Optimal fuzzy PID control tuned with genetic algorithms

Fuzzy logic controllers (FLC) are intelligent systems, based on heuristic knowledge, that have been largely applied in numerous areas of everyday life. They can be used to describe a linear or nonlinear system and are suitable when a real system is not known or too difficult to find their model. FLC provide a formal methodology for representing, manipulating and implementing a human heuristic knowledge on how to control a system. These controllers can be seen as artificial decision makers that operate in a closed-loop system, in real time. The main aim of this work was to develop a single optimal fuzzy controller, easily adaptable to a wide range of systems – simple to complex, linear to nonlinear – and able to control all these systems. Due to their efficiency in searching and finding optimal solution for high complexity problems, GAs were used to perform the FLC tuning by finding the best parameters to obtain the best responses. The work was performed using the MATLAB/SIMULINK software. This is a very useful tool that provides an easy way to test and analyse the FLC, the PID and the GAs in the same environment. Therefore, it was proposed a Fuzzy PID controller (FL-PID) type namely, the Fuzzy PD+I. For that, the controller was compared with the classical PID controller tuned with, the heuristic Ziegler-Nichols tuning method, the optimal Zhuang-Atherton tuning method and the GA method itself. The IAE, ISE, ITAE and ITSE criteria, used as the GA fitness functions, were applied to compare the controllers performance used in this work. Overall, and for most systems, the FL-PID results tuned with GAs were very satisfactory. Moreover, in some cases the results were substantially better than for the other PID controllers. The best system responses were obtained with the IAE and ITAE criteria used to tune the FL-PID and PID controllers.

Voltage Analysis and Load Curtailment Minimization in Sub-transmission Networks with Distributed Generation

Most of distributed generation and smart grid research works are dedicated to network operation parameters studies, reliability, etc. However, many of these works normally uses traditional test systems, for instance, IEEE test systems. This paper proposes voltage magnitude and reliability studies in presence of fault conditions, considering realistic conditions found in countries like Brazil. The methodology considers a hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models and a remedial action algorithm which is based on optimal power flow. To illustrate the application of the proposed method, the paper includes a case study that considers a real 12-bus sub-transmission network.

An efficient numerical scheme for solving multi-dimensional fractional optimal control problems with a quadratic performance index

The shifted Legendre orthogonal polynomials are used for the numerical solution of a new formulation for the multi-dimensional fractional optimal control problem (M-DFOCP) with a quadratic performance index. The fractional derivatives are described in the Caputo sense. The Lagrange multiplier method for the constrained extremum and the operational matrix of fractional integrals are used together with the help of the properties of the shifted Legendre orthonormal polynomials. The method reduces the M-DFOCP to a simpler problem that consists of solving a system of algebraic equations. For confirming the efficiency and accuracy of the proposed scheme, some test problems are implemented with their approximate solutions.

TEC4SEA - A Modular Platform for Research, Test and Validation of Technologies Supporting a Sustainable Blue Economy

This paper presents the TEC4SEA research infrastructure created in Portugal to support research, development, and validation of marine technologies. It is a multidisciplinary open platform, capable of supporting research, development, and test of marine robotics, telecommunications, and sensing technologies for monitoring and operating in the ocean environment. Due to the installed research facilities and its privileged geographic location, it allows fast access to deep sea, and can support multidisciplinary research, enabling full validation and evaluation of technological solutions designed for the ocean environment. It is a vertically integrated infrastructure, in the sense that it possesses a set of skills and resources which range from pure conceptual research to field deployment missions, with strong industrial and logistic capacities in the middle tier of prototype production. TEC4SEA is open to the entire scientific and enterprise community, with a free access policy for researchers affiliated with the research units that ensure its maintenance and sustainability. The paper describes the infrastructure in detail, and discusses associated research programs, providing a strategic vision for deep sea research initiatives, within the context of both the Portuguese National Ocean Strategy and European Strategy frameworks.

An Exact Schedulability Test for Global FP Using State Space Pruning

Presented at 23rd International Conference on Real-Time Networks and Systems (RTNS 2015). 4 to 6, Nov, 2015, Main Track. Lille, France.

Optimal slopes and speeds in uphill ski mountaineering: a laboratory study.

