Dissertations / Theses on the topic 'Sensitivity to Uncertain Threat'

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In field experiments with subjects living either inside or outside Brazilian slums (n=955), we show that consumers living in slums are less price sensitive, in opposition with recent price sensitivity research. Comparing slum and non-slum dwellers, we found that negatively stereotyped consumers (e.g. slum dwellers) were more likely to pay higher amounts for friendlier customer service when facing social identity threats (SITs) in marketplaces such as banks. The mechanism which makes them less price sensitive is related to the perception of how other people evaluate their social groups, and we argue that they pay more because they are seeking identity-safe commercial relationships. This work, besides extending the literature in SITs, presents a perspective for the exchange between economics and psychology on price sensitivity, showing that consumers living in slums are willing to pay more to avoid possibly social identity threating experiences.

The aim of this study was to examine whether three different psychological predictors; Health anxiety (SHAI), Disgust sensitivity (DS-R) and intolerance of uncertainty (IUS-12) could predict COVID-19-related anxiety in students at Orebro University, Sweden. It was hypothesized that there would be a significant relationship between the three psychological behaviors and pandemic-related anxiety. An online survey, consisting of both standardized and non-standardized questionnaires, was constructed. The survey was completed by 199 participants, aged between 19-48 (M = 25.14 and SD = 5.35) from Orebro University, Sweden through Limesurvey. A correlation revealed that Health anxiety and Disgust sensitivity were significantly correlated with COVID-19-related anxiety. The regression analysis revealed that there was a significance between the three psychological behaviors and COVID-19-related anxiety. In conclusion, Health anxiety, Disgust sensitivity and intolerance of uncertainty, could indeed be associated with COVID-19-related anxiety in the students.
Syftet med studien är att examinera huruvida tre olika psykologiska beteenden; Health anxiety (SHAI), Disgust sensitivity (DS-R) och Intolerance of uncertainty (IUS-12) kan förutse COVID-19-relaterad ångest i studenter på Örebro Universitet. Det hypotiserades att det skulle finnas en signifikant relation baserat på tidigare studier. En online enkät, med både standardiserade och icke-standardiserade frågeformulär, konstruerades. Antal deltagare som kompletterade enkäten genom Limesurvey var 199 studenter mellan åldrarna 19–48 (M = 25.14 och SD = 5.35) från Örebro Universitet. Genom en korrelationsanalys kunde man se att både Health anxiety och Disgust sensitivity var signifikant korrelerade med COVID-19-relaterad Pandemi. Avslutningsvis, en multipel regressionsanalys visade att Health anxiety, Disgust sensitivity och Intolerance of uncertainty var signifikant relaterat med COVID-19-relaterad ångest i studenterna.

The deployment of offshore wind farms (OWFs) has increased in response to the threat of diminishing fossil fuel resources, climate change and the need for security of supply. The cost of offshore wind generation has not reached parity with established forms of electricity production. Operators need to simultaneously decrease the total project costs and increase energy yield to achieve a levelised cost of energy of £100/MWh. However, aspects of the Operations and Maintenance (O&M) remain uncertain, either through stochastic processes or through inexperience in the field. One way to handle uncertainty is to define how much the variance in these aspects affect the cost and availability. The thesis in hand introduces an O&M model and seeks to quantify the effects of uncertain inputs using complex sensitivity analysis methods. The sensitivity analysis is applied to an O&M computer simulation model for offshore wind that was developed prior to this project. Case study OWFs are identified to assess if the important factors are different when projects are comprised of a large number of wind turbine generators (WTGs) and are further offshore from the O&M hub port. The set of cases for the global sensitivity analysis comprises of three projects, to provide information applicable to the industry and demonstrate pertinence of sensitivity analysis on a case by case basis. A screening analysis, using the Morris method, is conducted to identify the most important factors on project cost and availability. This resulted in a list of twenty factors, relating to failure rates; duration of operations and information relating to vessels costs. An in-depth uncertainty analysis is conducted with the important factors to establish their distributions where possible. A global, variance-based sensitivity analysis, using the Sobol’ method, is performed to quantify the effect on the variance of the two outputs. No single factor dominated the effect on O&M cost and availability for all cases. For each case, one to five factors contributed most to output variances. As an example, for a case of 30 WTGs located 20km offshore from the O&M hub port, the output variances are mainly a result of the change of number of crew transfer vessels and heavy lift vessel mobilisation time for nacelle component replacement. For an OWF with more WTGs, further from shore; the availability variance is dominated by more routine repair operations. Moreover, costs are largely dominated by WTG reliability. This work has confirmed that O&M costs are affected by the cost of deploying heavy-lift vessels even though only a small proportion of repairs require them. Significant factors are inconsistent across all the scenarios, supporting the conclusion that sensitivity analysis of each case is a necessary part of O&M costs and availability simulation. Using the most up-to-date information on current O&M practices, the analysis provides an indication of where to focus efforts for O&M cost reduction and improved availability.

