Robust Adaptive Soft Landing Control of an Electromagnetic Valve Actuator for Camless Engines

This paper deals with a signal‐based robust adaptive approximation technique for a proportional derivative (PD) regulator which is applied to an electromagnetic valve actuator control for camless internal combustion engines. PD regulators generate very high spikes in the presence of unavoidable noise. These spikes cause high power dissipation and poor dynamic performance with a lack of precision. The presented method allows the reduction of the noise and not robust nonlinear uncertainties effects by using minimum variance analysis. The technique with which the PD regulator is approximated does not depend on the model of the controlled system. Hence, the technique is quite general and can be applied to any type of system. In addition, this paper describes a feasible real‐time self‐tuning of an approximated discrete PD regulator using a backward Euler technique. The main contribution of the paper is the presentation of an approximated PD controller using a minimum variance control strategy together with a weighted least squares method to adapt the parameters of this approximated controller. This control law realises a robust control technique with respect to the noise and nonlinear uncertainties. Moreover, a comparison with the approximate PD controller proposed in MATLAB by Mathworks is provided. The presented technique ensures a good dynamic performance, including low dissipation as well as accurate positioning and soft landing control.     

Pareto-based negotiation in distributed multidisciplinary design

The process of distributed engineering design calls for a methodology making use of the most recent advances in optimization-based design including multidisciplinary and multiobjective optimization. In distributed design, the participating teams do not have access to the design problems of other teams but may exchange limited information about their own current designs, making negotiation among themselves a key mechanism to reach a desired compromise which, nevertheless, is also a Pareto design to the original problem. A mathematical model of this distributed but decomposable design process is posed and solved using Lagrangian relaxation, while Pareto optimality is equivalently converted to single-objective optimality by means of multicriteria decision making strategies. The proposed coordination algorithm allows negotiation among the teams (subproblems) by sharing only limited information that is restricted to values of optimization quantities. The proposed modeling and solution scheme is applied to a numerical example representing the design of vehicle subsystems and components.     

DrawBot: a bio-inspired robotic portraitist

Abstract

We are developing the control architecture of a portraitist artificial agent called DrawBot that reproduces the visuomotor behaviour of a human carrying out a realistic portrait. The visuomotor strategy adopted by DrawBot is based on computational models of eye movements in human beings,and one xperimental findings on eye-hand coordination in expert draughtsmen. In this paper we present a behavioural model of the visuomotor coordination adopted by a draughtsman, designed in terms of visual routines.Eventually we outline the implementation of the basic routines.     

Shape from defocus via diffusion

Defocus can be modeled as a diffusion process and represented mathematically using the heat equation, where image blur corresponds to the diffusion of heat. This analogy can be extended to non-planar scenes by allowing a space-varying diffusion coefficient. The inverse problem of reconstructing 3-D structure from blurred images corresponds to an "inverse diffusion" that is notoriously ill-posed. We show how to bypass this problem by using the notion of relative blur. Given two images, within each neighborhood, the amount of diffusion necessary to transform the sharper image into the blurrier one depends on the depth of the scene. This can be used to devise a global algorithm to estimate the depth profile of the scene without recovering the deblurred image, using only forward diffusion.     

A bio-inspired predictive sensory-motor coordination scheme for robot reaching and preshaping

This paper presents a sensory-motor coordination scheme for a robot hand-arm-head system that provides the robot with the capability to reach an object while pre-shaping the fingers to the required grasp configuration and while predicting the tactile image that will be perceived after grasping. A model for sensory-motor coordination derived from studies in humans inspired the development of this scheme. A peculiar feature of this model is the prediction of the tactile image. The implementation of the proposed scheme is based on a neuro-fuzzy module that, after a learning phase, starting from visual data, calculates the position and orientation of the hand for reaching, selects the best-suited hand configuration, and predicts the tactile feedback. The implementation of the scheme on a humanoid robot allowed experimental validation of its effectiveness in robotics and provided perspectives on applications of sensory predictions in robot motor control.     

High power GaN‐HEMT SPDT switches for microwave applications

In this article, the design, fabrication, and on‐wafer test of X‐Band and 2–18 GHz wideband high‐power SPDT MMIC switches in AlGaN/GaN technology are presented. The switches have demonstrated state‐of‐the‐art performance and RF fabrication yield better than 65%. Linear and power measurements for different control voltages have been reported and an explanation of the dependence of the power performances on the control voltage is given. In particular, the X‐band switch exhibits a 0.4 dB compression level at 10 GHz when driven by a 38 dBm input signal. The wideband switch shows a compression level of 1 dB at an input drive higher than 38 dBm across the entire bandwidth. © 2009 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2009.     

Dynamic Dictionary Matching in External Memory

In thedynamic dictionary matchingproblem, a dictionaryDcontains a set of patterns that can change over time under insertion and deletion of individual patterns. Given an arbitrary textT, we must efficiently list all the dictionary patterns that occur at each text position. We investigate the I/O complexity of this problem for a large dictionary that must be stored in external storage devices. By following a completely new approach, we devise an efficient solution which is based upon the SB-tree data structure (P. Ferragina and R. Grossi, 1995,in“Proc. ACM Symposium on Theory of Computing,” pp. 693–702), and a novel notion of certificate for the dictionary matching problem. Our data structure can be adapted to efficiently work in main memory and to solve other problems, thus providing a new insight into the nature of the dictionary matching problem.     

Markov Jump Linear Systems with switching transition rates: Mean square stability with dwell-time

The stability of a class of Markov Jump Linear Systems characterized by piecewise-constant transition rates and system dynamics is investigated. For these Switching Markov Jump Linear Systems, mean square stability is analyzed through the time evolution of the second-order moment of the state. The main result is a sufficient condition that guarantees mean square stability under constraints on the dwell-time between switching instants. An alternative condition based on Kronecker calculus is worked out. It is shown that both the stability criteria admit an LMI implementation.