The purpose of this study was to estimate the energy cost of linear (EC) and vertical displacement (ECvert), mechanical efficiency and main stride parameters during simulated ski mountaineering at different speeds and gradients, to identify an optimal speed and gradient that maximizes performance. 12 subjects roller skied on a treadmill at three different inclines (10, 17 and 24 %) at three different speeds (approximately 70, 80 and 85 % of estimated peak heart rate). Energy expenditure was calculated by indirect calorimetry, while biomechanical parameters were measured with an inertial sensor-based system. At 10 % there was no significant change with speed in EC, ECvert and mechanical efficiency. At 17 and 24 % the fastest speed was significantly more economical. There was a significant effect of gradient on EC, ECvert and mechanical efficiency. The most economical gradient was the steepest one. There was a significant increase of stride frequency with speed. At steep gradients only, relative thrust phase duration decreased significantly, while stride length increased significantly with speed. There was a significant effect of gradient on stride length (decrease with steepness) and relative thrust phase duration (increase with steepness). A combination of a decreased relative thrust phase duration with increased stride length and frequency decreases ECvert. To minimize the energy expenditure to reach the top of a mountain and to optimize performance, ski-mountaineers should choose a steep gradient (~24 %) and, provided they possess sufficient metabolic scope, combine it with a fast speed (~6 km h(-1)).

Implementing the OPTIMAL model : the impact on students' motivation in an elementary school games environment

Optimal challenge occurs when an individual perceives the challenge of the task to be equaled or matched by his or her own skill level (Csikszentmihalyi, 1990). The purpose of this study was to test the impact of the OPTIMAL model on physical education students' motivation and perceptions of optimal challenge across four games categories (i. e. target, batting/fielding, net/wall, invasion). Enjoyment, competence, student goal orientation and activity level were examined in relation to the OPTIMAL model. A total of 22 (17 M; 5 F) students and their parents provided informed consent to take part in the study and were taught four OPTIMAL lessons and four non-OPTIMAL lessons ranging across the four different games categories by their own teacher. All students completed the Task and Ego in Sport Questionnaire (TEOSQ; Duda & Whitehead, 1998), the Intrinsic Motivation Inventory (IMI; McAuley, Duncan, & Tanmien, 1987) and the Children's Perception of Optimal Challenge Instrument (CPOCI; Mandigo, 2001). Sixteen students (two each lesson) were observed by using the System for Observing Fitness Instruction Time tool (SOFTT; McKenzie, 2002). As well, they participated in a structured interview which took place after each lesson was completed. Quantitative results concluded that no overall significant difference was found in motivational outcomes when comparing OPTIMAL and non-OPTIMAL lessons. However, when the lessons were broken down into games categories, significant differences emerged. Levels of perceived competence were found to be higher in non-OPTIMAL batting/fielding lessons compared to OPTIMAL lessons, whereas levels of enjoyment and perceived competence were found to be higher in OPTIMAL invasion lessons in comparison to non-OPTIMAL invasion lessons. Qualitative results revealed significance in feehngs of skill/challenge balance, enjoyment and competence in the OPTIMAL lessons. Moreover, a significance of practically twice the active movement time percentage was found in OPTIMAL lessons in comparison to non-OPTIMAL lessons.

Set-up and evaluation of a mid-infrared reflectometer and investigation of the optical properties of doped tin telluride

A system comprised of a Bomem interferometer and a LT3-110 Heli-Tran cryostat was set up to measure the reflectance of materials in the mid-infrared spectral region. Several tests were conducted to ensure the consistency and reliability of the system. Silicon and Chromium, two materials with well known optical properties were measured to test the accuracy of the system, and the results were found to be in good agreement with the literature. Reflectance measurements on pure SnTe and several Pb and Mn-doped alloys were carried out. These materials were chosen because they exhibit a strong plasma edge in the mid infrared region. The optical conductivity and several related optical parameters were calculated from the measured reflectance. Very low temperature measurements were carried out in the far-infrared on Sn9SMn2Te, and the results are indicative of a spin glass phase at 0.8 K. Resistivity measurements were made at room temperature. The resistivity values were found, as expected, to decrease with increasing carrier concentration and to increase with increasing manganese concentration.

