Cluster analysis for multivariable process control

This paper describes the novel use of cluster analysis in the field of industrial process control. The severe multivariable process problems encountered in manufacturing have often led to machine shutdowns, where the need for corrective actions arises in order to resume operation. Production faults which are caused by processes running in less efficient regions may be prevented or diagnosed using a reasoning based on cluster analysis. Indeed the intemal complexity of a production machinery may be depicted in clusters of multidimensional data points which characterise the manufacturing process. The application of a Mean-Tracking cluster algorithm (developed in Reading) to field data acquired from a high-speed machinery will be discussed. The objective of such an application is to illustrate how machine behaviour can be studied, in particular how regions of erroneous and stable running behaviour can be identified.

Inverted decoupling internal model control for square stable multivariable time delay systems

This paper presents a new tuning methodology of the main controller of an internal model control structure for n×n stable multivariable processes with multiple time delays based on the centralized inverted decoupling structure. Independently of the system size, very simple general expressions for the controller elements are obtained. The realizability conditions are provided and the specification of the closed-loop requirements is explained. A diagonal filter is added to the proposed control structure in order to improve the disturbance rejection without modifying the nominal set-point response. The effectiveness of the method is illustrated through different simulation examples in comparison with other works.

Desarrollo y aplicación de estrategias de control avanzado en procesos biológicos de tratamiento de efluentes contaminados

En este proyecto se ha desarrollado estrategias de control avanzadas para plantas de depuración de aguas residuales urbanas que eliminan conjuntamente materia orgánica, nitrógeno y fósforo. Las estrategias se han basado en el estudio multivariable del comportamiento del sistema, que ha producido subsidios para la utilización de lazos de control feedforward, de control predictivo y de un control de costes que automáticamente enviaba las consignas más adecuadas para los controladores de proceso. Para el desarrollo de las estrategias, se ha creado un sistema virtual de simulación (simulador) de plantas de depuradoras, basado en datos de literatura. Para el caso de una planta real, se ha desarrollado un simulador de la planta de Manresa (Catalunya). Sin embargo, el sistema de Manresa se ha utilizado exclusivamente para auxiliar los ingenieros de la planta en la tomada de decisiones de cambio de configuración para que la eliminación de fósforo se dé por la ruta biológica y no por la ruta química. La implementación de los simuladores ha permitido hacer muchas pruebas que en una planta real demandarían mucho tiempo y consumirían muchos recursos energéticos y financieros. Las estrategias de control más elaboradas han podido ahorrar hasta 150.000,00 Euros por año en relación a la operación de la planta sin el control automático. Cuanto a los estudios del modelo de la planta real, se concluyó que la eliminación biológica de fósforo puede sustituir el actual proceso químico de eliminación de fósforo, bajando los costes operacionales (costes del agente precipitante).

Control de márgenes quirúrgicos del carcinoma basocelular según la especialidad del cirujano

Introducción: el principal tratamiento del carcinoma basocelular (CBC) es la extirpación quirúrgica. Objetivo: determinar la prevalencia de márgenes afectados por el tumor, globalmente y en función del especialista que lo interviene. Métodos: se realizó un estudio retrospectivo de de los informes histológicos de CBC (enero de 2009 - marzo de 2010), un análisis estadístico (Chi-cuadrado de Pearson, U de Mann-Whitney, test de Kruskal-Wallis) y multivariable mediante regresión

Oral and general health-related quality of life in patients treated for oral cancer compared to control group.

BACKGROUND Health-related quality of life (HRQoL) is gaining importance as a valuable outcome measure in oral cancer area. The aim of this study was to assess the general and oral HRQoL of oral and oropharyngeal cancer patients 6 or more months after treatment and compare them with a population free from this disease. METHODS A cross-sectional study was carried out with patients treated for oral cancer at least 6 months post-treatment and a gender and age group matched control group. HRQoL was measured with the 12-Item Short Form Health Survey (SF-12); oral HRQoL (OHRQoL) was evaluated using the Oral Health Impact Profile (OHIP-14) and the Oral Impacts on Daily Performances (OIDP). Multivariable regression models assessed the association between the outcomes (SF-12, OHIP-14 and OIDP) and the exposure (patients versus controls), adjusting for sex, age, social class, functional tooth units and presence of illness. RESULTS For patients (n = 142) and controls (n = 142), 64.1% were males. The mean age was 65.2 (standard deviation (sd): 12.9) years in patients and 67.5 (sd: 13.7) years in controls. Patients had worse SF-12 Physical Component Summary scores than controls even in fully the adjusted model [β-coefficient = -0.11 (95% CI: -5.12-(-0.16)]. The differences in SF-12 Mental Component Summary were not statistically significant. Regarding OHRQoL patients had 11.63 (95% CI: 6.77-20.01) higher odds for the OHIP-14 and 21.26 (95% CI: 11.54-39.13) higher odds for OIDP of being in a worse category of OHRQoL compared to controls in the fully adjusted model. CONCLUSION At least 6 months after treatment, oral cancer patients had worse OHRQoL, worse physical HRQoL and similar psychological HRQoL than the general population.

