Robust predictive extended state observer for a class of nonlinear systems with time-varying input delay

ABSTRACT

This paper deals with asymptotic stabilisation of a class of nonlinear input-delayed systems via dynamic output feedback in the presence of disturbances. The proposed strategy has the structure of an observer-based control law, in which the observer estimates and predicts both the plant state and the external disturbance. A nominal delay value is assumed to be known and stability conditions in terms of linear matrix inequalities are derived for fast-varying delay uncertainties. Asymptotic stability is achieved if the disturbance or the time delay is constant. The controller design problem is also addressed and a numerical example with an unstable system is provided to illustrate the usefulness of the proposed strategy.     

Fabrication of Cu/graphite film/Cu sandwich composites with ultrahigh thermal conductivity for thermal management applications

Effective thermal management of electronic integrated devices with high powder density has become a serious issue, which requires materials with high thermal conductivity (TC). In order to solve the problem of weak bonding between graphite and Cu, a novel Cu/graphite film/Cu sandwich composite (Cu/GF/Cu composite) with ultrahigh TC was fabricated by electro-deposition. The micro-riveting structure was introduced to enhance the bonding strength between graphite film and deposited Cu layers by preparing a rectangular array of micro-holes on the graphite film before electro-deposition. TC and mechanical properties of the composites with different graphite volume fractions and current densities were investigated. The results showed that the TC enhancement generated by the micro-riveting structure for Cu/GF/Cu composites at low graphite content was more effective than that at high graphite content, and the strong texture orientation of deposited Cu resulted in high TC. Under the optimizing preparing condition, the highest in-plane TC reached 824.3 W·m⁻¹·K⁻¹, while the ultimate tensile strength of this composite was about four times higher than that of the graphite film.     

Characteristics and formation mechanism of porosities in CFRP during laser joining of CFRP and steel

An experimental investigation on the mechanism of porosity formation during the laser joining of carbon fiber reinforced polymer (CFRP) and steel is presented. The porosity morphology and distribution were characterized by optical and scanning electron microscopy, and the thermal pyrolysis behaviors were investigated by thermal analysis and designed back-side cooling experiments. The results show that there are two types of porosities in CFRP. Porosity I only appears when the heat input is more than 77.8 J/mm. It has a smooth inner wall and distributes near the bonding interface between CFRP and steel at the central area of melted zone, which is caused by gaseous products such as CO₂, NH₃, H₂O, and hydrocarbons produced by the pyrolysis of CFRP. Porosity II can be seen under all joining conditions. It has a rough inner wall and distributes far away from the bonding interface, concentrating at the final solidification locations. Porosity II is caused by the shrinkage of melted CFRP during solidification stage.     

The effects of surface-modified graphene nanoplatelets on the sliding wear properties of basalt fibers-reinforced epoxy composites

Possessing unique designs and properties absent in conventional materials, nanocomposites have made a remarkable imprint in science and technology. This is particularly true regarding the polymer matrix composites when they are further reinforced with nanoparticles. In this study, the effects of different weight percentages (0, 0.1, 0.2, 0.3, 0.4, and 0.5) of surface-modified graphene nanoplatelets (GNPs) on the microhardness and wear properties of basalt fibers/epoxy composites were investigated. The GNPs were surface modified by silane, and the composites were made by the hand lay-up method. The wear tests were conducted under two different loads of 20 and 40 N. The best wear properties were achieved at 0.3 wt % GNPs as a result of the GNPs' self-lubrication property and the formation of a stable transfer/lubricating film at the pin and disk interface. Moreover, the friction coefficient was lower at the higher normal load of 40 N. The microscopic studies by FESEM and SEM showed that the presence of GNPs up to 0.3 wt % led to the stability of the transfer/lubricating film by enhancing the adhesion of the basalt fibers to the epoxy resin. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47986.     

Leader-following consensus of fractional-order multi-agent systems via adaptive control

This article focuses on the consensus problem of leader-following fractional-order multi-agent systems (MASs) with general linear and Lipschitz nonlinear dynamics. First, the distributed adaptive protocols for linear and nonlinear fractional-order MASs are constructed, respectively. We allow the control coupling gains to be time varying for each agent. Moreover, the adaptive modification schemes for the control gain are designed, which renders smaller control gains and thus requires smaller amplitude on the control input without sacrificing consensus convergence. Second, based on fractional-order Lyapunov stability theorem and Barbalat's lemma, two novel sufficient conditions in terms of linear matrix inequalities are provided to ensure that the leader-following consensus can be obtained in the case for any undirected connected communication graph. Furthermore, we show that the proposed algorithm also works for consensus of agents with intrinsic Lipschitz nonlinear dynamics. As a result, the proposed framework requires no global information and thus can be implemented in a fully distributed manner. Finally, the numerical simulations are given to demonstrate the effectiveness of obtained the theoretical results.     

