Stable MPC for tracking with maximal domain of attraction

In this work, a stable MPC that maximizes the domain of attraction of the closed-loop system is proposed. The proposed approach is suitable to real applications in the sense that it accounts for the case of output tracking, it is offset free if the output target is reachable and minimizes the offset if some of the constraints are active at steady state. The new approach is based on the definition of a Minkowski functional related to the input and terminal constraints of the stable infinite horizon MPC. It is also shown that the domain of attraction is defined by the system model and the constraints, and it does not depend on the controller tuning parameters. The proposed controller is illustrated with small order examples of the control literature. (C) 2011 Elsevier Ltd. All rights reserved.

Robust integration of real time optimization with linear model predictive control

Here, we study the stable integration of real time optimization (RTO) with model predictive control (MPC) in a three layer structure. The intermediate layer is a quadratic programming whose objective is to compute reachable targets to the MPC layer that lie at the minimum distance to the optimum set points that are produced by the RTO layer. The lower layer is an infinite horizon MPC with guaranteed stability with additional constraints that force the feasibility and convergence of the target calculation layer. It is also considered the case in which there is polytopic uncertainty in the steady state model considered in the target calculation. The dynamic part of the MPC model is also considered unknown but it is assumed to be represented by one of the models of a discrete set of models. The efficiency of the methods presented here is illustrated with the simulation of a low order system. (C) 2010 Elsevier Ltd. All rights reserved.

Robust model predictive controller with output feedback and target tracking

A model predictive controller (MPC) is proposed, which is robustly stable for some classes of model uncertainty and to unknown disturbances. It is considered as the case of open-loop stable systems, where only the inputs and controlled outputs are measured. It is assumed that the controller will work in a scenario where target tracking is also required. Here, it is extended to the nominal infinite horizon MPC with output feedback. The method considers an extended cost function that can be made globally convergent for any finite input horizon considered for the uncertain system. The method is based on the explicit inclusion of cost contracting constraints in the control problem. The controller considers the output feedback case through a non-minimal state-space model that is built using past output measurements and past input increments. The application of the robust output feedback MPC is illustrated through the simulation of a low-order multivariable system.

Stable Model Predictive Control for Integrating Systems with Optimizing Targets

This paper concern the development of a stable model predictive controller (MPC) to be integrated with real time optimization (RTO) in the control structure of a process system with stable and integrating outputs. The real time process optimizer produces Optimal targets for the system inputs and for Outputs that Should be dynamically implemented by the MPC controller. This paper is based oil a previous work (Comput. Chem. Eng. 2005, 29, 1089) where a nominally stable MPC was proposed for systems with the conventional control approach where only the outputs have set points. This work is also based oil the work of Gonzalez et at. (J. Process Control 2009, 19, 110) where the zone control of stable systems is studied. The new control for is obtained by defining ail extended control objective that includes input targets and zone controller the outputs. Additional decision variables are also defined to increase the set of feasible solutions to the control problem. The hard constraints resulting from the cancellation of the integrating modes Lit the end of the control horizon are softened,, and the resulting control problem is made feasible to a large class of unknown disturbances and changes of the optimizing targets. The methods are illustrated with the simulated application of the proposed,approaches to a distillation column of the oil refining industry.

Enlarging the domain of attraction of stable MPC controllers, maintaining the output performance

This work presents an alternative way to formulate the stable Model Predictive Control (MPC) optimization problem that allows the enlargement of the domain of attraction, while preserving the controller performance. Based on the dual MPC that uses the null local controller, it proposed the inclusion of an appropriate set of slacked terminal constraints into the control problem. As a result, the domain of attraction is unlimited for the stable modes of the system, and the largest possible for the non-stable modes. Although this controller does not achieve local optimality, simulations show that the input and output performances may be comparable to the ones obtained with the dual MPC that uses the LQR as a local controller. (C) 2009 Elsevier Ltd. All rights reserved.

