Enhancement of Nematic Order and Global Phase Diagram of a Lattice Model for Coupled Nematic Systems

We use an infinite-range Maier-Saupe model, with two sets of local quadrupolar variables and restricted orientations, to investigate the global phase diagram of a coupled system of two nematic subsystems. The free energy and the equations of state are exactly calculated by standard techniques of statistical mechanics. The nematic-isotropic transition temperature of system A increases with both the interaction energy among mesogens of system B, and the two-subsystem coupling J. This enhancement of the nematic phase is manifested in a global phase diagram in terms of the interaction parameters and the temperature T. We make some comments on the connections of these results with experimental findings for a system of diluted ferroelectric nanoparticles embedded in a nematic liquid-crystalline environment.

Modeling of active holonic control systems for intelligent buildings

Building facilities have become important infrastructures for modern productive plants dedicated to services. In this context, the control systems of intelligent buildings have evolved while their reliability has evidently improved. However, the occurrence of faults is inevitable in systems conceived, constructed and operated by humans. Thus, a practical alternative approach is found to be very useful to reduce the consequences of faults. Yet, only few publications address intelligent building modeling processes that take into consideration the occurrence of faults and how to manage their consequences. In the light of the foregoing, a procedure is proposed for the modeling of intelligent building control systems, considersing their functional specifications in normal operation and in the of the event of faults. The proposed procedure adopts the concepts of discrete event systems and holons, and explores Petri nets and their extensions so as to represent the structure and operation of control systems for intelligent buildings under normal and abnormal situations. (C) 2012 Elsevier B.V. All rights reserved.

Linear matrix inequality-based robust model predictive control for time-delayed systems

This work addresses the solution to the problem of robust model predictive control (MPC) of systems with model uncertainty. The case of zone control of multi-variable stable systems with multiple time delays is considered. The usual approach of dealing with this kind of problem is through the inclusion of non-linear cost constraint in the control problem. The control action is then obtained at each sampling time as the solution to a non-linear programming (NLP) problem that for high-order systems can be computationally expensive. Here, the robust MPC problem is formulated as a linear matrix inequality problem that can be solved in real time with a fraction of the computer effort. The proposed approach is compared with the conventional robust MPC and tested through the simulation of a reactor system of the process industry.

Closed-loop stable model predictive control of integrating systems with dead time

Model predictive control (MPC) applications in the process industry usually deal with process systems that show time delays (dead times) between the system inputs and outputs. Also, in many industrial applications of MPC, integrating outputs resulting from liquid level control or recycle streams need to be considered as controlled outputs. Conventional MPC packages can be applied to time-delay systems but stability of the closed loop system will depend on the tuning parameters of the controller and cannot be guaranteed even in the nominal case. In this work, a state space model based on the analytical step response model is extended to the case of integrating time systems with time delays. This model is applied to the development of two versions of a nominally stable MPC, which is designed to the practical scenario in which one has targets for some of the inputs and/or outputs that may be unreachable and zone control (or interval tracking) for the remaining outputs. The controller is tested through simulation of a multivariable industrial reactor system. (C) 2012 Elsevier Ltd. All rights reserved.

Polymerization kinetics and reactivity of alternative initiators systems for use in light-activated dental resins

Objectives. The purpose of this study was to evaluate the reactivity and polymerization kinetics behavior of a model dental adhesive resin with water-soluble initiator systems. Methods. A monomer blend based on Bis-GMA, TEGDMA and HEMA was used as a model dental adhesive resin, which was polymerized using a thioxanthone type (QTX) as a photoinitiator. Binary and ternary photoinitiator systems were formulated using 1 mol% of each initiator. The co-initiators used in this study were ethyl 4-dimethylaminobenzoate (EDAB), diphenyliodonium hexafluorophosphate (DPIHFP), 1,3-diethyl-2-thiobarbituric acid (BARB), p-toluenesulfinic acid and sodium salt hydrate (SULF). Absorption spectra of the initiators were measured using a UV-Vis spectrophotometer, and the photon absorption energy (PAE) was calculated. The binary system camphorquinone (CQ)/amine was used as a reference group (control). Twelve groups were tested in triplicate. Fourier-transform infrared spectroscopy (FTIR) was used to investigate the polymerization reaction during the photoactivation period to obtain the degree of conversion (DC) and maximum polymerization rate (R-p(max)) profile of the model resin. Results. In the analyzed absorption profiles, the absorption spectrum of QTX is almost entirely localized in the UV region, whereas that of CQ is in the visible range. With respect to binary systems, CQ + EDAB exhibited higher DC and R-p(max) values. In formulations that contained ternary initiator systems, the group CQ + QTX + EDAB was the only one of the investigated experimental groups that exhibited an R-p(max) value greater than that of CQ + EDAB. The groups QTX + EDAB + DPIHFP and QTX + DPIHFP + SULF exhibited values similar to those of CQ + EDAB with respect to the final DC; however, they also exhibited lower reactivity. Significance. Water-soluble initiator systems should be considered as alternatives to the widely used CQ/amine system in dentin adhesive formulations. (C) 2012 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

SINGULARLY PERTURBED DISCOUNTED MARKOV CONTROL PROCESSES IN A GENERAL STATE SPACE

This paper studies the asymptotic optimality of discrete-time Markov decision processes (MDPs) with general state space and action space and having weak and strong interactions. By using a similar approach as developed by Liu, Zhang, and Yin [Appl. Math. Optim., 44 (2001), pp. 105-129], the idea in this paper is to consider an MDP with general state and action spaces and to reduce the dimension of the state space by considering an averaged model. This formulation is often described by introducing a small parameter epsilon > 0 in the definition of the transition kernel, leading to a singularly perturbed Markov model with two time scales. Our objective is twofold. First it is shown that the value function of the control problem for the perturbed system converges to the value function of a limit averaged control problem as epsilon goes to zero. In the second part of the paper, it is proved that a feedback control policy for the original control problem defined by using an optimal feedback policy for the limit problem is asymptotically optimal. Our work extends existing results of the literature in the following two directions: the underlying MDP is defined on general state and action spaces and we do not impose strong conditions on the recurrence structure of the MDP such as Doeblin's condition.

Optimal mean-variance control for discrete-time linear systems with Markovian jumps and multiplicative noises

In this paper, we consider the stochastic optimal control problem of discrete-time linear systems subject to Markov jumps and multiplicative noises under two criteria. The first one is an unconstrained mean-variance trade-off performance criterion along the time, and the second one is a minimum variance criterion along the time with constraints on the expected output. We present explicit conditions for the existence of an optimal control strategy for the problems, generalizing previous results in the literature. We conclude the paper by presenting a numerical example of a multi-period portfolio selection problem with regime switching in which it is desired to minimize the sum of the variances of the portfolio along the time under the restriction of keeping the expected value of the portfolio greater than some minimum values specified by the investor. (C) 2011 Elsevier Ltd. All rights reserved.