Optimal and Robust Designs of Step-stress Accelerated Life Testing Experiments for Proportional Hazards Models

Accelerated life testing (ALT) is widely used to obtain reliability information about a product within a limited time frame. The Cox s proportional hazards (PH) model is often utilized for reliability prediction. My master thesis research focuses on designing accelerated life testing experiments for reliability estimation. We consider multiple step-stress ALT plans with censoring. The optimal stress levels and times of changing the stress levels are investigated. We discuss the optimal designs under three optimality criteria. They are D-, A- and Q-optimal designs. We note that the classical designs are optimal only if the model assumed is correct. Due to the nature of prediction made from ALT experimental data, attained under the stress levels higher than the normal condition, extrapolation is encountered. In such case, the assumed model cannot be tested. Therefore, for possible imprecision in the assumed PH model, the method of construction for robust designs is also explored.

GA approach for finding Rough Set decision rules based on bireducts

Feature selection plays an important role in knowledge discovery and data mining nowadays. In traditional rough set theory, feature selection using reduct - the minimal discerning set of attributes - is an important area. Nevertheless, the original definition of a reduct is restrictive, so in one of the previous research it was proposed to take into account not only the horizontal reduction of information by feature selection, but also a vertical reduction considering suitable subsets of the original set of objects. Following the work mentioned above, a new approach to generate bireducts using a multi--objective genetic algorithm was proposed. Although the genetic algorithms were used to calculate reduct in some previous works, we did not find any work where genetic algorithms were adopted to calculate bireducts. Compared to the works done before in this area, the proposed method has less randomness in generating bireducts. The genetic algorithm system estimated a quality of each bireduct by values of two objective functions as evolution progresses, so consequently a set of bireducts with optimized values of these objectives was obtained. Different fitness evaluation methods and genetic operators, such as crossover and mutation, were applied and the prediction accuracies were compared. Five datasets were used to test the proposed method and two datasets were used to perform a comparison study. Statistical analysis using the one-way ANOVA test was performed to determine the significant difference between the results. The experiment showed that the proposed method was able to reduce the number of bireducts necessary in order to receive a good prediction accuracy. Also, the influence of different genetic operators and fitness evaluation strategies on the prediction accuracy was analyzed. It was shown that the prediction accuracies of the proposed method are comparable with the best results in machine learning literature, and some of them outperformed it.

Validation et conditionnement d'un test PAMPA amélioré pour l'évaluation de la perméabilité membranaire de médicaments.

Les tests PAMPA et les tests Caco-2 sont des essais in vitro de l’évaluation de la perméabilité intestinale des médicaments. Ils sont réalisés lors de la phase de découverte du médicament. Les tests PAMPA ne sont pas biologiquement représentatifs de la paroi intestinale, mais ils sont rapides et peu coûteux. Les tests Caco-2 nécessitent plus de 21 jours pour la culture cellulaire et des installations spécifiques sont requises. Ils sont constitués d’une monocouche d’entérocytes à confluence et donc plus biologiquement représentatifs. Il y a un besoin pour le développement d’un essai qui est biologiquement représentatif de la membrane intestinale humaine, rapide et peu coûteux. Le premier but de ce projet était de développer une méthode analytique qui permettrait l’évaluation simultanée de huit médicaments témoins utilisés pour la validation de l’essai de perméabilité. Le deuxième but de ce projet était donc d’améliorer la membrane des tests PAMPA pour proposer un nouveau test : le néoPAMPA. Contrairement au test PAMPA traditionnel, cette membrane est constituée de trois composantes : (1) un filtre poreux qui agit à titre de support, (2) un coussin polydopamine chargé négativement qui sert d’ancrage et qui assure la fluidité de la bicouche et (3) une bicouche lipidique formée par fusion de vésicules. Une méthode analytique HPLC-MS/MS a été validée selon les spécifications de la FDA et de la EMA. Cette méthode a permis de quantifier simultanément les huit médicaments standards utilisés pour le test néoPAMPA. Le test PAMPA traditionnel a été mis en place à titre d’essai control. Les coefficients de perméabilité mesurés pour les huit médicaments au travers de la membrane PAMPA comparaient favorablement aux résultats de la littérature. Les composantes de la membrane néoPAMPA ont été optimisées. Les conditions optimales retenues étaient les filtres de polycarbonate hydrophile ayant des pores de 15 nm, les plaques Costar 12 puits comme dispositif des tests de perméabilité, une bicouche lipidique composée de 70 % DOPC et de 30 % cholestérol cationique ainsi qu’une déposition des liposomes en présence de 150 mM NaCl suivi d’un équilibre d’1 h en présence d’une solution saturée en DOPC. Les stabilités de la cassette de médicaments et des liposomes sont insuffisantes pour le conditionnement commercial des membranes néoPAMPA. Les différentes optimisations réalisées ont permis d’améliorer la membrane néoPAMPA sans toutefois la rendre fonctionnelle. La membrane néoPAMPA n’est toujours pas en mesure de discriminer des molécules en fonction de leur perméabilité attendue.