Robust model predictive control with zone control

Model predictive control (MPC) is usually implemented as a control strategy where the system outputs are controlled within specified zones, instead of fixed set points. One strategy to implement the zone control is by means of the selection of different weights for the output error in the control cost function. A disadvantage of this approach is that closed-loop stability cannot be guaranteed, as a different linear controller may be activated at each time step. A way to implement a stable zone control is by means of the use of an infinite horizon cost in which the set point is an additional variable of the control problem. In this case, the set point is restricted to remain inside the output zone and an appropriate output slack variable is included in the optimisation problem to assure the recursive feasibility of the control optimisation problem. Following this approach, a robust MPC is developed for the case of multi-model uncertainty of open-loop stable systems. The controller is devoted to maintain the outputs within their corresponding feasible zone, while reaching the desired optimal input target. Simulation of a process of the oil re. ning industry illustrates the performance of the proposed strategy.

A stable MPC with zone control

Several MPC applications implement a control strategy in which some of the system outputs are controlled within specified ranges or zones, rather than at fixed set points [J.M. Maciejowski, Predictive Control with Constraints, Prentice Hall, New Jersey, 2002]. This means that these outputs will be treated as controlled variables only when the predicted future values lie outside the boundary of their corresponding zones. The zone control is usually implemented by selecting an appropriate weighting matrix for the output error in the control cost function. When an output prediction is inside its zone, the corresponding weight is zeroed, so that the controller ignores this output. When the output prediction lies outside the zone, the error weight is made equal to a specified value and the distance between the output prediction and the boundary of the zone is minimized. The main problem of this approach, as long as stability of the closed loop is concerned, is that each time an output is switched from the status of non-controlled to the status of controlled, or vice versa, a different linear controller is activated. Thus, throughout the continuous operation of the process, the control system keeps switching from one controller to another. Even if a stabilizing control law is developed for each of the control configurations, switching among stable controllers not necessarily produces a stable closed loop system. Here, a stable M PC is developed for the zone control of open-loop stable systems. Focusing on the practical application of the proposed controller, it is assumed that in the control structure of the process system there is an upper optimization layer that defines optimal targets to the system inputs. The performance of the proposed strategy is illustrated by simulation of a subsystem of an industrial FCC system. (C) 2008 Elsevier Ltd. All rights reserved.

A Separation Principle for the Continuous-Time LQ-Problem With Markovian Jump Parameters

In this paper, we devise a separation principle for the finite horizon quadratic optimal control problem of continuous-time Markovian jump linear systems driven by a Wiener process and with partial observations. We assume that the output variable and the jump parameters are available to the controller. It is desired to design a dynamic Markovian jump controller such that the closed loop system minimizes the quadratic functional cost of the system over a finite horizon period of time. As in the case with no jumps, we show that an optimal controller can be obtained from two coupled Riccati differential equations, one associated to the optimal control problem when the state variable is available, and the other one associated to the optimal filtering problem. This is a separation principle for the finite horizon quadratic optimal control problem for continuous-time Markovian jump linear systems. For the case in which the matrices are all time-invariant we analyze the asymptotic behavior of the solution of the derived interconnected Riccati differential equations to the solution of the associated set of coupled algebraic Riccati equations as well as the mean square stabilizing property of this limiting solution. When there is only one mode of operation our results coincide with the traditional ones for the LQG control of continuous-time linear systems.

Adaptation for tandem cold mill models

The ideal conditions for the operation of tandem cold mills are connected to a set of references generated by models and used by dynamic regulators. Aiming at the optimization of the friction and yield stress coefficients an adaptation algorithm is proposed in this paper. Experimental results obtained from an industrial cold rolling mill are presented. (C) 2008 Elsevier B.V. All rights reserved.

Generalized Coupled Algebraic Riccati Equations for Discrete-time Markov Jump with Multiplicative Noise Systems

In this paper we consider the existence of the maximal and mean square stabilizing solutions for a set of generalized coupled algebraic Riccati equations (GCARE for short) associated to the infinite-horizon stochastic optimal control problem of discrete-time Markov jump with multiplicative noise linear systems. The weighting matrices of the state and control for the quadratic part are allowed to be indefinite. We present a sufficient condition, based only on some positive semi-definite and kernel restrictions on some matrices, under which there exists the maximal solution and a necessary and sufficient condition under which there exists the mean square stabilizing solution fir the GCARE. We also present a solution for the discounted and long run average cost problems when the performance criterion is assumed be composed by a linear combination of an indefinite quadratic part and a linear part in the state and control variables. The paper is concluded with a numerical example for pension fund with regime switching.

