A greenhouse climate multivariable predictive controller

A multivariable predictive controller was implemented to regulate the air temperature, humidity and CO2 concentration for a greenhouse located in the north of Portugal. The controller outputs are computed in order to optimise the future behaviour of the greenhouse environment, concerning the set-point accuracy and the minimization of energy inputs.

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.

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.

Multivariable cluster analysis for high-speed industrial machinery

The overall operation and internal complexity of a particular production machinery can be depicted in terms of clusters of multidimensional points which describe the process states, the value in each point dimension representing a measured variable from the machinery. The paper describes a new cluster analysis technique for use with manufacturing processes, to illustrate how machine behaviour can be categorised and how regions of good and poor machine behaviour can be identified. The cluster algorithm presented is the novel mean-tracking algorithm, capable of locating N-dimensional clusters in a large data space in which a considerable amount of noise is present. Implementation of the algorithm on a real-world high-speed machinery application is described, with clusters being formed from machinery data to indicate machinery error regions and error-free regions. This analysis is seen to provide a promising step ahead in the field of multivariable control of manufacturing systems.

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.

Optimal design of smart structures using bonded piezoelectrics for vibration control

Smart material technology has become an area of increasing interest for the development of lighter and stronger structures which are able to incorporate actuator and sensor capabilities for collocated control. In the design of actively controlled structures, the determination of the actuator locations and the controller gains, is a very important issue. For that purpose, smart material modelling, modal analysis methods, control and optimization techniques are the most important ingredients to be taken into account. The optimization problem to be solved in this context presents two interdependent aspects. The first one is related to the discrete optimal actuator location selection problem, which is solved in this paper using genetic algorithms. The second is represented by a continuous variable optimization problem, through which the control gains are determined using classical techniques. A cantilever Euler-Bernoulli beam is used to illustrate the presented methodology.

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.

Architectures and design patterns for functional design of logic control and diagnostics in industrial automation