Changes in cortical and sub-cortical patterns of activity associated with aging during the performance of a lexical set-shifting task

Bien que le passage du temps altère le cerveau, la cognition ne suit pas nécessairement le même destin. En effet, il existe des mécanismes compensatoires qui permettent de préserver la cognition (réserve cognitive) malgré le vieillissement. Les personnes âgées peuvent utiliser de nouveaux circuits neuronaux (compensation neuronale) ou des circuits existants moins susceptibles aux effets du vieillissement (réserve neuronale) pour maintenir un haut niveau de performance cognitive. Toutefois, la façon dont ces mécanismes affectent l’activité corticale et striatale lors de tâches impliquant des changements de règles (set-shifting) et durant le traitement sémantique et phonologique n’a pas été extensivement explorée. Le but de cette thèse est d’explorer comment le vieillissement affecte les patrons d’activité cérébrale dans les processus exécutifs d’une part et dans l’utilisation de règles lexicales d’autre part. Pour cela nous avons utilisé l’imagerie par résonance magnétique fonctionnelle (IRMf) lors de la performance d’une tâche lexicale analogue à celle du Wisconsin. Cette tâche a été fortement liée à de l’activité fronto-stritale lors des changements de règles, ainsi qu’à la mobilisation de régions associées au traitement sémantique et phonologique lors de décisions sémantiques et phonologiques, respectivement. Par conséquent, nous avons comparé l’activité cérébrale de jeunes individus (18 à 35 ans) à celle d’individus âgés (55 à 75 ans) lors de l’exécution de cette tâche. Les deux groupes ont montré l’implication de boucles fronto-striatales associées à la planification et à l’exécution de changements de règle. Toutefois, alors que les jeunes semblaient activer une « boucle cognitive » (cortex préfrontal ventrolatéral, noyau caudé et thalamus) lorsqu’ils se voyaient indiquer qu’un changement de règle était requis, et une « boucle motrice » (cortex postérieur préfrontal et putamen) lorsqu’ils devaient effectuer le changement, les participants âgés montraient une activation des deux boucles lors de l’exécution des changements de règle seulement. Les jeunes adultes tendaient à présenter une augmentation de l’activité du cortex préfrontal ventrolatéral, du gyrus fusiforme, du lobe ventral temporale et du noyau caudé lors des décisions sémantiques, ainsi que de l’activité au niveau de l’aire de Broca postérieur, de la junction temporopariétale et du cortex moteur lors de décisions phonologiques. Les participants âgés ont montré de l’activité au niveau du cortex préfrontal latéral et moteur durant les deux types de décisions lexicales. De plus, lorsque les décisions sémantiques et phonologiques ont été comparées entre elles, les jeunes ont montré des différences significatives au niveau de plusieurs régions cérébrales, mais pas les âgés. En conclusion, notre première étude a montré, lors du set-shifting, un délai de l’activité cérébrale chez les personnes âgées. Cela nous a permis de conceptualiser l’Hypothèse Temporelle de Compensation (troisième manuscrit) qui consiste en l’existence d’un mécanisme compensatoire caractérisé par un délai d’activité cérébrale lié au vieillissement permettant de préserver la cognition au détriment de la vitesse d’exécution. En ce qui concerne les processus langagiers (deuxième étude), les circuits sémantiques et phonologiques semblent se fusionner dans un seul circuit chez les individus âgés, cela représente vraisemblablement des mécanismes de réserve et de compensation neuronales qui permettent de préserver les habilités langagières.