Based on existing theories of personality and socio-emotional functioning (e.g. Clark, 2005; Lynch, Hempel & Clark, in press) a new model is proposed and tested. The model hypothesises that (i) temperament (reward and threat sensitivity) and childhood invalidation predict problems with interpersonal functioning, (ii) this effect is mediated by self-regulatory capacity; where self-regulatory capacity comprises self-control (ranging from emotional over-control to emotional under-control) and flexible control and (iii) self-regulatory capacity itself has a quadratic relationship with interpersonal functioning. A UK community sample (n= 512) completed a self-report survey, measuring each of the aforementioned latent variables. Structural equation modelling (SEM) was used to determine the goodness-of-fit of this and variations of this model. SEM identified that a non-mediation model provided the best fit (χ²=49.403, p< 0.001; CFI=0.98; RMSEA=0.056). Good-fit was obtained for a model including flexible control as a partial mediator (χ²=269.06, p< 0.001; CFI=0.956; RMSEA=0.081) and adequate-fit for a model including over-control as a partial mediator (χ²= 91.744, p < 0.001, CFI=0.932; RMSEA= 0.096). Correlation analyses suggested that over-control and under-control correlated positively with interpersonal problems. Results from SEM provided promising initial evidence for the mediating role of self-regulatory capacity, particularly for the flexible control component. Correlation analyses provided support for the non-linear relationship between self-regulatory capacity and interpersonal functioning, whereby extreme over-control or extreme under-control is associated with interpersonal problems. Findings have implications for identifying mechanisms of change for therapeutic approaches to emotion dysregulation and for understanding the over-controlled population, which has previously been overlooked.

This thesis examines the validity of polyvagal theory as a model of normal socio-emotional responding (Porges, 1995, 2001, 2003a). Polyvagal theory makes several claims, and to date many of its predictions lack empirical testing. In the current research, five main hypotheses stemming from polyvagal theory were identified and tested using healthy participants. The initial empirical study examined the influence of laboratory stressors on autonomic function. The findings revealed that social evaluative threat increases activation of the sympathetic nervous system more than a virtual reality maze, and that arousal remains elevated for longer during anticipation of social evaluative threat in comparison to recovery from social evaluative threat. The second study investigated the effects of emotion regulation strategies on autonomic function, and highlighted the effectiveness of two meditation practices in reducing defensive physiological arousal and increasing subjective positive emotion. These studies were followed with a set of studies designed to evaluate the effects of defensive physiological arousal on socio-emotional functioning, as a direct test of polyvagal theory. The first study examined the effects of a laboratory stressor on facial expressivity, revealing that social evaluative threat had little impact on expressive regulation. A second study investigated the effects of a laboratory stressor on emotional sensitivity and spontaneous facial mimicry. Some limited support was found for polyvagal theory, although neither emotional sensitivity nor facial mimicry was significantly affected by laboratory stress. A final empirical study investigated the effects of a laboratory stressor on affiliation tendencies. The laboratory stressor did not influence participants’ willingness to spend time with others, however the experiment did reveal significant relationships between markers of social safeness and affiliation. The overall conclusion of this thesis is that polyvagal may not be a representative model of socio-emotional functioning in healthy participants. The implications of these findings are discussed in relation to the validity of polyvagal theory as a universal model of socio-emotional responding.