A Nested Case-Control Study of Metabolically Defined Body Size Phenotypes and Risk of Colorectal Cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC).

BACKGROUND Obesity is positively associated with colorectal cancer. Recently, body size subtypes categorised by the prevalence of hyperinsulinaemia have been defined, and metabolically healthy overweight/obese individuals (without hyperinsulinaemia) have been suggested to be at lower risk of cardiovascular disease than their metabolically unhealthy (hyperinsulinaemic) overweight/obese counterparts. Whether similarly variable relationships exist for metabolically defined body size phenotypes and colorectal cancer risk is unknown. METHODS AND FINDINGS The association of metabolically defined body size phenotypes with colorectal cancer was investigated in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolic health/body size phenotypes were defined according to hyperinsulinaemia status using serum concentrations of C-peptide, a marker of insulin secretion. A total of 737 incident colorectal cancer cases and 737 matched controls were divided into tertiles based on the distribution of C-peptide concentration amongst the control population, and participants were classified as metabolically healthy if below the first tertile of C-peptide and metabolically unhealthy if above the first tertile. These metabolic health definitions were then combined with body mass index (BMI) measurements to create four metabolic health/body size phenotype categories: (1) metabolically healthy/normal weight (BMI < 25 kg/m2), (2) metabolically healthy/overweight (BMI ≥ 25 kg/m2), (3) metabolically unhealthy/normal weight (BMI < 25 kg/m2), and (4) metabolically unhealthy/overweight (BMI ≥ 25 kg/m2). Additionally, in separate models, waist circumference measurements (using the International Diabetes Federation cut-points [≥80 cm for women and ≥94 cm for men]) were used (instead of BMI) to create the four metabolic health/body size phenotype categories. Statistical tests used in the analysis were all two-sided, and a p-value of <0.05 was considered statistically significant. In multivariable-adjusted conditional logistic regression models with BMI used to define adiposity, compared with metabolically healthy/normal weight individuals, we observed a higher colorectal cancer risk among metabolically unhealthy/normal weight (odds ratio [OR] = 1.59, 95% CI 1.10-2.28) and metabolically unhealthy/overweight (OR = 1.40, 95% CI 1.01-1.94) participants, but not among metabolically healthy/overweight individuals (OR = 0.96, 95% CI 0.65-1.42). Among the overweight individuals, lower colorectal cancer risk was observed for metabolically healthy/overweight individuals compared with metabolically unhealthy/overweight individuals (OR = 0.69, 95% CI 0.49-0.96). These associations were generally consistent when waist circumference was used as the measure of adiposity. To our knowledge, there is no universally accepted clinical definition for using C-peptide level as an indication of hyperinsulinaemia. Therefore, a possible limitation of our analysis was that the classification of individuals as being hyperinsulinaemic-based on their C-peptide level-was arbitrary. However, when we used quartiles or the median of C-peptide, instead of tertiles, as the cut-point of hyperinsulinaemia, a similar pattern of associations was observed. CONCLUSIONS These results support the idea that individuals with the metabolically healthy/overweight phenotype (with normal insulin levels) are at lower colorectal cancer risk than those with hyperinsulinaemia. The combination of anthropometric measures with metabolic parameters, such as C-peptide, may be useful for defining strata of the population at greater risk of colorectal cancer.

Hematopoietic stem cell transplantation in Switzerland: a comprehensive quality control report on centre effect.