Recently in most of the industrial automation process an ever increasing degree of automation has been observed. This increasing is motivated by the higher requirement of systems with great performance in terms of quality of products/services generated, productivity, efficiency and low costs in the design, realization and maintenance. This trend in the growth of complex automation systems is rapidly spreading over automated manufacturing systems (AMS), where the integration of the mechanical and electronic technology, typical of the Mechatronics, is merging with other technologies such as Informatics and the communication networks. An AMS is a very complex system that can be thought constituted by a set of flexible working stations, one or more transportation systems. To understand how this machine are important in our society let considerate that every day most of us use bottles of water or soda, buy product in box like food or cigarets and so on. Another important consideration from its complexity derive from the fact that the the consortium of machine producers has estimated around 350 types of manufacturing machine. A large number of manufacturing machine industry are presented in Italy and notably packaging machine industry,in particular a great concentration of this kind of industry is located in Bologna area; for this reason the Bologna area is called “packaging valley”. Usually, the various parts of the AMS interact among them in a concurrent and asynchronous way, and coordinate the parts of the machine to obtain a desiderated overall behaviour is an hard task. Often, this is the case in large scale systems, organized in a modular and distributed manner. Even if the success of a modern AMS from a functional and behavioural point of view is still to attribute to the design choices operated in the definition of the mechanical structure and electrical electronic architecture, the system that governs the control of the plant is becoming crucial, because of the large number of duties associated to it. Apart from the activity inherent to the automation of themachine cycles, the supervisory system is called to perform other main functions such as: emulating the behaviour of traditional mechanical members thus allowing a drastic constructive simplification of the machine and a crucial functional flexibility; dynamically adapting the control strategies according to the different productive needs and to the different operational scenarios; obtaining a high quality of the final product through the verification of the correctness of the processing; addressing the operator devoted to themachine to promptly and carefully take the actions devoted to establish or restore the optimal operating conditions; managing in real time information on diagnostics, as a support of the maintenance operations of the machine. The kind of facilities that designers can directly find on themarket, in terms of software component libraries provides in fact an adequate support as regard the implementation of either top-level or bottom-level functionalities, typically pertaining to the domains of user-friendly HMIs, closed-loop regulation and motion control, fieldbus-based interconnection of remote smart devices. What is still lacking is a reference framework comprising a comprehensive set of highly reusable logic control components that, focussing on the cross-cutting functionalities characterizing the automation domain, may help the designers in the process of modelling and structuring their applications according to the specific needs. Historically, the design and verification process for complex automated industrial systems is performed in empirical way, without a clear distinction between functional and technological-implementation concepts and without a systematic method to organically deal with the complete system. Traditionally, in the field of analog and digital control design and verification through formal and simulation tools have been adopted since a long time ago, at least for multivariable and/or nonlinear controllers for complex time-driven dynamics as in the fields of vehicles, aircrafts, robots, electric drives and complex power electronics equipments. Moving to the field of logic control, typical for industrial manufacturing automation, the design and verification process is approached in a completely different way, usually very “unstructured”. No clear distinction between functions and implementations, between functional architectures and technological architectures and platforms is considered. Probably this difference is due to the different “dynamical framework”of logic control with respect to analog/digital control. As a matter of facts, in logic control discrete-events dynamics replace time-driven dynamics; hence most of the formal and mathematical tools of analog/digital control cannot be directly migrated to logic control to enlighten the distinction between functions and implementations. In addition, in the common view of application technicians, logic control design is strictly connected to the adopted implementation technology (relays in the past, software nowadays), leading again to a deep confusion among functional view and technological view. In Industrial automation software engineering, concepts as modularity, encapsulation, composability and reusability are strongly emphasized and profitably realized in the so-calledobject-oriented methodologies. Industrial automation is receiving lately this approach, as testified by some IEC standards IEC 611313, IEC 61499 which have been considered in commercial products only recently. On the other hand, in the scientific and technical literature many contributions have been already proposed to establish a suitable modelling framework for industrial automation. During last years it was possible to note a considerable growth in the exploitation of innovative concepts and technologies from ICT world in industrial automation systems. For what concerns the logic control design, Model Based Design (MBD) is being imported in industrial automation from software engineering field. Another key-point in industrial automated systems is the growth of requirements in terms of availability, reliability and safety for technological systems. In other words, the control system should not only deal with the nominal behaviour, but should also deal with other important duties, such as diagnosis and faults isolations, recovery and safety management. Indeed, together with high performance, in complex systems fault occurrences increase. This is a consequence of the fact that, as it typically occurs in reliable mechatronic systems, in complex systems such as AMS, together with reliable mechanical elements, an increasing number of electronic devices are also present, that are more vulnerable by their own nature. The diagnosis problem and the faults isolation in a generic dynamical system consists in the design of an elaboration unit that, appropriately processing the inputs and outputs of the dynamical system, is also capable of detecting incipient faults on the plant devices, reconfiguring the control system so as to guarantee satisfactory performance. The designer should be able to formally verify the product, certifying that, in its final implementation, it will perform itsrequired function guarantying the desired level of reliability and safety; the next step is that of preventing faults and eventually reconfiguring the control system so that faults are tolerated. On this topic an important improvement to formal verification of logic control, fault diagnosis and fault tolerant control results derive from Discrete Event Systems theory. The aimof this work is to define a design pattern and a control architecture to help the designer of control logic in industrial automated systems. The work starts with a brief discussion on main characteristics and description of industrial automated systems on Chapter 1. In Chapter 2 a survey on the state of the software engineering paradigm applied to industrial automation is discussed. Chapter 3 presentes a architecture for industrial automated systems based on the new concept of Generalized Actuator showing its benefits, while in Chapter 4 this architecture is refined using a novel entity, the Generalized Device in order to have a better reusability and modularity of the control logic. In Chapter 5 a new approach will be present based on Discrete Event Systems for the problemof software formal verification and an active fault tolerant control architecture using online diagnostic. Finally conclusive remarks and some ideas on new directions to explore are given. In Appendix A are briefly reported some concepts and results about Discrete Event Systems which should help the reader in understanding some crucial points in chapter 5; while in Appendix B an overview on the experimental testbed of the Laboratory of Automation of University of Bologna, is reported to validated the approach presented in chapter 3, chapter 4 and chapter 5. In Appendix C some components model used in chapter 5 for formal verification are reported.