The software engineering community recognized the importance of addressing security requirements with other functional requirements from the beginning of the software development life cycle. Therefore, there are some techniques that have been developed to achieve this goal. Thus, we conducted a theoretical study that focuses on reviewing and evaluating some of the techniques that are used to model and analyze security requirements. Thus, the Abuse Cases, Misuse Cases, Data Sensitivity and Threat Analyses, Strategic Modeling, and Attack Trees techniques are investigated in detail to understand and highlight the similarities and differences between them. We found that using these techniques, in general, help requirements engineer to specify more detailed security requirements. Also, all of these techniques cover the concepts of security but in different levels. In addition, the existence of different techniques provides a variety of levels for modeling and analyzing security requirements. This helps requirements engineer to decide which technique to use in order to address security issues for the system under investigation. Finally, we found that using only one of these techniques will not be suitable enough to satisfy the security requirements of the system under investigation. Consequently, we consider that it would be beneficial to combine the Abuse Cases or Misuse Cases techniques with the Attack Trees technique or to combine the Strategic Modeling and Attack Trees techniques together in order to model and analyze security requirements of the system under investigation. The concentration on using the Attack Trees technique is due to the reusability of the produced attack trees, also this technique helps in covering a wide range of attacks, thus covering security concepts as well as security requirements in a proper way.

This is a thesis about anti-paternalism – the liberal doctrine that we may not interfere with a person’s liberty for her own good. Empirical circumstances and moral values may certainly give us reason to avoid benevolent interference. Anti-paternalism as a normative doctrine should, however, be rejected.

Essay I concerns the definitions of paternalism and anti-paternalism. It is argued that only a definition of paternalism in terms of compound reason-actions can accommodate its special moral properties. Definitions in terms of actions, common in the literature, cannot. It is argued, furthermore, that in specifying the reason-actions in further detail, the notion of what is self-regarding, as opposed to other-regarding, is irrelevant, contrary to received opinion.

Essay II starts out with the definition of paternalism defended in essay I and claims that however this very general definition is specified, anti-paternalism is unreasonable and should be rejected. Anti-paternalism is the position that certain reasons – referring one way or the other to the good of a person, give no valid normative support to certain actions – some kind of interferences with the same person. Since the reasons in question are normally quite legitimate and important reasons for action, a convincing argument for anti-paternalism must explain why they are invalid in cases of interference. A closer look at the reasons and actions in question provides no basis for such an explanation.

Essay III considers a concrete case of benevolent interference – the withholding of information concerning uncertain threats to public health in the public’s best interest. Such a policy has been suggested in relation to the European Commission’s proposed new system for the Registration, Evaluation, and Authorisation of Chemicals (REACH). Information about uncertain threats to health from chemicals would allegedly spread anxiety and depression and thus do more harm than good. The avoidance of negative health effects is accepted as a legitimate and good reason for withholding of information, thus respecting the conclusion of essay II, that anti-paternalism should be rejected. Other reasons, however, tip the balance in favour of making the information available. These reasons include the net effects on knowledge, psychological effects, effects on private decisions and effects on political decisions.