Determining the effect of grain size and maximum induction upon coercive field of electrical steels

Although theoretical models have already been proposed, experimental data is still lacking to quantify the influence of grain size upon coercivity of electrical steels. Some authors consider a linear inverse proportionality, while others suggest a square root inverse proportionality. Results also differ with regard to the slope of the reciprocal of grain size-coercive field relation for a given material. This paper discusses two aspects of the problem: the maximum induction used for determining coercive force and the possible effect of lurking variables such as the grain size distribution breadth and crystallographic texture. Electrical steel sheets containing 0.7% Si, 0.3% Al and 24 ppm C were cold-rolled and annealed in order to produce different grain sizes (ranging from 20 to 150 mu m). Coercive field was measured along the rolling direction and found to depend linearly on reciprocal of grain size with a slope of approximately 0.9 (A/m)mm at 1.0 T induction. A general relation for coercive field as a function of grain size and maximum induction was established, yielding an average absolute error below 4%. Through measurement of B(50) and image analysis of micrographs, the effects of crystallographic texture and grain size distribution breadth were qualitatively discussed. (C) 2011 Elsevier B.V. All rights reserved.

Modeling soil organic carbon dynamics in Oxisols of Ibiruba (Brazil) with the Century Model

introduction of conservation practices in degraded agricultural land will generally recuperate soil quality, especially by increasing soil organic matter. This aspect of soil organic C (SOC) dynamics under distinct cropping and management systems can be conveniently analyzed with ecosystem models such as the Century Model. In this study, Century was used to simulate SOC stocks in farm fields of the Ibiruba region of north central Rio Grande do Sul state in Southern Brazil. The region, where soils are predominantly Oxisols, was originally covered with subtropical woodlands and grasslands. SOC dynamics was simulated with a general scenario developed with historical data on soil management and cropping systems beginning with the onset of agriculture in 1900. From 1993 to 2050, two contrasting scenarios based on no-tillage soil management were established: the status quo scenario, with crops and agricultural inputs as currently practiced in the region and the high biomass scenario with increased frequency of corn in the cropping system, resulting in about 80% higher biomass addition to soils. Century simulations were in close agreement with SOC stocks measured in 2005 in the Oxisols with finer texture surface horizon originally under woodlands. However, simulations in the Oxisols with loamy surface horizon under woodlands and in the grassland soils were not as accurate. SOC stock decreased from 44% to 50% in fields originally under woodland and from 20% to 27% in fields under grasslands with the introduction of intensive annual grain crops with intensive tillage and harrowing operations. The adoption of conservation practices in the 1980s led to a stabilization of SOC stocks followed by a partial recovery of native stocks. Simulations to 2050 indicate that maintaining status quo would allow SOC stocks to recover from 81% to 86% of the native stocks under woodland and from 80% to 91 % of the native stocks under grasslands. Adoption of a high biomass scenario would result in stocks from 75% to 95% of the original stocks under woodlands and from 89% to 102% in the grasslands by 2050. These simulations outcomes underline the importance of cropping system yielding higher biomass to further increase SOC content in these Oxisols. This application of the Century Model could reproduce general trends of SOC loss and recovery in the Oxisols of the Ibiruba region. Additional calibration and validation should be conducted before extensive usage of Century as a support tool for soil carbon sequestration projects in this and other regions can be recommended. (C) 2009 Elsevier B.V. All rights reserved.

Bacterial communities and biogeochemical transformations of iron and sulfur in a high saltmarsh soil profile

