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.

Real time optimization (RTO) with model predictive control (MPC)

This paper studies a simplified methodology to integrate the real time optimization (RTO) of a continuous system into the model predictive controller in the one layer strategy. The gradient of the economic objective function is included in the cost function of the controller. Optimal conditions of the process at steady state are searched through the use of a rigorous non-linear process model, while the trajectory to be followed is predicted with the use of a linear dynamic model, obtained through a plant step test. The main advantage of the proposed strategy is that the resulting control/optimization problem can still be solved with a quadratic programming routine at each sampling step. Simulation results show that the approach proposed may be comparable to the strategy that solves the full economic optimization problem inside the MPC controller where the resulting control problem becomes a non-linear programming problem with a much higher computer load. (C) 2010 Elsevier Ltd. All rights reserved.

Optimizing model predictive control of an industrial distillation column

The main scope of this work is the implementation of an MPC that integrates the control and the economic optimization of the system. The two problems are solved simultaneously through the modification of the control cost function that includes an additional term related to the economic objective. The optimizing MPC is based on a quadratic program (QP) as the conventional MPC and can be solved with the available QP solvers. The method was implemented in an industrial distillation system, and the results show that the approach is efficient and can be used, in several practical cases. (C) 2011 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.

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.

Identification of protein coding regions using the modified Gabor-wavelet transform

An important topic in genomic sequence analysis is the identification of protein coding regions. In this context, several coding DNA model-independent methods based on the occurrence of specific patterns of nucleotides at coding regions have been proposed. Nonetheless, these methods have not been completely suitable due to their dependence on an empirically predefined window length required for a local analysis of a DNA region. We introduce a method based on a modified Gabor-wavelet transform (MGWT) for the identification of protein coding regions. This novel transform is tuned to analyze periodic signal components and presents the advantage of being independent of the window length. We compared the performance of the MGWT with other methods by using eukaryote data sets. The results show that MGWT outperforms all assessed model-independent methods with respect to identification accuracy. These results indicate that the source of at least part of the identification errors produced by the previous methods is the fixed working scale. The new method not only avoids this source of errors but also makes a tool available for detailed exploration of the nucleotide occurrence.

Coding Strategies of Indirect Reported Speech in Typological Perspective

The purpose of this paper is to provide a cross-linguistic survey of the variation of coding strategies that are available for the grammatical distinction between direct and indirect speech representation with a particular focus on the expression of indirect reported speech. Cross-linguistic data from a sample of 42 languages will be provided to illustrate the range of available grammatical coding strategies.

The expression of messenger RNAs coding for growth factors, their receptors, and eph-class receptor tyrosine kinases in normal and ototoxically damaged chick cochleae

Messenger RNAs coding for growth factors and receptor tyrosine kinases were measured by quantitative competitive and by semi-quantitative reverse-transcription polymerase chain reaction in whole and dissected chick inner ears. The fibroblast growth factor (FGF) receptor 1 chick embryonic kinase (CEK) 1 was expressed in all structures examined (otocyst, hatchling whole cochlea, cochlear nerve ganglion, and cochlear and vestibular sensory epithelia), although slightly more heavily in the otocyst. The related fibroblast growth factor receptors CEK 2 and 3 were preferentially expressed in the nerve ganglion and in the vestibular sensory epithelium, respectively. FGF 1 mRNA was low in early development, increasing to mature levels at around embryonic age 11 days, while FGF2, mRNA was expressed at constant levels at all ages. In response to ototoxic damage, FGF1 mRNA levels were increased in the early damaged cochlear sensory epithelium. Immunohistochemistry for CEK1 showed that normal hair cells expressed the receptor heavily on the hair cell stereocilia, while with early damage, CEK1 came to be expressed heavily on the apical surfaces of the supporting cells. In normal chicks, the CEK4 and CEK8 eph-class receptor tyrosine kinases were expressed relatively heavily by the cochlear nerve ganglion, and CEK10 was expressed relatively heavily by the cochlear hair cell sensory epithelium. The results suggest that the FGF system may be involved in the response of the cochlear epithelium to ototoxic damage. The eph-class receptor tyrosine kinase CEK10 may be involved in cell interactions in the cochlear sensory epithelium, while CEK4 and CEK8 may play a role in the cochlear innervation.

Nucleotide sequence of the nifH gene coding for nitrogen reductase in the acetic acid bacterium Acetobacter diazotrophicus

The nifH gene sequence of the nitrogen-fixing bacterium Acetobacter diazotrophicus was determined with the use of the polymerase chain reaction and universal degenerate oligonucleotide primers. The gene shows highest pair-wise similarity to the nifH gene of Azospirillum brasilense. The phylogenetic relationships of the nifH gene sequences were compared with those inferred from 16S rRNA gene sequences. Knowledge of the sequence of the nifH gene contributes to the growing database of nifH gene sequences, and will allow the detection of Acet. diazotrophicus from environmental samples with nifH gene-based primers.