Model-based Fault Detection and Isolation (FDI) is a major theoretical topic that is becoming increasingly to one of the most significant key features to increase safety and reliability of complex automatic control systems. Basically, model-based FDI relies on the use of a mathematical model to describe the system behavior. However, uncertainty remains always present when modelling a system since its effect is non-negligible even if there are no process faults. One way to deal with uncertainty is to assume its unknown-but-bounded description. Generally speaking, the uncertainty in so-called \emph{set-based approaches} is represented by a set that is unknown-but-bounded at each time instant. Set-based approaches can be classified into three main paradigms: interval observer approach, set-membership approach and set-invariance approach. In this thesis, the influence of the uncertainty is addressed using the set-based approaches considering a zonotopic representation. Moreover, this thesis presents both analysis and comparison of the set-based approaches for the state estimation and FDI frameworks with the goal of establishing the advantages and disadvantages of each approach, and also, to find out their relationship in a formal mathematical framework. However, the mentioned set-based approaches implicitly assume time-varying uncertainty. In the set-based approach, the propagation of the state set is affected by several problems such as the wrapping effect, temporal variance on uncertain parameters (or uncertain parameter time dependency) and range evaluation of an interval function, especially in the case of using the interval hull of the set at each iteration. Therefore, conservative and unstable results may be obtained (for even a stable system) when using the set-based approach in the simulation of the system with parametric time-invariant uncertainties. On the other hand, the approximated state set can be computed based on a set of point-wise trajectories. This type of approach is called \emph{trajectory-based approach}. Therefore, the uncertain parameter time dependency is preserved if the set of point-wise trajectories is generated using the mentioned trajectory-based approach.
La detección y el aislamiento de fallos (DAF) basado en modelos es un problema teórico importante que se está convirtiendo cada vez m ás en una de las características clave para aumentar la seguridad y abilidad de los sistemas de control autom ático complejos. Básicamente, la DAF basada en modelos utiliza un modelo m atem ático para describir el comportamiento del sistem a. Sin embargo, la incertidumbre permanece siempre presente cuando se modela un sistema, ya que su efecto no es despreciable, incluso si no hay fallos que afecten al sistema. Una form a de tener en cuenta la incertidumbre es asumir una descripción desconocida pero acotada. En términos generales, la incertidumbre en los llamados enfoques basados en conjuntos se representa mediante un conjunto que es desconocido pero acotado en cada instante de tiempo. Los enfoques basados en conjuntos se pueden clasicar en tres paradigmas principales: enfoque basado en observadores intervalares, enfoque de pertenencia al conjunto y enfoque basados en conjuntos invariante. En esta tesis, la inuencia de la incertidumbre se aborda utilizando los enfoques basados en conjuntos y representaciones zonotópicas de los mismos. Adem ás, esta tesis presenta tanto el análisis como la comparación de los enfoques basados en conjuntos para la estimación de estado con el objetivo de establecer las ventajas y desventajas de cada enfoque, y también, para descubrir su relación en un m arco matemático formal. Sin embargo, los mencionados enfoques basados en conjuntos suponen implícitamente una incertidumbre variante en el tiempo. En el enfoque basado en pertenencia a conjuntos, la propagación del conjunto de estados se ve afectada por varios problemas, como el efecto de del aum ento de incertidumbre, la varianza temporal de los parámetros inciertos (o la dependencia