643 research outputs found
An improved lion strategy for the lion and man problem
In this paper, a novel lion strategy for David Gale's lion and man problem is
proposed. The devised approach enhances a popular strategy proposed by Sgall,
which relies on the computation of a suitable "center". The key idea of the new
strategy is to update the center at each move, instead of computing it once and
for all at the beginning of the game. Convergence of the proposed lion strategy
is proven and an upper bound on the game length is derived, which dominates the
existing bounds.Comment: Preprint submitted to IEEE Control Systems Letter
Distributed interpolatory algorithms for set membership estimation
This work addresses the distributed estimation problem in a set membership
framework. The agents of a network collect measurements which are affected by
bounded errors, thus implying that the unknown parameters to be estimated
belong to a suitable feasible set. Two distributed algorithms are considered,
based on projections of the estimate of each agent onto its local feasible set.
The main contribution of the paper is to show that such algorithms are
asymptotic interpolatory estimators, i.e. they converge to an element of the
global feasible set, under the assumption that the feasible set associated to
each measurement is convex. The proposed techniques are demonstrated on a
distributed linear regression estimation problem
A Distributed Asynchronous Method of Multipliers for Constrained Nonconvex Optimization
This paper presents a fully asynchronous and distributed approach for
tackling optimization problems in which both the objective function and the
constraints may be nonconvex. In the considered network setting each node is
active upon triggering of a local timer and has access only to a portion of the
objective function and to a subset of the constraints. In the proposed
technique, based on the method of multipliers, each node performs, when it
wakes up, either a descent step on a local augmented Lagrangian or an ascent
step on the local multiplier vector. Nodes realize when to switch from the
descent step to the ascent one through an asynchronous distributed logic-AND,
which detects when all the nodes have reached a predefined tolerance in the
minimization of the augmented Lagrangian. It is shown that the resulting
distributed algorithm is equivalent to a block coordinate descent for the
minimization of the global augmented Lagrangian. This allows one to extend the
properties of the centralized method of multipliers to the considered
distributed framework. Two application examples are presented to validate the
proposed approach: a distributed source localization problem and the parameter
estimation of a neural network.Comment: arXiv admin note: substantial text overlap with arXiv:1803.0648
Exploiting structure in piecewise affine identification of LFT systems
Identification of interconnected systems is a challenging problem in which it is crucial to exploit the available knowledge about the interconnection structure. In this paper, identification of discrete-time nonlinear systems composed by interconnected linear
and nonlinear systems, is addressed. An iterative identification procedure is proposed, which alternates the estimation of the linear and the nonlinear components. Standard identification techniques are applied to the linear subsystem, whereas recently developed piecewise affine (PWA) identification techniques are employed for modelling the nonlinearity. A numerical
example analyzes the benefits of the proposed structure-exploiting identification algorithm compared to applying black-box PWA identification techniques to the overall system
Medical Waste Regulation: Recommendations for Cleaning Up the Mess
In many applications, design or analysis is performed over a finite frequency range of interest. The importance of the H2/robust H2 norm highlights the necessity of computing this norm accordingly. This paper provides different methods for computing upper bounds on the robust finite-frequency H2 norm for systems with structured uncertainties. An application of the robust finite-frequency H2 norm for a comfort analysis problem of an aero-elastic model of an aircraft is also presented
MARS: An Educational Environment for Multiagent Robot Simulations
Undergraduate robotics students often find it difficult to design and validate control algorithms for teams of mobile robots. This is mainly due to two reasons. First, very rarely educational laboratories are equipped with large teams of robots, which are usually expensive, bulky and difficult to manage and maintain. Second, robotics simulators often require student to spend much time to learn their use and functionalities.
For this purpose, a simulator of multi-agent mobile robots named MARS has been developed within the Matlab environment, with the aim of facilitating students to simulate a wide variety of control algorithms in an easy way and without spending time for understanding a new language. Through this facility, the user is able to simulate multi-robot teams performing different tasks, from cooperative to competitive ones, by using both centralized and distributed controllers. Virtual sensors are provided to simulate real devices. A graphical user interface allows students to monitor the robots behaviour through an online animation
A novel bio-inspired microstructure for progressive compressive failure in multidirectional composite laminates
n this study we take inspiration from biological materials to design a modified microstructure for laminated multidirectional (MD) carbon fiber reinforced polymers (CFRP), with the objective of mitigating their compressive failure behavior. We introduce soft inclusions in the form of thin longitudinal strips of foam in 0° load bearing layers, aiming at arresting kinkband propagation. We conceived a bespoke stacking sequence and developed a tailored procedure for manufacturing the microstructure. We then performed in-situ tests on small scale notched specimens from a baseline laminate and a modified one. Results are presented and discussed
Periodic Model Predictive Control for Tracking Halo Orbits in the Elliptic Restricted Three-Body Problem
A periodic model predictive control (MPC) scheme is proposed for tracking halo orbits. The problem is formulated and solved in the elliptic restricted three-body problem (ER3BP) setting. The reference trajectory to be tracked is designed by using eccentricity continuation techniques. The MPC design exploits the periodicity of the tracking model and guarantees exponential stability of the linearized closed-loop system, through a suitable choice of the terminal set and weight matrices. A sum-of-norms cost function is adopted to promote fuel saving. The proposed control scheme is validated on two simulated missions in the Earth-Moon system, which, respectively, involve station keeping on a halo orbit near the L1 Lagrange point and rendezvous to a halo orbit near the L2 Lagrange point. Results illustrate the advantage of designing the reference trajectory and the periodic control directly in the ER3BP setting versus approximate solutions based on the circular restricted three-body problem (CR3BP)
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