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

QUESTIONS UNDER STUDY / PRINCIPLES: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Simulating the impact of four control strategies on the population dynamics of Neospora caninum infection in Swiss dairy cattle

A dynamic deterministic simulation model was developed to assess the impact of different putative control strategies on the seroprevalence of Neospora caninum in female Swiss dairy cattle. The model structure comprised compartments of "susceptible" and "infected" animals (SI-model) and the cattle population was divided into 12 age classes. A reference model (Model 1) was developed to simulate the current (status quo) situation (present seroprevalence in Switzerland 12%), taking into account available demographic and seroprevalence data of Switzerland. Model 1 was modified to represent four putative control strategies: testing and culling of seropositive animals (Model 2), discontinued breeding with offspring from seropositive cows (Model 3), chemotherapeutic treatment of calves from seropositive cows (Model 4), and vaccination of susceptible and infected animals (Model 5). Models 2-4 considered different sub-scenarios with regard to the frequency of diagnostic testing. Multivariable Monte Carlo sensitivity analysis was used to assess the impact of uncertainty in input parameters. A policy of annual testing and culling of all seropositive cattle in the population reduced the seroprevalence effectively and rapidly from 12% to <1% in the first year of simulation. The control strategies with discontinued breeding with offspring from all seropositive cows, chemotherapy of calves and vaccination of all cattle reduced the prevalence more slowly than culling but were still very effective (reduction of prevalence below 2% within 11, 23 and 3 years of simulation, respectively). However, sensitivity analyses revealed that the effectiveness of these strategies depended strongly on the quality of the input parameters used, such as the horizontal and vertical transmission factors, the sensitivity of the diagnostic test and the efficacy of medication and vaccination. Finally, all models confirmed that it was not possible to completely eradicate N. caninum as long as the horizontal transmission process was not interrupted.

Obesity and risk of multiple myeloma: A case-control study

Introduction. Several studies have reported a positive association of body mass index (BMI) with multiple myeloma; however, the period of adulthood where BMI is most important remains unclear. In addition, it is well known that body fat is associated with both sex-steroid hormone storage and with increasing insulin levels; therefore, it was hypothesized that the association between obesity and multiple myeloma may be attributed to increased aromatization of androgen in adipose tissue. Objective. The overall objective of this case-control study was to determine whether multiple myeloma cases had higher BMI and greater adult weight gain relative to healthy controls. In addition, we tested the hypothesis that hormone replacement therapy use among women will further increase the association between BMI and risk of multiple myeloma. This study used data from a pilot case-control study at M.D. Anderson Cancer Center (MDACC), entitled Etiology of multiple myeloma, directed by Dr. Sara Strom and Dr. Sergio Giralt. Methods. The pilot study recruited a total of 122 cases of histopathologically confirmed multiple myeloma from MDACC. Controls (n=183) were selected from a database of random digit dialing controls accrued in the Department of Epidemiology at MDACC and were frequency matched to the cases on age (±5 years), gender, and race/ethnicity. Demographic and risk factor information were obtained from all participants who completed a self-administered questionnaire. Items included in the questionnaire include demographic information, height and weight at age 25, 40 and current/diagnosis, medical history, family history of cancer, smoking and alcohol use. Statistical analysis. Initial descriptive analysis included Student's t-test and Pearson's chi-squared tests. Odds ratios and 95% confidence intervals were calculated to quantify the association between the variables of interest and multiple myeloma. A multivariable model will be developed using unconditional logistic regression. Results. MM cases were 1.79 times (95% CI=0.99-3.32) more likely to have been overweight or obese (BMI > 25 kg/m2) at age 25 relative to healthy controls after controlling for age, gender, race/ethnicty, education and family history of cancer. Being overweight or obese at age 40 was not significantly associated with mutliple myeloma risk (OR=1.42, 95% CI=0.86-2.34) nor was being overweight or obses at diagnosis (OR=1.43, 95% CI=0.78, 2.63). We observed a statistically significant 2-fold increased odds of multiple myeloma in individuals who gained more than 4.7 kg during between 25 and 40 years (OR=1.97, 95% CI=1.15-3.39). When assessing HRT as a modifier of the BMI and multiple myeloma association among women (N=123), no association between obesity and MM status was observed among women who have never used HRT (OR=0.60, 95% CI=0.23-1.61; n=73). Yet among women who have ever used HRT (n=50), being overweight or obese was associated with an increase in MM risk (OR=2. 93, 95% CI=0.81-10.6) after adjusting for age; however, the association was not statistically significant. Significance. This study provides further evidence that increased BMI increases the risk of multiple myeloma. Furthermore, among women, HRT use may modify risk of disease. ^