temporal de los parámetros inciertos) y la evaluación de rango de una función de intervalo, especialm ente cundo se usa el "lnterval Hull" en cada iteración. Por lo tanto, se pueden obtener resultados conservadores (incluso para un sistema estable) en la simulación del sistema con incertidumbres param étricas invariantes en el tiempo con el uso del enfoque basado en pertenencia a conjuntos. Por otro lado, el conjunto de estados aproximados se puede calcular con base en un conjunto de trayectorias puntuales. Este tipo de enfoque se denomina enfoque basado en trayectorias. Por lo tanto, la dependencia temporal del parámetro incierto se conserva si el conjunto de trayectorias puntuales se genera utilizando el mencionado enfoque basado en trayectorias
La detecció i aïllament de fallades basada en models (DAF) és un problema teòric important que està esdevenint cada cop més una de les característiques clau per augmentar la seguretat i la fiabilitat dels sistemes de control automàtic complexos. Bàsicament, la DAF basada en models es basa en l’ús d'un model matemàtic per descriure el comportament del sistema. Tanmateix, la incertesa roman sempre present quan es modelitza un sistema ja que el seu efecte no és insignificant, fins i tot si no hi ha fallades en el procés. Una forma de fer front a la incertesa és assumir una descripció desconeguda però acotada. En termes generals, la incertesa en els anomenats enfocaments basats en conjunts està representada per un conjunt desconegut però acotat en cada instant. Els enfocaments basats en conjunts es poden classificar en tres paradigmes principals: l'enfocament d'observadors d'intervals, l'enfocament de pertinença a conjunts i l'enfocament d’invariància. En aquesta tesi, s'aborda la influència de la incertesa mitjançant els enfocaments basats en conjunts fent servir una representació zonotòpica. A més, aquesta tesi presenta tant l’anàlisi com la comparació dels enfocaments basats en conjunts per a l’estimació de l'estat i la seva aplicació a DAF amb l'objectiu d'establir els avantatges i desavantatges de cada enfocament i, a més, conèixer la seva relació en un marc matemàtic formal. Tanmateix, els esmentats enfocaments basats en conjunts assumeixen implícitament una incertesa variable en el temps. En l'enfocament basat en conjunts, la propagació del conjunt d'estats es veu afectada per diversos problemes com l'efecte d'embolcall, la variació temporal dels paràmetres incerts (o la dependència en el temps dels paràmetres incerts) i l’avaluació del rang d'una funció intervalar, especialment en el cas d'utilitzar el "Interval Hull" del conjunt a cada iteració. Per tant, es poden obtenir resultats conservadors i inestables (fins i tot per a un sistema estable) en la simulació del sistema amb incerteses temporals invariants paramètriques amb l’ús del mètode basat en conjunts. D'altra banda, el conjunt d'estats aproximat es pot calcular a partir d'un conjunt de trajectòries puntuals. Aquest tipus d'enfocament s'anomena enfocament basat en trajectòries. Per tant, la dependència en el temps del paràmetres es conserva si el conjunt de trajectòries puntuals es generen utilitzant l'enfocament basat en trajectòries esmentat. Aquesta tesi inclou sis parts. La primera part, presenta l'estat de la tècnica i fa una introducció de les eines de recerca. La segona part proposa la relació matemàtica entre l'observador intervalar i els enfocaments de pertinença. La tercera part se centra en la integració dels enfocaments basats en observadors i d’invariància de conjunts en la seva aplicació a DAF caracteritzant la mínima fallada detectable i aïllable. La quarta part presenta el disseny d'un observador intervalar que millora la sensibilitat a les fallades respecte les pertorbacions. La cinquena part proposa el disseny robust d'observadors d'intervals per a sistemes incerts, subjectes a incerteses tant temporals com variables es el temps. L'última part presenta algunes conclusions, resumeix la investigació realitzada i estableix les bases per al treball futur

