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.

Assessment of the high-dose concept and level of control provided by MON 87701 x MON 89788 soybean against Anticarsia gemmatalis and Pseudoplusia includens (Lepidoptera: Noctuidae) in Brazil

BACKGROUND: Genetically modified MON 87701 X MON 89788 soybean (Glycine max), which expresses the Cry1Ac and EPSP-synthase proteins, has been registered for commercial use in Brazil. To develop an Insect Resistance Management (IRM) program for this event, laboratory and field studies were conducted to assess the high-dose concept and level of control it provides against Anticarsia gemmatalis and Pseudoplusia includens. RESULTS: The purified Cry1Ac protein was more active against A. gemmatalis [LC50 (FL 95%) = 0.23 (0.150.34) mu g Cry1Ac mL-1 diet] than P. includens [LC50 (FL 95%) = 3.72 (2.654.86) mu g Cry1Ac mL-1 diet]. In bioassays with freeze-dried MON 87701X MON 89788 soybean tissue diluted 25 times in an artificial diet, there was 100% mortality of A. gemmatalis and up to 95.79% mortality for P. includens. In leaf-disc bioassays and under conditions of high artificial infestation in the greenhouse and natural infestation in the field, MON 87701X MON 89788 soybean showed a high level of efficacy against both target pests. CONCLUSIONS: The MON 87701X MON 89788 soybean provides a high level of control against A. gemmatalis and P. includes, but a high-dose event only to A. gemmatalis. Copyright (c) 2012 Society of Chemical Industry

Cost Management Practices and Strategic Perspectives: a study in the construction industry of the State of Parana

The purpose of this paper is to investigate the cost management practices of building industry companies of Parana that follow the typology of Porter's strategies. The sample comprises member companies of the Association of Construction Industries of the State of Parana (PR-SINDUSCON) operating in the segment of residential buildings. The data were collected by means of questionnaires sent to 317 SINDUSCON members. 69 were returned and 54 used for our research. Exploratory Factorial Analysis of the data allowed us to identify two groups of cost management practices. Analyses suggest equality between the adopted cost management practices and the Cost Control Planning (CCP) practices among the companies of the Group 1, regardless of the generic strategy adopted. The companies of the Group 2 that adopted the differentiation strategy seem to use mainly the ACR cost management practice. Our findings differ from those obtained by Chenhall insofar as companies that adopt low cost strategies tend to use managerial controls focused on cost control and rigid budgetary controls.

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.