Interest groups advocate centre-specific outcome data as a useful tool for patients in choosing a hospital for their treatment and for decision-making by politicians and the insurance industry. Haematopoietic stem cell transplantation (HSCT) requires significant infrastructure and represents a cost-intensive procedure. It therefore qualifies as a prime target for such a policy. We made use of the comprehensive database of the Swiss Blood Stem Cells Transplant Group (SBST) to evaluate potential use of mortality rates. Nine institutions reported a total of 4717 HSCT - 1427 allogeneic (30.3%), 3290 autologous (69.7%) - in 3808 patients between the years 1997 and 2008. Data were analysed for survival- and transplantation-related mortality (TRM) at day 100 and at 5 years. The data showed marked and significant differences between centres in unadjusted analyses. These differences were absent or marginal when the results were adjusted for disease, year of transplant and the EBMT risk score (a score incorporating patient age, disease stage, time interval between diagnosis and transplantation, and, for allogeneic transplants, donor type and donor-recipient gender combination) in a multivariable analysis. These data indicate comparable quality among centres in Switzerland. They show that comparison of crude centre-specific outcome data without adjustment for the patient mix may be misleading. Mandatory data collection and systematic review of all cases within a comprehensive quality management system might, in contrast, serve as a model to ascertain the quality of other cost-intensive therapies in Switzerland.

Impact of tight glycemic control on cerebral glucose metabolism after severe brain injury: a microdialysis study.

OBJECTIVES: To analyze the effect of tight glycemic control with the use of intensive insulin therapy on cerebral glucose metabolism in patients with severe brain injury. DESIGN: Retrospective analysis of a prospective observational cohort. SETTING: University hospital neurologic intensive care unit. PATIENTS: Twenty patients (median age 59 yrs) monitored with cerebral microdialysis as part of their clinical care. INTERVENTIONS: Intensive insulin therapy (systemic glucose target: 4.4-6.7 mmol/L [80-120 mg/dL]). MEASUREMENTS AND MAIN RESULTS: Brain tissue markers of glucose metabolism (cerebral microdialysis glucose and lactate/pyruvate ratio) and systemic glucose were collected hourly. Systemic glucose levels were categorized as within the target "tight" (4.4-6.7 mmol/L [80-120 mg/dL]) vs. "intermediate" (6.8-10.0 mmol/L [121-180 mg/dL]) range. Brain energy crisis was defined as a cerebral microdialysis glucose <0.7 mmol/L with a lactate/pyruvate ratio >40. We analyzed 2131 cerebral microdialysis samples: tight systemic glucose levels were associated with a greater prevalence of low cerebral microdialysis glucose (65% vs. 36%, p < 0.01) and brain energy crisis (25% vs.17%, p < 0.01) than intermediate levels. Using multivariable analysis, and adjusting for intracranial pressure and cerebral perfusion pressure, systemic glucose concentration (adjusted odds ratio 1.23, 95% confidence interval [CI] 1.10-1.37, for each 1 mmol/L decrease, p < 0.001) and insulin dose (adjusted odds ratio 1.10, 95% CI 1.04-1.17, for each 1 U/hr increase, p = 0.02) independently predicted brain energy crisis. Cerebral microdialysis glucose was lower in nonsurvivors than in survivors (0.46 +/- 0.23 vs. 1.04 +/- 0.56 mmol/L, p < 0.05). Brain energy crisis was associated with increased mortality at hospital discharge (adjusted odds ratio 7.36, 95% CI 1.37-39.51, p = 0.02). CONCLUSIONS: In patients with severe brain injury, tight systemic glucose control is associated with reduced cerebral extracellular glucose availability and increased prevalence of brain energy crisis, which in turn correlates with increased mortality. Intensive insulin therapy may impair cerebral glucose metabolism after severe brain injury.

Multivariate Statistical Process Control and Case-Based Reasoning for situation assessment of Sequencing Batch Reactors

ABSRACT This thesis focuses on the monitoring, fault detection and diagnosis of Wastewater Treatment Plants (WWTP), which are important fields of research for a wide range of engineering disciplines. The main objective is to evaluate and apply a novel artificial intelligent methodology based on situation assessment for monitoring and diagnosis of Sequencing Batch Reactor (SBR) operation. To this end, Multivariate Statistical Process Control (MSPC) in combination with Case-Based Reasoning (CBR) methodology was developed, which was evaluated on three different SBR (pilot and lab-scales) plants and validated on BSM1 plant layout.

