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Abstract This paper considers the problems of reachable set estimation and synthesis of delta operator systems under bounded peak disturbances. A basic reachable set estimation tool for delta operator systems is developed, which can be reduced to the z -domain or s -domain forms when sampling period is 1 or tends to 0. Through the obtained generalized criterion of reachable set, the ellipsoidal reachable set estimation condition of delta operator systems is proposed. Moreover, the state-feedback controller design problem for delta operator systems is investigated. The intention of the controller is to bound the closed-loop system to a given ellipsoid or to make the reachable set of system trajectory as small as possible. Finally, the effectiveness of the obtained results are illustrated by several numerical examples. [ABSTRACT FROM AUTHOR]

This paper proposes a novel multiple-stress-based predictive model (MSBPM) to rapidly assess the lifetime of light-emitting diodes (LEDs). The MSBPM addresses the lifetime estimation of LEDs with respect to temperature, humidity, and current; these three stresses are rarely considered simultaneously in the assessment of reliability. Using several degradation data sets from accelerated life tests (ALTs) without using extrapolation method, a designed adaptive genetic algorithm is employed to identify five unknown parameters of the MSBPM. A simulation of the proposed MSBPM is presented as validation. By applying the degradation data from the ALTs under high stresses, an MSBPM for the LEDs is established. Under the nominal conditions of 25 °C/22.5% RH and a current of 0.35 A, the lifetime of the LED is estimated using the established MSBPM. The effectiveness of the proposed MSBPM is further verified through the estimated results. [ABSTRACT FROM AUTHOR]

• Development of a focusing recovery technology for 3D reconstruction of wear particle surfaces. • Establishment of a fixed-focus quasi-planar strategy for measuring the depth of wear particle surfaces. • Optimization of the 3D model to mitigate unevenness and enhance reconstruction accuracy. Wear particles hold morphological traits that are linked to wear rate and mechanisms. Wear particle analysis is vital in the context of wear monitoring. Current methods can be used in three-dimensional (3D) reconstruction for particle type recognition and wear mechanism identification. A 3D reconstruction method based on microscopic focusing and image processing is here proposed. A fixed-focus quasi-planar strategy is built using the defocusing principle. The stationary wavelet transform is employed to assess the degree of focus for the purpose of depth mapping, facilitating the construction of 3D particle models. The model is then optimized for surface morphology to address noise and unevenness. The reconstruction results of the proposed approach were compared with that of laser scanning confocal microscope with average errors of arithmetic mean height (Sa), root-mean-square height (Sq), and kurtosis (Sku) at 2.81%, 2.96%, and 10.06%, respectively. The algorithm is non-contact and adaptable, offering value across various fields. [ABSTRACT FROM AUTHOR]