Crack initiation and propagation in braided SiC/SiC composite tubes: Effect of braiding angle

Crack initiation and propagation in three braided SiC/SiC composite tubes with different braiding angles are investigated by in situ tensile tests with synchrotron micro-computed tomography. Crack networks are precisely detected after an image subtraction procedure based on Digital Volume Correlation. FFT based simulations are performed on the full-resolution 3D images to assess elastic stress/strain fields. Quantitative measurements of the crack geometries are performed using a novel method based on grey levels. The results show that braiding angle has no obvious effect on the location of crack onsets (initiation always occurs at tow interfaces), whereas it significantly affects the paths of crack propagation. This work provides an explicit demonstration of the crack propagation scenarios with respect to the mesoscopic fibre architectures.     

Impact behavior and fractographic study of carbon nanotubes grafted carbon fiber-reinforced epoxy matrix multi-scale hybrid composites

Carbon nanotubes are the most promising reinforcement for high performance composites. Multiwall carbon nanotubes were directly grown onto the carbon fiber surface by catalytic thermal chemical vapor deposition technique. Multi-scale hybrid composites were fabricated using the carbon nanotubes grown fibers with epoxy matrix. Morphology of the grown carbon nanotubes was investigated using field emission scanning electron microscopy and transmission electron microscopy. The fabricated composites were subjected to impact tests which showed 48.7% and 42.2% higher energy absorption in Charpy and Izod impact tests respectively. Fractographic analysis of the impact tested specimens revealed the presence of carbon nanotubes both at the fiber surface and within the matrix which explained the reason for improved energy absorption capability of these composites. Carbon nanotubes presence at various cracks formed during loading provided a direct evidence of micro crack bridging. Thus the enhanced fracture strength of these composites is attributed to stronger fiber–matrix interfacial bonding and simultaneous matrix strengthening due to the grown carbon nanotubes.     

Mechanical damage characterization of glass fiber-reinforced polymer laminates by ultrasonic maps

A method for simultaneous measurement of the thickness and density for Glass Fiber-Reinforced Polymer (GFRP) laminate plates with ultrasonic waves in C-Scan mode is presented in the form of maps. The method uses three different signals in immersion pulse-echo C-Scan mode. The maps obtained based on the density show the heterogeneity of the material at high resolution at the pixel level (1 × 1 mm²) and therefore they represent an efficient tool to assess and evaluate the damage of the composite structures after manufacturing and after an applied mechanical loading.     

Core–shell NTC materials with low thermal constant and high resistivity for wide-temperature thermistor ceramics

Core–shell structures have been proposed to improve the electrical properties of negative-temperature coefficient (NTC) thermistor ceramics. In this work, Al₂O₃-modified Co_1.5Mn_1.2Ni_0.3O₄ NTC thermistor ceramics with adjustable electrical properties were prepared through citrate-chelation followed by conventional sintering. Co_1.5Mn_1.2Ni_0.3O₄ powder was coated with a thin Al₂O₃ shell layer to form a core–shell structure. Resistivity (ρ) increased rapidly with increasing thickness of the Al₂O₃ layer, and the thermal constant (B) varied moderately between 3706 and 3846 K. In particular, Co_1.5Mn_1.2Ni_0.3O₄@Al₂O₃ ceramic with 0.08 wt% Al₂O₃ showed the increase of ρ double, and the change in its B was less than 140 K. The Co_1.5Mn_1.2Ni_0.3O₄@Al₂O₃ NTC ceramics showed high stability, and their grain size was relatively uniform due to the protection offered by the shell. The aging coefficient of the ceramic was less than 0.2% after aging for 500 hours at 125°C. Taken together, the results indicate that as-prepared Co_1.5Mn_1.2Ni_0.3O₄@Al₂O₃ NTC ceramics with a core–shell structure may be promising candidates for application as wide-temperature NTC thermistor ceramics.     

A bat-neural network multi-agent system (BNNMAS) for stock price prediction: Case study of DAX stock price

Creating an intelligent system that can accurately predict stock price in a robust way has always been a subject of great interest for many investors and financial analysts. Predicting future trends of financial markets is more remarkable these days especially after the recent global financial crisis. So traders who access to a powerful engine for extracting helpful information throw raw data can meet the success. In this paper we propose a new intelligent model in a multi-agent framework called bat-neural network multi-agent system (BNNMAS) to predict stock price. The model performs in a four layer multi-agent framework to predict eight years of DAX stock price in quarterly periods. The capability of BNNMAS is evaluated by applying both on fundamental and technical DAX stock price data and comparing the outcomes with the results of other methods such as genetic algorithm neural network (GANN) and some standard models like generalized regression neural network (GRNN), etc. The model tested for predicting DAX stock price a period of time that global financial crisis was faced to economics. The results show that BNNMAS significantly performs accurate and reliable, so it can be considered as a suitable tool for predicting stock price specially in a long term periods.