Guido Maione

High-Speed Digital Realizations of Fractional Operators in the Delta Domain

The realization of fractional-order controllers is based on the approximation of the irrational operators by continuous or discrete transfer functions. However, at high sampling frequencies, discrete z-transfer functions approximations can be very sensitive even to small changes in coefficient values. This technical note proposes a realization of sν , in terms of transfer functions in the complex delta-domain, which improves considerably the robustness of the approximation to parameter changes and then to truncation in transfer function coefficients applied for implementation with finite word length.

Design of Supervisors to Avoid Deadlock in Flexible Assembly Systems

Modern production systems exhibit a high degree of resource sharing that can lead to deadlock conditions. Deadlock arises when some parts remain indefinitely blocked because each of them requests access to a resource held by some other parts. One of the tasks of the control system lies in preventing such situations from occurring by proper resource management.This article addresses the deadlock problem for an important class of production facilities, that is, flexible assembly systems, that can perform both manufacturing or assembly operations. In particular, we develop an approach to deadlock avoidance based on a supervisory control that works by inhibiting or enabling the events involving resource allocation. The article proposes two supervisors characterized by easy implementation, efficiency, and flexibility in resource management. The analysis of some case studies, performed by discrete event simulation, confirms the effectiveness of the approach.

A rational discrete approximation to the operator s/sup 0.5/

This letter deals with the discrete approximation of the fractional-order differentiator s/sup 0.5/. The proposed approach is based on the efficient continued fraction approximation of the operator. The discrete differentiator is expressed as a z-transfer function, whose coefficients are given in closed form in terms of the sampling time and an approximation parameter. Simulation experiments show the efficiency of the approximation with low-order z-transfer functions.

On the Laguerre Rational Approximation to Fractional Discrete Derivative and Integral Operators

This note ties the Laguerre continued fraction expansion of the Tustin fractional discrete-time operator to irreducible Jacobi tri-diagonal matrices. The aim is to prove that the Laguerre approximation to the Tustin fractional operator s-ν (or sν ) is stable and minimum-phase for any value 0 <; ν <; 1 of the fractional order ν. It is also shown that zeros and poles of the approximation are interlaced and lie in the unit circle of the complex z -plane, keeping a special symmetry on the real axis. The quality of the approximation is analyzed both in the frequency and time domain. Truncation error bounds of the approximants are given.

Genetic identification of dynamical systems with static nonlinearities

This paper describes the application of genetic algorithms (GA) to identify a class of nonlinear SISO models composed of a memoryless nonlinearity in series with a linear transfer function. In contrast with recent literature on the considered problem, we encode in the chromosomes also the structure of the model (type of nonlinearity, number of zeros and poles), and use the GA to identify both the optimal structure and the associated parameters. New operators for mutation and crossover to deal with chromosomes with variable length are introduced. The effectiveness of the approach is tested on a set of case studies derived from literature.

A genetic approach for adaptive multiagent control in heterarchical manufacturing systems

In this paper, we apply genetic algorithms to adapt the decision strategies of autonomous controllers in a part-driven heterarchical manufacturing system. The control agents use pre-assigned decision rules only for a limited amount of time, and obey a rule replacement policy propagating the most successful rules to the subsequent populations of concurrently operating agents. The twofold objective of this approach is to automatically optimize the performance of the control system during the steady-state unperturbed conditions of the manufacturing floor, and to improve the reactions of the agents to unforeseen disturbances (e.g., failures, shortages of materials) by adapting their decision strategies. Results on a detailed discrete event model of a multiagent heterarchical manufacturing system confirm the effectiveness of the approach.

Distributed event-control for deadlock avoidance in automated manufacturing systems

This paper develops a decentralized event-control strategy to avoid deadlock in automated manufacturing systems. On the basis of the characteristics of the part mix that is currently active, the system is partitioned in subsystems that can be controlled locally and independently using graph-theoretic tools. The controller of each subsystem can be chosen as the best compromise between computational costs and flexibility in resource allocation and depending on the particular layout of the subsystem. The decentralized scheme allows the overall system to improve its flexibility and guarantee good performance measures. The approach is particularly suitable for cellular manufacturing systems that do not exclude intercell flow. In this case the method determines the cells that can be controlled independently and the ones that must be controlled jointly. A case study performed by discrete-event simulation confirms the efficiency of the proposed methodology.

Concerning continued fractions representation of noninteger order digital differentiators

The discretization of a fractional-order differentiator snu , where nu is a real number 0<nu<1, is an important issue in digital signal processing. This letter gives the analytical expression of the convergents of a continued fraction expansion of the binomial (1+s)nu to get a rapidly convergent, stable, minimum-phase approximation of digital differentiators

Closed-Form Rational Approximations of Fractional, Analog and Digital Differentiators/Integrators

This paper provides closed-form formulas for coefficients of convergents of some popular continued fraction expansions (CFEs) approximating s^ν, with , and (2/T)^ν((z-1)/(z+1))^ν. The expressions of the coefficients are given in terms of ν and of the degree n of the polynomials defining the convergents. The formulas greatly reduce the effort for approximating fractional operators and show the equivalence between two well-known CFEs in a given condition.

A novel FDTD formulation based on fractional derivatives for dispersive Havriliak-Negami media

A novel finite-difference time-domain (FDTD) scheme modeling the electromagnetic pulse propagation in Havriliak-Negami dispersive media is proposed. In traditional FDTD methods, the main drawback occurring in the evaluation of the electromagnetic propagation is the approximation of the fractional derivatives appearing in the Havriliak-Negami model equation. In order to overcome this problem, we have developed a novel FDTD scheme based on the direct solution of the time-domain Maxwell equations by using the Riemann-Liouville operator for fractional differentiation. The scheme can be easily applied to other dispersive material models such as Debye, Cole-Cole and Cole-Davidson. Different examples relevant to plane wave propagation in a variety of dispersive media are analyzed. The numerical results obtained by means of the proposed FDTD scheme are found to be in good accordance with those obtained implementing analytical method based on Fourier transformation over a wide frequency range. Moreover, the feasibility of the proposed method is demonstrated by simulating the transient wave propagation in slabs of dispersive materials. HighlightsFDTD modeling for electromagnetic pulse propagation in complex media.Evaluation of the transmittance and reflectance in slab of dispersive materials.Approximations of fractional derivatives using finite differences.