Microbial community structure in saltmarsh soils is stratified by depth and availability of electron acceptors for respiration. However, the majority of the microbial species that are involved in the biogeochemical transformations of iron (Fe) and sulfur (S) in such environments are not known. Here we examined the structure of bacterial communities in a high saltmarsh soil profile and discuss their potential relationship with the geochemistry of Fe and S. Our data showed that the soil horizons Ag (oxic-suboxic), Bg (suboxic), Cri (anoxic with low concentration of pyrite Fe) and Cr-2 (anoxic with high concentrations of pyrite Fe) have distinct geochemical and microbiological characteristics. In general, total S concentration increased with depth and was correlated with the presence of pyrite Fe. Soluble + exchangable-Fe, pyrite Fe and acid volatile sulfide Fe concentrations also increased with depth, whereas ascorbate extractable-Fe concentrations decreased. The occurrence of reduced forms of Fe in the horizon Ag and oxidized Fe in horizon Cr-2 suggests that the typical redox zonation, common to several marine sediments, does not occur in the saltmarsh soil profile studied. Overall, the bacterial community structure in the horizon Ag and Cr-2 shared low levels of similarity, as compared to their adjacent horizons, Bg and Cr-1, respectively. The phylogenetic analyses of bacterial 16S rRNA gene sequences from clone libraries showed that the predominant phylotypes in horizon Ag were related to Alphaproteobacteria and Bacteroidetes. In contrast, the most abundant phylotypes in horizon Cr-2 were related to Deltaproteo-bacteria, Chloroflexi, Deferribacteres and Nitrospira. The high frequency of sequences with low levels of similarity to known bacterial species in horizons Ag and Cr-2 indicates that the bacterial communities in both horizons are dominated by novel bacterial species. (c) 2008 Elsevier Ltd. All rights reserved.

Inhibitory effects of Solidago chilensis Meyen hydroalcoholic extract on acute inflammation

Aim of the study: Alcoholic or hydroalcoholic preparations of the plant Solidago chilensis Meyen (Asteraceae) are employed in popular medicines to treat inflammation. The anti-inflammatory effects of the hydroalcoholic extract of aerial parts of the plant (93% ethanol) were investigated and the main components of the extract were identified. Materials and methods: Ear oedema was induced in male Wistar rats by topical application of the chloroform fraction of latex-extract from Euphorbia milii. Leukocyte mobilisation was quantified after air-pouch inflammation evoked by oyster glycogen. Leukocyte-endothelial interactions and mast cell degranulation were quantified by intravital microscopy. The extract itself was characterised via HPLC-DAD-MS and HPLC-MS/MS. Results: Topical (12.5-50 mg/kg) or intraperitoneal (25 or 50 mg/kg) administrations of the extract reduced ear oedema formation (>25% reduction). Intraperitoneal applications of 25 mg/kg of extract inhibited the migration of polymorphonuclear cells into the inflamed cavity (about 50%). In addition, the rolling behaviour and adherence of circulating leukocytes to postcapillary venules of the mesentery network was diminished (50%), but the mast cell degranulation in the perivascular area was not affected. The major components of the extract were identified as caffeoylquinic acid derivatives and the flavonoid rutin. Conclusions: The data presented herein show local and systemic anti-inflammatory effects of the hydroalcoholic extract of aerial parts of Solidago chilensis, and implicate the inhibition of leukocyte-endothelial interactions as an important mechanism of the extract`s action. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

Budlein A from Viguiera robusta inhibits leukocyte-endothelial cell interactions, adhesion molecule expression and inflammatory mediators release

Budlein A has been reported to exert some analgesic and anti-inflammatory properties. In this study, we have evaluated its effect on LPS-induced leukocyte recruitment in vivo and the mechanisms involved in its anti-inflammatory activity. In vivo, intravital videomicroscopy was used to determine the effects of budlein A on LPS-induced leukocyte-endothelial cell interactions in the murine cremasteric microcirculation. In vitro, the effects of budlein A on LPS-induced cytokine, chemokine and nitrites release, T-cell proliferative response as well as cell adhesion molecule expression (CAM) were evaluated. In vivo, intraperitoneal administration of budlein A (2.6 mM/kg) caused a significant reduction of LPS-induced leukocyte rolling flux, adhesion and emigration by 84, 92 and 96% respectively. In vitro, T-cell proliferative response was also affected by budlein A. When murine J774 macrophages were incubated with the sesquiterpene lactone, LPS-induced IL-1 beta, tumor necrosis factor-alpha (TNF-alpha) and keratinocyte-derived chemokine (KC) release were concentration-dependently inhibited. In human umbilical vein endothelial cells (HUVECs), budlein A also reduced the production of TNF-alpha, monocyte chemoattractant protein-1 (MCP-1), IL-8, nitrites and CAM expression elicited by LPS. Budlein A is a potent inhibitor of LPS-induced leukocyte accumulation in vivo. This effect appears to be mediated through inhibition of cytokine and chemokine release and down-regulation of CAM expression. Thus, it has potential therapeutic interest for the control of leukocyte recruitment that occurs in different inflammatory disorders. (C) 2009 Elsevier GrnbH. All rights reserved.