an estab- lished tool for pattern recognition. However, their application to real-time object detection (such as detection of objects in each frame of a video stream) is limited due to the relatively high computational cost. Speed is indeed crucial in such applications. Motivated by a practical problem (hand detec...

We present new results in trajectory clustering, obtained by extending a recent methodology based on Earth Mover's Distance (EMD). The EMD can be adapted as a tool for trajectory clustering, taking advantage of an effective method for identifying the clusters' representatives by means of the p median location problem. This methodology can be used e...

In this work, the off-line approximation of state-feedback nonlinear model predictive control laws by means of smooth functions of the state is addressed. The idea is to investigate how the approximation errors affect the stability of the closed-loop system, in order to derive suitable bounds which have to be fulfilled by the approximating function...

In this work, we propose an adaptive scheme which is a counterpart of existing high gain control techniques based on control Lyapunov functions. Given a control Lyapunov function, the main idea is that of tuning the feedback gain according to a suitably-chosen Lyapunov time-derivative. The control gain is not monotonically non-decreasing as in exis...

The paper deals with the problem of positioning a manipulator in a cluttered environment while avoiding collision with obstacles. Recently a control strategy based on invariant sets has been introduced by some of the authors: it consists of covering the configuration space by means of a connected family of polyhedral regions which can be rendered c...

In this paper we consider the problem of designing a state-feedback controller that simultaneously achieves different optimality criteria defined on different input–output pairs. Precisely, if r “optimal” target transfer functions are given (as the result of local “optimal” controllers), it is shown that (under mild assumptions) there exists a uniq...

We propose an adaptive scheme which is a counterpart of existing high gain control techniques based on control Lyapunov functions. Given a control Lyapunov function, the main idea is that of tuning the feedback gain according to a suitably-chosen Lyapunov time-derivative. The control gain is not monotonically non-decreasing as in existing technique...

A relatively optimal control is a stabilizing controller that, without initialization nor feedforwarding and tracking the optimal trajectory, produces the optimal (constrained) behavior for the nominal initial condition of the plant. In a previous work, for discrete-time linear systems, we presented a linear dynamic relatively optimal control. Here...

A new microplankton imaging and analysis instrument, HAB Buoy, is described. It integrates a high-speed camera for in-flow image acquisition with automatic specimen labelling software, known as DiCANN (Dinoflagellate Categorisation by Artificial Neural Network). Some preliminary results are presented together with a rationale for its use.

A relatively optimal control is a stabilizing controller such that, if initialized at its zero state, produces the optimal (constrained) behavior for the nominal initial condition of the plant (without feedforwarding and tracking the optimal trajectory). In this paper, we prove that a relatively optimal control can be obtained under quite general c...

In this paper we show that (under some input matrix rank conditions) there exists a single compensator which achieves simultaneously the performances of r≤n (the system order) given static state feedback (local) compensators. The compensator, whose order is r(n-1), is then capable of matching the r (possibly different) optimality criteria defined f...

A relatively optimal control is a stabilizing controller that, without initialization nor feedforwarding and tracking the optimal trajectory, produces the optimal (constrained) behavior for the nominal initial condition of the plant. In a previous work, a linear dynamic relatively optimal control, for discrete-time linear systems, was presented. He...

A relatively optimal control is a stabilizing controller such that, if initialized at its zero state, produces the optimal (constrained) behavior for the nominal initial condition of the plant (without feedforwarding and tracking the optimal trajectory). In a previous work we have shown that one of such controllers is linear, dead-beat, and its ord...

The paper considers a novel technique for manipulator motion in a constrained environment due to the presence of obstacles. The basic problem is that of avoiding collisions of the manipulator with the obstacles. The main idea is to cover the free space (i.e. the points of the configurations space in which no collisions are possible) by a connected...

Constraint fulfillment and optimality are two important aspects of most real–world con- trol problems. Constraints typically arise from safety, physical or performance limita- tions and must be taken into account in the design stage, especially in those cases when constraint violation may have serious consequences. As a matter of fact, the control...

We propose a new technique for controlling manipulators in constrained environments. Based on recent developments on constrained control theory, our approach basically consists in covering the admissible region of the configuration space by partially overlapping convex polyhedra arbitrarily fixed and forming a connected family. Each of these polyhe...

This paper describes a vision-based system that is able to automatically recognize deformable objects, to estimate their pose, and to select suitable picking points. A hierarchical self-organized neural network is used to segment color images based on texture information. A morphological analysis allows the recognition of the objects and the pickin...

Often an image g(x,y) is regularized and even restored by minimizing the Mumford-Shah functional. Properties of the regularized image u(x,y) depends critically on the numerical value of the two parameters alpha and gamma controlling smoothness and fidelity. When alpha and gamma are constant over the image, small details are lost when an extensive f...

The present manuscript aims at solving four problems of edge detection: the simultaneous detection of all step edges from a fine to a coarse scale; the detection of thin bars with a width of very few pixels; the detection of trihedral junctions; the development of an algorithm with image-independent parameters. The proposed solution of these proble...

Motivated by the fact that determining a feedback solution for the optimal control problem under constraints is a hard task we introduce the concept of relative optimality, roughly optimality for a specific (nominal) plant initial condition. We consider a generic discrete-time finite-horizon constrained optimal control problem for linear systems, a...

Motivated by the fact that determining a feedback solution for the optimal control problem under constraints is a hard task we introduce the concept of relative optimality, roughly optimality for a specific (nominal) plant initial condition. We consider a generic discrete-time finite-horizon constrained optimal control problem for linear systems, a...

Solving a continuous-time optimal control problem under state and control constraints is known to be a very hard task. In this note, we propose a suboptimal solution based on the Euler auxiliary system (EAS). We show that we can determine a continuous-time stabilizing control whose cost not only converges to the optimal as the EAS time parameter va...

The present manuscript aims to address and possibly solve three classical problems of edge detection: i—the detection of all
step edges from a fine to a coarse scale; ii—the detection of thin bars, i.e. of roof edges; iii—the detection of corners
and trihedral junctions. The proposed solution of these problems combines an extensive spatial filterin...