188 research outputs found
A Unified Dissertation on Bearing Rigidity Theory
This work focuses on the bearing rigidity theory, namely the branch of
knowledge investigating the structural properties necessary for multi-element
systems to preserve the inter-units bearings when exposed to deformations. The
original contributions are twofold. The first one consists in the definition of
a general framework for the statement of the principal definitions and results
that are then particularized by evaluating the most studied metric spaces,
providing a complete overview of the existing literature about the bearing
rigidity theory. The second one rests on the determination of a necessary and
sufficient condition guaranteeing the rigidity properties of a given
multi-element system, independently of its metric space
On the estimation of atmospheric turbulence layers for AO systems
In current and next generation of ground telescopes, Adaptive Optics (AO) are employed to overcome the
detrimental effects induced by the presence of atmospheric
turbulence, that strongly affects the quality of data transmission and therefore limits the actual resolution of the overall system.
The analysis as well as the prediction of the turbulent phase
affecting the light wavefront is therefore of paramount impor-
tance to guarantee the effective performance of the AO solution.
In this work, a layered model of turbulence is proposed, based on the definition of a Markov-Random-Field whose parameters are determined according to the turbulence statistics. The problem of turbulence estimation is formalized within the stochastic framework and conditions for the identifiability of the turbulence structure (numbers of layers, energies and velocities) are stated. Finally, an algorithm to allow the layer detection and characterization from measurements is designed. Numerical simulations are used to assess the proposed procedure and validate the results, confirming the validity of the approach and the accuracy of the detection
Optimal Time-Invariant Distributed Formation Tracking for Second-Order Multi-Agent Systems
This paper addresses the optimal time-invariant formation tracking problem
with the aim of providing a distributed solution for multi-agent systems with
second-order integrator dynamics. In the literature, most of the results
related to multi-agent formation tracking do not consider energy issues while
investigating distributed feedback control laws. In order to account for this
crucial design aspect, we contribute by formalizing and proposing a solution to
an optimization problem that encapsulates trajectory tracking, distance-based
formation control, and input energy minimization, through a specific and key
choice of potential functions in the optimization cost. To this end, we show
how to compute the inverse dynamics in a centralized fashion by means of the
Projector-Operator-based Newton's method for Trajectory Optimization (PRONTO)
and, more importantly, we exploit such an offline solution as a general
reference to devise a novel online distributed control law. Finally, numerical
examples involving a cubic formation following a straight path in the 3D space
are provided to validate the proposed control strategies.Comment: 28 pages, 2 figures, submitted to the European Journal of Control on
June 23rd, 2023 (version 1
Quaternion-based non-singular terminal sliding mode control for a satellite-mounted space manipulator
In this paper, a robust control solution for a satellite equipped with a
robotic manipulator is presented. First, the dynamic model of the system is
derived based on quaternions to describe the evolution of the attitude of the
base satellite. Then, a non-singular terminal sliding mode controller that
employs quaternions for attitude control, is proposed for concurrently handling
all the degrees of freedom of the space manipulator. Moreover, an additional
adaptive term is embedded in the controller to estimate the upper bounds of
disturbances and uncertainties. The result is a resilient solution able to
withstand unmodelled dynamics and interactions. Lyapunov theory is used to
prove the stability of the controller and numerical simulations allow assessing
performance and fuel efficiency
Newton-Raphson Consensus for Distributed Convex Optimization
We address the problem of distributed uncon- strained convex optimization
under separability assumptions, i.e., the framework where each agent of a
network is endowed with a local private multidimensional convex cost, is
subject to communication constraints, and wants to collaborate to compute the
minimizer of the sum of the local costs. We propose a design methodology that
combines average consensus algorithms and separation of time-scales ideas. This
strategy is proved, under suitable hypotheses, to be globally convergent to the
true minimizer. Intuitively, the procedure lets the agents distributedly
compute and sequentially update an approximated Newton- Raphson direction by
means of suitable average consensus ratios. We show with numerical simulations
that the speed of convergence of this strategy is comparable with alternative
optimization strategies such as the Alternating Direction Method of
Multipliers. Finally, we propose some alternative strategies which trade-off
communication and computational requirements with convergence speed.Comment: 18 pages, preprint with proof
A Proximal Point Approach for Distributed System State Estimation
System state estimation constitutes a key problem in several applications
involving multi-agent system architectures. This rests upon the estimation of
the state of each agent in the group, which is supposed to access only relative
measurements w.r.t. some neighbors state. Exploiting the standard least-squares
paradigm, the system state estimation task is faced in this work by deriving a
distributed Proximal Point-based iterative scheme. This solution entails the
emergence of interesting connections between the structural properties of the
stochastic matrices describing the system dynamics and the convergence behavior
toward the optimal estimate. A deep analysis of such relations is provided,
jointly with a further discussion on the penalty parameter that characterizes
the Proximal Point approach.Comment: 6 pages, 2 figures, 1 table, manuscript n 3555, \c{opyright} 2020 the
authors. This work has been accepted to IFAC for publication under a Creative
Commons Licence CC-BY-NC-N
An Active-Sensing Approach for Bearing-based Target Localization
Characterized by a cross-disciplinary nature, the bearing-based target
localization task involves estimating the position of an entity of interest by
a group of agents capable of collecting noisy bearing measurements. In this
work, this problem is tackled by resting both on the weighted least square
estimation approach and on the active-sensing control paradigm. Indeed, we
propose an iterative algorithm that provides an estimate of the target position
under the assumption of Gaussian noise distribution, which can be considered
valid when more specific information is missing. Then, we present a seeker
agents control law that aims at minimizing the localization uncertainty by
optimizing the covariance matrix associated with the estimated target position.
The validity of the designed bearing-based target localization solution is
confirmed by the results of an extensive Monte Carlo simulation campaign
Adaptive Consensus-based Regulation of Open-Channel Networks
This paper deals with water management over open-channel networks subject to
water height imbalance. Specifically, it is devised a fully distributed
adaptive consensus-based algorithm within the discrete-time domain capable of
(i) providing a suitable tracking reference that stabilizes the water
increments over the underlying network at a common level; (ii) coping with
general flow constraints related to each channel of the considered system. This
iterative procedure is derived by solving a guidance problem that guarantees to
steer the regulated network - represented as a closed-loop system - while
satisfying requirements (i) and (ii), provided that a suitable design for the
local feedback law controlling each channel flow is already available. The
proposed solution converges exponentially fast towards the average consensus
without violating the imposed constraints over time. In addition, numerical
results are reported to support the theoretical findings, and the performance
of the developed algorithm is discussed in the context of a realistic scenario.Comment: 13 pages, 5 figures, submitted to IEEE Access (version 1
- …