Adaptive neural dynamic surface control of MIMO nonlinear time delay systems with time‐varying actuator failures

In this paper, an adaptive dynamic surface control approach is developed for a class of multi‐input multi‐output nonlinear systems with unknown nonlinearities, bounded time‐varying state delays, and in the presence of time‐varying actuator failures. The type of the considered actuator failure is that some unknown inputs may be stuck at some time‐varying values where the values, times, and patterns of the failures are unknown. The considered actuator failure can cover most failures that may occur in actuators of the systems. With the help of neural networks to approximate the unknown nonlinear functions and combining the dynamic surface control approach with the backstepping design method, a novel control approach is constructed. The proposed design method does not require a priori knowledge of the bounds of the unknown time delays and actuator failures. The boundedness of all the closed‐loop signals is guaranteed, and the tracking errors are proved to converge to a small neighborhood of the origin. The proposed approach is employed for a double inverted pendulums benchmark as well as a chemical reactor system. The simulation results show the effectiveness of the proposed method. Copyright © 2016 John Wiley & Sons, Ltd.     

Oxy‐fuel combustion technology: current status,applications, and trends

The increased level of emissions of carbon dioxide into the atmosphere due to burning of fossil fuels represents one of the main barriers toward the reduction of greenhouse gases and the control of global warming. In the last decades, the use of renewable and clean sources of energies such as solar and wind energies has been increased extensively. However, due to the tremendously increasing world energy demand, fossil fuels would continue in use for decades which necessitates the integration of carbon capture technologies (CCTs) in power plants. These technologies include oxycombustion, pre‐combustion, and post‐combustion carbon capture. Oxycombustion technology is one of the most promising carbon capture technologies as it can be applied with slight modifications to existing power plants or to new power plants. In this technology, fuel is burned using an oxidizer mixture of pure oxygen plus recycled exhaust gases (consists mainly of CO₂). The oxycombustion process results in highly CO₂‐concentrated exhaust gases, which facilitates the capture process of CO₂ after H₂O condensation. The captured CO₂ can be used for industrial applications or can be sequestrated. The current work reviews the current status of oxycombustion technology and its applications in existing conventional combustion systems (including gas turbines and boilers) and novel oxygen transport reactors (OTRs). The review starts with an introduction to the available CCTs with emphasis on their different applications and limitations of use, followed by a review on oxycombustion applications in different combustion systems utilizing gaseous, liquid, and coal fuels. The current status and technology readiness level of oxycombustion technology is discussed. The novel application of oxycombustion technology in OTRs is analyzed in some details. The analyses of OTRs include oxygen permeation technique, fabrication of oxygen transport membranes (OTMs), calculation of oxygen permeation flux, and coupling between oxygen separation and oxycombustion of fuel within the same unit called OTR. The oxycombustion process inside OTR is analyzed considering coal and gaseous fuels. The future trends of oxycombustion technology are itemized and discussed in details in the present study including: (i) ITMs for syngas production; (ii) combustion utilizing liquid fuels in OTRs; (iii) oxy‐combustion integrated power plants and (iv) third generation technologies for CO₂ capture. Techno‐economic analysis of oxycombustion integrated systems is also discussed trying to assess the future prospects of this technology. Copyright © 2017 John Wiley & Sons, Ltd.     

Current Distribution and Nonlinearity of Open-Ends and Gaps in Superconducting Microstrip Structures

Superconducting devices are known to produce nonlinear effects. In planar structures, these nonlinearities depend on the current distribution on the strip, which definitely depends on the structure of device. This paper used a numerical method based on 3D-FEM to obtain the current distribution in the open-ends and gaps in the superconducting microstrip structures. This is used to present the nonlinear distributed circuit modeling of these discontinuities and its impact on the nonlinear phenomenon. This nonlinear circuit model is used in the Harmonic Balance (HB) method to analyze nonlinearity in the superconducting microwave devices. Therefore, this simple accurate enough nonlinear circuit model is warmly welcomed to retire the seemingly inevitable use of time- and memory-consuming numerical techniques for nonlinear analysis of discontinuities in superconducting microwave structures. As an example, we analyze a microstrip superconducting end-coupled band pass filter (BPF). These results are very useful for optimizing the resonators of the superconducting microwave filters in order to minimize its nonlinear distortions.     

An acidic ionic liquid-conventional alkali-catalyzed biodiesel production process

A study was undertaken to prepare biodiesel via two-step process using ionic liquid as first step catalyst due to the unsuitability of using the straight alkaline-catalyzed transesterification of high FFA presented in crude palm oil (CPO). In the first step, esterification of the FFA presented in the CPO was carried out using butylimidazolium hydrogen sulfate (BIMHSO₄), in which the acid value was reduced from 6.93 to 1.02mg KOH/g and then, KOH-catalyzed transesterification was applied. The conversion rate of FFA attained 85.3% when 4.8 wt% of BIMHSO₄ was applied to the reaction system containing methanol to CPO ratio of 12: 1 reacted at 170 °C for 150min. The final yield in 97.3% revealed that the process proposed in this study could lead to an excellent biodiesel meeting the ASTM requirements. Furthermore, this new two-step catalysis process could solve the old conventional catalysis process drawbacks.     

Chaos control of a bounded 4D chaotic system

This paper is concerned with the problem of optimal and adaptive control for controlling chaos in a novel bounded four-dimensional (4D) chaotic system. This system can display hyperchaos, chaos, quasiperiodic and periodic behaviors, and may have a unique equilibrium, three equilibria and five equilibria for the different system parameters. An optimal control law is designed for the novel bounded chaotic system, based on the Pontryagin minimum principle. Furthermore, we propose Lyapunov stability conditions to control the new bounded 4D chaotic system with unknown parameters by a feedback control approach. Numerical simulations are presented to show the effectiveness of the proposed chaos control scheme.     

A parsimonious SVM model selection criterion for classification of real-world data sets via an adaptive population-based algorithm

This paper proposes and optimizes a two-term cost function consisting of a sparseness term and a generalized v-fold cross-validation term by a new adaptive particle swarm optimization (APSO). APSO updates its parameters adaptively based on a dynamic feedback from the success rate of the each particle’s personal best. Since the proposed cost function is based on the choosing fewer numbers of support vectors, the complexity of SVM model is decreased while the accuracy remains in an acceptable range. Therefore, the testing time decreases and makes SVM more applicable for practical applications in real data sets. A comparative study on data sets of UCI database is performed between the proposed cost function and conventional cost function to demonstrate the effectiveness of the proposed cost function.