Le processus d'évaluation des risques technologiques, notamment liés au Transport de Matières Dangereuses (TMD), consiste, quand un événement accidentel se produit, à évaluer le niveau de risque potentiel des zones impactées afin de pouvoir dimensionner et prendre rapidement des mesures de prévention et de protection (confinement, évacuation...) dans le but de réduire et maitriser les effets sur les personnes et l'environnement. La première problématique de ce travail consiste donc à évaluer le niveau de risque des zones soumises au transport des matières dangereuses. Pour ce faire, un certain nombre d'informations sont utilisées, comme la quantification de l'intensité des phénomènes qui se produisent à l'aide de modèles d'effets (analytique ou code informatique). Pour ce qui concerne le problème de dispersion de produits toxiques, ces modèles contiennent principalement des variables d'entrée liées à la base de données d'exposition, de données météorologiques,… La deuxième problématique réside dans les incertitudes affectant certaines entrées de ces modèles. Pour correctement réaliser une cartographie en déterminant la zone de de danger où le niveau de risque est jugé trop élevé, il est nécessaire d'identifier et de prendre en compte les incertitudes sur les entrées afin de les propager dans le modèle d'effets et ainsi d'avoir une évaluation fiable du niveau de risque. Une première phase de ce travail a consisté à évaluer et propager l'incertitude sur la concentration qui est induite par les grandeurs d'entrée incertaines lors de son évaluation par les modèles de dispersion. Deux approches sont utilisées pour modéliser et propager les incertitudes : l'approche ensembliste pour les modèles analytiques et l'approche probabiliste (Monte-Carlo) qui est plus classique et utilisable que le modèle de dispersion soit analytique ou défini par du code informatique. L'objectif consiste à comparer les deux approches pour connaitre leurs avantages et inconvénients en termes de précision et temps de calcul afin de résoudre le problème proposé. Pour réaliser les cartographies, deux modèles de dispersion (Gaussien et SLAB) sont utilisés pour évaluer l'intensité des risques dans la zone contaminée. La réalisation des cartographies a été abordée avec une méthode probabiliste (Monte Carlo) qui consiste à inverser le modèle d'effets et avec une méthode ensembliste générique qui consiste à formuler ce problème sous la forme d'un ensemble de contraintes à satisfaire (CSP) et le résoudre ensuite par inversion ensembliste. La deuxième phase a eu pour but d'établir une méthodologie générale pour réaliser les cartographies et améliorer les performances en termes de temps du calcul et de précision. Cette méthodologie s'appuie sur 3 étapes : l'analyse préalable des modèles d'effets utilisés, la proposition d'une nouvelle approche pour la propagation des incertitudes mixant les approches probabiliste et ensembliste en tirant notamment partie des avantages des deux approches précitées, et utilisable pour n'importe quel type de modèle d'effets spatialisé et statique, puis finalement la réalisation des cartographies en inversant les modèles d'effets. L'analyse de sensibilité présente dans la première étape s'adresse classiquement à des modèles probabilistes. Nous discutons de la validité d'utiliser des indices de type Sobol dans le cas de modèles intervalles et nous proposerons un nouvel indice de sensibilité purement intervalle cette fois-ci
When an accidental event is occurring, the process of technological risk assessment, in particular the one related to Dangerous Goods Transportation (DGT), allows assessing the level of potential risk of impacted areas in order to provide and quickly take prevention and protection actions (containment, evacuation ...). The objective is to reduce and control its effects on people and environment. The first issue of this work is to evaluate the risk level for areas subjected to dangerous goods transportation. The quantification of the intensity of the occurring events needed to do this evaluation is based on effect models (analytical or computer code). Regarding the problem of dispersion of toxic products, these models mainly contain inputs linked to different databases, like the exposure data and meteorological data. The second problematic is related to the uncertainties affecting some model inputs. To determine the geographical danger zone where the estimated risk level is not acceptable, it is necessary to identify and take in consideration the uncertainties on the inputs in aim to propagate them in the effect model and thus to have a reliable evaluation of the risk level. The first phase of this work is to evaluate and propagate the uncertainty on the gas concentration induced by uncertain model inputs during its evaluation by dispersion models. Two approaches are used to model and propagate the uncertainties. The first one is the set-membership approach based on interval calculus for analytical models. The second one is the probabilistic approach (Monte Carlo), which is more classical and used more frequently when the dispersion model is described by an analytic expression or is is defined by a computer code. The objective is to compare the two approaches to define their advantages and disadvantages in terms of precision and computation time to solve the proposed problem. To determine the danger zones, two dispersion models (Gaussian and SLAB) are used to evaluate the risk intensity in the contaminated area. The risk mapping is achieved by using two methods: a probabilistic method (Monte Carlo) which consists in solving an inverse problem on the effect model and a set-membership generic method that defines the problem as a constraint satisfaction problem (CSP) and to resolve it with an set-membership inversion method. The second phase consists in establishing a general methodology to realize the risk mapping and to improve performance in terms of computation time and precision. This methodology is based on three steps: - Firstly the analysis of the used effect model. - Secondly the proposal of a new method for the uncertainty propagationbased on a mix between the probabilistic and set-membership approaches that takes advantage of both approaches and that is suited to any type of spatial and static effect model. -Finally the realization of risk mapping by inversing the effect models. The sensitivity analysis present in the first step is typically addressed to probabilistic models. The validity of using Sobol indices for interval models is discussed and a new interval sensitivity indiceis proposed