The critical power function is dependent on the duration of the predictive exercise tests chosen

The linear relationship between work accomplished (W-lim) and time to exhaustion (t(lim)) can be described by the equation: W-lim = a + CP.t(lim). Critical power (CP) is the slope of this line and is thought to represent a maximum rate of ATP synthesis without exhaustion, presumably an inherent characteristic of the aerobic energy system. The present investigation determined whether the choice of predictive tests would elicit significant differences in the estimated CP. Ten female physical education students completed, in random order and on consecutive days, five art-out predictive tests at preselected constant-power outputs. Predictive tests were performed on an electrically-braked cycle ergometer and power loadings were individually chosen so as to induce fatigue within approximately 1-10 mins. CP was derived by fitting the linear W-lim-t(lim) regression and calculated three ways: 1) using the first, third and fifth W-lim-t(lim) coordinates (I-135), 2) using coordinates from the three highest power outputs (I-123; mean t(lim) = 68-193 s) and 3) using coordinates from the lowest power outputs (I-345; mean t(lim) = 193-485 s). Repeated measures ANOVA revealed that CPI123 (201.0 +/- 37.9W) > CPI135 (176.1 +/- 27.6W) > CPI345 (164.0 +/- 22.8W) (P < 0.05). When the three sets of data were used to fit the hyperbolic Power-t(lim) regression, statistically significant differences between each CP were also found (P < 0.05). The shorter the predictive trials, the greater the slope of the W-lim-t(lim) regression; possibly because of the greater influence of 'aerobic inertia' on these trials. This may explain why CP has failed to represent a maximal, sustainable work rate. The present findings suggest that if CP is to represent the highest power output that an individual can maintain for a very long time without fatigue then CP should be calculated over a range of predictive tests in which the influence of aerobic inertia is minimised.

Strategies of accommodation: Development of a coding system for conversational interaction

This study describes a coding system developed to operationalize the sociolinguistic strategies proposed by communication accommodation theory (CAT) in an academic context. Fifty interactions between two students (of Australian or Chinese ethnic background) or a student and faculty member were videotaped. A turn- and episode-based coding system was developed, focusing on verbal and nonverbal behavior. The development of this system is described in detail, before results are presented. Results indicated that status was the main influence on choice of strategies, particularly the extent and type of discourse management and interpersonal control. Participants' sew and ethnicity also played a role: Male participants made more use of interpretability (largely questions), whereas female participants used discourse management to develop a shared perspective. The results make clear that there is no automatic correspondence between behaviors and the strategies they constitute, and they point to the appropriateness of conceptualizing behavior and strategies separately in CAT.

The novel mitochondrial gene arrangement of the cattle tick, Boophilus microplus: Fivefold tandem repetition of a coding region

We sequenced across all of the gene boundaries in the mitochondrial genome of the cattle tick, Boophilus microplus, to determine the arrangement of its genes. The mtDNA of B. microplus has a coding region, composed of tRNA(Glu) and 60 bp of the 3' end of ND1, that is repeated five times. Boophilus microplus is the first coelomate animal known to have more than two copies of a coding sequence. The mitochondrial genome of B, microplus has other unusual features, including (1) reduced T arms in tRNAs, (2) an AT bias in codon use, (3) two control regions that have evolved in concert, (4) three gene rearrangements, and (5) a stem-loop between tRNA(Gln) and tRNA(Phe). The short T arms and small control regions (CRs) of B. microplus and other ticks suggest strong selection for small genomes. Imprecise termination of replication beyond its origin, which can account for the evolution of tandem repeats of coding regions in other mitochondrial genomes, cannot explain the evolution of the fivefold repeated sequence in the mitochondrial genome of B. microplus. Instead, slipped-strand mispairing or recombination are the most plausible explanations for the evolution of these tandem repeats.

A landscape-scale test of the predictive ability of a spatially explicit model for population viability analysis

1. Although population viability analysis (PVA) is widely employed, forecasts from PVA models are rarely tested. This study in a fragmented forest in southern Australia contrasted field data on patch occupancy and abundance for the arboreal marsupial greater glider Petauroides volans with predictions from a generic spatially explicit PVA model. This work represents one of the first landscape-scale tests of its type. 2. Initially we contrasted field data from a set of eucalypt forest patches totalling 437 ha with a naive null model in which forecasts of patch occupancy were made, assuming no fragmentation effects and based simply on remnant area and measured densities derived from nearby unfragmented forest. The naive null model predicted an average total of approximately 170 greater gliders, considerably greater than the true count (n = 81). 3. Congruence was examined between field data and predictions from PVA under several metapopulation modelling scenarios. The metapopulation models performed better than the naive null model. Logistic regression showed highly significant positive relationships between predicted and actual patch occupancy for the four scenarios (P = 0.001-0.006). When the model-derived probability of patch occupancy was high (0.50-0.75, 0.75-1.00), there was greater congruence between actual patch occupancy and the predicted probability of occupancy. 4. For many patches, probability distribution functions indicated that model predictions for animal abundance in a given patch were not outside those expected by chance. However, for some patches the model either substantially over-predicted or under-predicted actual abundance. Some important processes, such as inter-patch dispersal, that influence the distribution and abundance of the greater glider may not have been adequately modelled. 5. Additional landscape-scale tests of PVA models, on a wider range of species, are required to assess further predictions made using these tools. This will help determine those taxa for which predictions are and are not accurate and give insights for improving models for applied conservation management.

Inter-subband redundancy prediction using neural network for video coding

High performance video codec is mandatory for multimedia applications such as video-on-demand and video conferencing. Recent research has proposed numerous video coding techniques to meet the requirement in bandwidth, delay, loss and Quality-of-Service (QoS). In this paper, we present our investigations on inter-subband self-similarity within the wavelet-decomposed video frames using neural networks, and study the performance of applying the spatial network model to all video frames over time. The goal of our proposed method is to restore the highest perceptual quality for video transmitted over a highly congested network. Our contributions in this paper are: (1) A new coding model with neural network based, inter-subband redundancy (ISR) prediction for video coding using wavelet (2) The performance of 1D and 2D ISR prediction, including multiple levels of wavelet decompositions. Our result shows a short-term quality enhancement may be obtained using both 1D and 2D ISR prediction.