A hyperstable neural network for the modelling and control of nonlinear systems

A multivariable hyperstable robust adaptive decoupling control algorithm based on a neural network is presented for the control of nonlinear multivariable coupled systems with unknown parameters and structure. The Popov theorem is used in the design of the controller. The modelling errors, coupling action and other uncertainties of the system are identified on-line by a neural network. The identified results are taken as compensation signals such that the robust adaptive control of nonlinear systems is realised. Simulation results are given.

Mitigation of symmetry condition in positive realness for adaptive control

Feasibility of nonlinear and adaptive control methodologies in multivariable linear time-invariant systems with state-space realization (A, B, C) is apparently limited by the standard strictly positive realness conditions that imply that the product CB must be positive definite symmetric. This paper expands the applicability of the strictly positive realness conditions used for the proofs of stability of adaptive control or control with uncertainty by showing that the not necessarily symmetric CB is only required to have a diagonal Jordan form and positive eigenvalues. The paper also shows that under the new condition any minimum-phase systems can be made strictly positive real via constant output feedback. The paper illustrates the usefulness of these extended properties with an adaptive control example. (C) 2006 Elsevier Ltd. All rights reserved.

Case-case-control study of risk factors for nasopharyngeal colonization with methicillin-resistant Staphylococcus aureus in a medical-surgical intensive care unit

Nasopharyngeal colonization with methicillin-resistant Staphylococcus aureus (MRSA) often precedes the development of nosocomial infections. In order to identify risk factors for MRSA colonization, we conducted a case-case-control study, enrolling 122 patients admitted to a medical-surgical intensive care unit (ICU). All patients had been screened for nasopharyngeal colonization with S. aureus upon admission and weekly thereafter. Two case-control studies were performed, using as cases patients who acquired colonization with MRSA and methicillin-susceptible S. aureus (MSSA), respectively. For both studies, patients in whom colonization was not detected during ICU stay were selected as control subjects. Several potential risk factors were assessed in univariate and multivariable (logistic regression) analysis. MRSA and MSSA were recovered from nasopharyngeal samples from 27 and 10 patients, respectively. Independent risk factors for MRSA colonization were: length-of-stay in the ICU (Odds Ratio [OR]=1.12, 95%Confidence Interval[CI]=1.06-1.19, p<0.001) and use of ciprofloxacin (OR=5.05, 95%CI=1.38-21.90, p=0.015). The use of levofloxacin had a protective effect (OR=0.08, 95%CI=0.01-0.55, p=0.01). Colonization with MSSA was positively associated with central nervous system disease (OR=7.45, 95%CI=1.33-41.74, p=0.02) and negatively associated with age (OR=0.94, 95%CI=0.90-0.99, p=0.01). In conclusion, our study suggests a role for both cross-transmission and selective pressure of antimicrobials in the spread of MRSA.

Robust state-derivative feedback LMI-based designs for multivariable linear systems

In some practical problems, for instance in the control systems for the suppression of vibration in mechanical systems, the state-derivative signals are easier to obtain than the state signals. New necessary and sufficient linear matrix inequalities (LMI) conditions for the design of state-derivative feedback for multi-input (MI) linear systems are proposed. For multi-input/multi-output (MIMO) linear time-invariant or time-varying plants, with or without uncertainties in their parameters, the proposed methods can include in the LMI-based control designs the specifications of the decay rate, bounds on the output peak, and bounds on the state-derivative feedback matrix K. These design procedures allow new specifications and also, they consider a broader class of plants than the related results available in the literature. The LMIs, when feasible, can be efficiently solved using convex programming techniques. Practical applications illustrate the efficiency of the proposed methods.

Necessary and sufficient condition for generalized passivity, passification and application to multivariable adaptive systems

Recently, a generalized passivity concept for linear multivariable systems was obtained which allows circumventing the restrictiveness of the usual passivity concept. The latter is associated with the classical SPR (Strictly Positive Real) condition whereas the new concept of passivity is associated with the so called WSPR condition and its advantage in multivariable systems is that it does not require a restrictive symmetry condition of SPR systems. As a result, it allows the design of multivariable adaptive control that, unlike some existing factorization approaches, does not imply in additional overparameterization of the adaptive controller. In this paper, we complete a previously established WSPR sufficient condition and prove that it is also necessary. We also propose some methods of passification by either premultiplying the system output tracking error vector or the system input vector by an adequate passifying matrix multiplier, so that the resulting input/output transfer function becomes WSPR. The efficiency of our proposals are illustrated by simulation utilizing a well known robotics adaptive visual servoing problem. © 2011 IFAC.

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.