This thesis examines how perturbing selected adversary capabilities in a design basis threat (DBT) may affect the assessment of a facility's security system performance. We found that using a strictly defined DBT to design and analytically test facility security systems can lead to invalid assessments that security measures are meeting standards. Design Basis Threats are intended to represent the most severe yet realistic attack a facility might face. However, the static nature of the standard DBT makes it unable to test the performance of a facility security system in the case where a specialized adversary may possess different capabilities than defined in the DBT. Our analysis of security system performance for various modeled facilities revealed significant vulnerabilities to certain perturbations of adversary capabilities. These vulnerabilities went undetected when the original strictly defined graded DBT was used in the assessment procedure. By maximizing one adversary capability at the expense of others, a specialized adversary force was able to efficiently defeat each facility. To address this problem, we proposed employing a so-called "point-based" DBT as an alternative to the existing strictly defined DBT. In a point-based DBT, multiple scenarios are assessed that test different sets of adversary capabilities to better uncover and understand any security system vulnerabilities that may exist. We believe the benefit of identifying these site-specific security vulnerabilities will outweigh the additional cost of generating a point-based DBT, especially if the vulnerabilities are identified during the initial design of the security system.

碩士
國立高雄應用科技大學
機械與精密工程研究所
99
In this thesis, a computational optimization approach which integrates robust stabilizability condition, orthogonal-function approach (OFA), Taguchi- sliding-based differential evolution algorithm (TSBDEA) or hybrid Taguchi-genetic algorithm (HTGA) is presented to design the robust-optimal fuzzy parallel-distributed -compensation (PDC) controller such that (i) the Takagi-Sugeno (TS) fuzzy model system with parametric uncertainties can be robustly stabilized , and (ii) a quadratic finite-horizon integral performance index including a quadratic trajectory sensitivity term for the nominal TS fuzzy model system can be directly minimized. In this thesis, the robust stabilizability condition is proposed in terms of linear matrix inequalities (LMIs). Base on the OFA, an algebraic algorithm only involving the algebraic computation for solving the nominal TS fuzzy feedback dynamic equations. By using the OFA and LMI-based robust stabilizaility condition, the robust-optimal fuzzy PDC control problem for the uncertain TS fuzzy dynamic systems are transformed into a static constrained-optimization problem represented by the algebraic equations with constraint of LMI-based robust stabilizaility condition; thus greatly simplifying the robust-optimal PDC control design problem. Then, for the static constrained -optimization problem, the TSBDEA or HTGA has been employed to find the robust-optimal PDC controllers with low trajectory sensitivity of the uncertain TS fuzzy model systems. Two design examples are given to demonstrate the applicability of the proposed new integrative approach.

碩士
國立高雄應用科技大學
機械工程系
105
In this paper, an integrative method, which combines the robust stabilizability condition, the orthogonal-functions approach (OFA), and the Taguchi-sliding-based differential evolution algorithm (TSBDEA), is presented to design the robust-stable and quadratic-finite-horizon-optimal static output feedback parallel-distributed- compensation (PDC) controller with low trajectory sensitivity such that (i) the Takagi-Sugeno (TS) fuzzy control system with elemental parametric uncertainties can be robustly stabilized, and (ii) a quadratic finite-time integral performance index including a quadratic sensitivity term for nominal TS fuzzy control system can be minimized. The robust stabilizability condition is proposed in terms of linear matrix inequalities (LMIs). By using the OFA and the robust stabilizability condition, the robust-stable and quadratic-finite-horizon-optimal static output feedback PDC control problem for the TS fuzzy dynamic systems is transformed into a static constrained-optimization problem represented by the algebraic equations with constraint of LMI-based robust stabilizability condition; thus greatly simplifying the optimal static output feedback PDC controller design problem. Then, for the static constrained-optimization problem, the TSBDEA is applied to find the robust-stable and quadratic-finite-horizon-optimal static output feedback PDC controllers with low trajectory sensitivity of the TS fuzzy control systems with elemental parametric uncertainties. A design example of robust-stable and quadratic-finite-horizon-optimal static output feedback PDC controllers with low trajectory sensitivity for uncertain nonlinear Chua circuit is given to demonstrate the applicability of the proposed integrative approach.

The utilization of in vitro tests with a tiered testing strategy for detection of mild ocular irritants can reduce the use of animals for testing, provide mechanistic data on toxic effects, and reduce the uncertainty associated with dose selection for clinical trials. The first section of this thesis describes how in vitro methods can be used to improve the prediction of the toxicity of chemicals and ophthalmic products. The proper utilization of in vitro methods can accurately predict toxic threshold levels and reduce animal use in product development. Sections two, three and four describe the development of new sensitive in vitro methods for predicting ocular toxicity. Maintaining the barrier function of the cornea is critical for the prevention of the penetration of infections microorganisms and irritating chemicals into the eye. Chapter 2 describes the development of a method for assessing the effects of chemicals on tight junctions using a human corneal epithelial and canine kidney epithelial cell line. In Chapter 3 a method that uses a primary organ culture for assessing single instillation and multiple instillation toxic effects is described. The ScanTox system was shown to be an ideal system to monitor the toxic effects over time as multiple readings can be taken of treated bovine lenses using the nondestructive method of assessing for the lens optical quality. Confirmations of toxic effects were made with the utilization of the viability dye alamarBlue. Chapter 4 describes the development of sensitive in vitro assays for detecting ocular toxicity by measuring the effects of chemicals on the mitochondrial integrity of bovine cornea, bovine lens epithelium and corneal epithelial cells, using fluorescent dyes. The goal of this research was to develop an in vitro test battery that can be used to accurately predict the ocular toxicity of new chemicals and ophthalmic formulations. By comparing the toxicity seen in vivo animals and humans with the toxicity response in these new in vitro methods, it was demonstrated that these in vitro methods can be utilized in a tiered testing strategy in the development of new chemicals and ophthalmic formulations.