Ultrafast Spectroscopy and Red Emission from β-Ga<Subscript>2</Subscript>O<Subscript>3</Subscript>/β-Ga<Subscript>2</Subscript>S<Subscript>3</Subscript> Nanowires

Ultrafast pump-probe and transient photoluminescence spectroscopy were used to investigate carrier dynamics in β-Ga₂O₃ nanowires converted to β-Ga₂O₃/Ga₂S₃ under H₂S between 400 to 600 °C. The β-Ga₂O₃ nanowires exhibited broad blue emission with a lifetime of 2.4 ns which was strongly suppressed after processing at 500–600 °C giving rise to red emission centered at 680 nm with a lifetime of 19 μs. Differential absorption spectroscopy reveals that state filling occurs in states located below the conduction band edge before sulfurization, but free carrier absorption is dominant in the β-Ga₂O₃/Ga₂S₃ nanowires processed at 500 to 600 °C for probing wavelengths >500 nm related to secondary excitation of the photo-generated carriers from the mid-gap states into the conduction band of Ga₂S₃.     

Robust near-optimal output feedback control of non-linear systems

This work proposes a robust near-optimal non-linear output feedback controller design for a broad class of non-linear systems with time-varying bounded uncertain variables. Both vanishing and non-vanishing uncertainties are considered. Under the assumptions of input-to-state stable (ISS) inverse dynamics and vanishing uncertainty, a robust dynamic output feedback controller is constructed through combination of a high-gain observer with a robust optimal state feedback controller synthesized via Lyapunov's direct method and the inverse optimal approach. The controller enforces exponential stability and robust asymptotic output tracking with arbitrary degree of attenuation of the effect of the uncertain variables on the output of the closed-loop system, for initial conditions and uncertainty in arbitrarily large compact sets, provided that the observer gain is sufficiently large. Utilizing the inverse optimal control approach and singular perturbation techniques, the controller is shown to be near-optimal in the sense that its performance can be made arbitrarily close to the optimal performance of the robust optimal state feedback controller on the infinite time-interval by selecting the observer gain to be sufficiently large. For systems with non-vanishing uncertainties, the same controller is shown to ensure boundedness of the states, uncertainty attenuation and near-optimality on a finite time-interval. The developed controller is successfully applied to a chemical reactor example.     

Effect of hydrogen-diesel fuel co-combustion on exhaust emissions with verification using an in–cylinder gas sampling technique

The paper presents an experimental investigation of hydrogen-diesel fuel co-combustion carried out on a naturally aspirated, direct injection diesel engine. The engine was supplied with a range of hydrogen-diesel fuel mixture proportions to study the effect of hydrogen addition (aspirated with the intake air) on combustion and exhaust emissions. The tests were performed at fixed diesel injection periods, with hydrogen added to vary the engine load between 0 and 6 bar IMEP. In addition, a novel in–cylinder gas sampling technique was employed to measure species concentrations in the engine cylinder at two in–cylinder locations and at various instants during the combustion process.     

The influence of molecular structure of fatty acid monoalkyl esters on diesel combustion

The subject of this paper is a series of experiments conducted on a single-cylinder research engine investigating the influence of molecular structure on the combustion behaviour of fatty acid alcohol ester (biodiesel) molecules under diesel engine conditions. The fuels employed in these experiments comprised various samples of pure individual fatty acid alcohol ester molecules of different structure, as well as several mixtures of such molecules. The latter consisted in biodiesel fuels produced by the transesterification of naturally occurring plant oils or animal fat with a monohydric alcohol. It was observed that the molecular structure of the fuel significantly influenced the formation of NO_x and particulate matter and their respective concentration in the exhaust gas. The influence on the formation of NO_x in particular, appeared to be exerted first through the effect which the molecular structure had on the auto-ignition delay occurring after the fuel was injected into the combustion chamber, and second through the flame temperature at which the various molecules burned. The emission of particulates on the other hand showed correlation with the number of double bonds in the fuel molecules for the case of larger accumulation mode particles, and with the boiling point of the fuel samples for the case of the smaller, nucleation mode particles. The effect of ignition delay on the exhaust emissions of these pollutants was isolated by adding the ignition promoting molecule 2-ethylhexyl nitrate to some of the fuel samples in closely specified concentrations, so as to equalise the ignition delay for the relevant fuel samples. The removal of the ignition delay as a main influence on the combustion process enabled the observation of the lesser effects of adiabatic flame temperature.     

On finite-time and infinite-time cost improvement of economic model predictive control for nonlinear systems

A novel two-layer economic model predictive control (EMPC) structure that addresses provable finite-time and infinite-time closed-loop economic performance of nonlinear systems in closed-loop with EMPC is presented. In the upper layer, a Lyapunov-based EMPC (LEMPC) scheme is formulated with performance constraints by taking advantage of an auxiliary Lyapunov-based model predictive control (LMPC) problem solution formulated with a quadratic cost function. The lower layer LEMPC uses a shorter prediction horizon and smaller sampling period than the upper layer LEMPC and involves explicit performance-based constraints computed by the upper layer LEMPC. Thus, the two-layer architecture allows for dividing dynamic optimization and control tasks into two layers for a computationally manageable control scheme at the feedback control (lower) layer. A chemical process example is used to demonstrate the performance and stability properties of the two-layer LEMPC structure.     

Output feedback control of nonlinear systems subject to sensor data losses

In this work, we focus on output feedback control of nonlinear systems subject to sensor data losses. We initially construct an output feedback controller based on a combination of a Lyapunov-based controller with a high-gain observer. We then study the stability and robustness properties of the closed-loop system in the presence of sensor data losses for both the continuous and sampled-data systems. We state a set of sufficient conditions under which the closed-loop system is guaranteed to be practically stable. The theoretical results are demonstrated using a chemical process example.     

Economic model predictive control with time‐varying objective function for nonlinear process systems

Economic model predictive control (EMPC) is a control scheme that combines real‐time dynamic economic process optimization with the feedback properties of model predictive control (MPC) by replacing the quadratic cost function with a general economic cost function. Almost all the recent work on EMPC involves cost functions that are time invariant (do not explicitly account for time‐varying process economics). In the present work, we focus on the development of a Lyapunov‐based EMPC (LEMPC) scheme that is formulated with an explicitly time‐varying economic cost function. First, the formulation of the proposed two‐mode LEMPC is given. Second, closed‐loop stability is proven through a theoretical treatment. Last, we demonstrate through extensive closed‐loop simulations of a chemical process that the proposed LEMPC can achieve stability with time‐varying economic cost as well as improve economic performance of the process over a conventional MPC scheme. © 2013 American Institute of Chemical Engineers AIChE J 60: 507–519, 2014