Multi-objective assembly job shop scheduling using genetic algorithm and tabu search

Assembly job shop scheduling problem (AJSP) is one of the most complicated combinatorial optimization problem that involves simultaneously scheduling the processing and assembly operations of complex structured products. The problem becomes even more complicated if a combination of two or more optimization criteria is considered. This thesis addresses an assembly job shop scheduling problem with multiple objectives. The objectives considered are to simultaneously minimizing makespan and total tardiness. In this thesis, two approaches viz., weighted approach and Pareto approach are used for solving the problem. However, it is quite difficult to achieve an optimal solution to this problem with traditional optimization approaches owing to the high computational complexity. Two metaheuristic techniques namely, genetic algorithm and tabu search are investigated in this thesis for solving the multiobjective assembly job shop scheduling problems. Three algorithms based on the two metaheuristic techniques for weighted approach and Pareto approach are proposed for the multi-objective assembly job shop scheduling problem (MOAJSP). A new pairing mechanism is developed for crossover operation in genetic algorithm which leads to improved solutions and faster convergence. The performances of the proposed algorithms are evaluated through a set of test problems and the results are reported. The results reveal that the proposed algorithms based on weighted approach are feasible and effective for solving MOAJSP instances according to the weight assigned to each objective criterion and the proposed algorithms based on Pareto approach are capable of producing a number of good Pareto optimal scheduling plans for MOAJSP instances.

Design, implementation and application of a generic framework for integrated regional land-use modeling

Land use is a crucial link between human activities and the natural environment and one of the main driving forces of global environmental change. Large parts of the terrestrial land surface are used for agriculture, forestry, settlements and infrastructure. Given the importance of land use, it is essential to understand the multitude of influential factors and resulting land use patterns. An essential methodology to study and quantify such interactions is provided by the adoption of land-use models. By the application of land-use models, it is possible to analyze the complex structure of linkages and feedbacks and to also determine the relevance of driving forces. Modeling land use and land use changes has a long-term tradition. In particular on the regional scale, a variety of models for different regions and research questions has been created. Modeling capabilities grow with steady advances in computer technology, which on the one hand are driven by increasing computing power on the other hand by new methods in software development, e.g. object- and component-oriented architectures. In this thesis, SITE (Simulation of Terrestrial Environments), a novel framework for integrated regional sland-use modeling, will be introduced and discussed. Particular features of SITE are the notably extended capability to integrate models and the strict separation of application and implementation. These features enable efficient development, test and usage of integrated land-use models. On its system side, SITE provides generic data structures (grid, grid cells, attributes etc.) and takes over the responsibility for their administration. By means of a scripting language (Python) that has been extended by language features specific for land-use modeling, these data structures can be utilized and manipulated by modeling applications. The scripting language interpreter is embedded in SITE. The integration of sub models can be achieved via the scripting language or by usage of a generic interface provided by SITE. Furthermore, functionalities important for land-use modeling like model calibration, model tests and analysis support of simulation results have been integrated into the generic framework. During the implementation of SITE, specific emphasis was laid on expandability, maintainability and usability. Along with the modeling framework a land use model for the analysis of the stability of tropical rainforest margins was developed in the context of the collaborative research project STORMA (SFB 552). In a research area in Central Sulawesi, Indonesia, socio-environmental impacts of land-use changes were examined. SITE was used to simulate land-use dynamics in the historical period of 1981 to 2002. Analogous to that, a scenario that did not consider migration in the population dynamics, was analyzed. For the calculation of crop yields and trace gas emissions, the DAYCENT agro-ecosystem model was integrated. In this case study, it could be shown that land-use changes in the Indonesian research area could mainly be characterized by the expansion of agricultural areas at the expense of natural forest. For this reason, the situation had to be interpreted as unsustainable even though increased agricultural use implied economic improvements and higher farmers' incomes. Due to the importance of model calibration, it was explicitly addressed in the SITE architecture through the introduction of a specific component. The calibration functionality can be used by all SITE applications and enables largely automated model calibration. Calibration in SITE is understood as a process that finds an optimal or at least adequate solution for a set of arbitrarily selectable model parameters with respect to an objective function. In SITE, an objective function typically is a map comparison algorithm capable of comparing a simulation result to a reference map. Several map optimization and map comparison methodologies are available and can be combined. The STORMA land-use model was calibrated using a genetic algorithm for optimization and the figure of merit map comparison measure as objective function. The time period for the calibration ranged from 1981 to 2002. For this period, respective reference land-use maps were compiled. It could be shown, that an efficient automated model calibration with SITE is possible. Nevertheless, the selection of the calibration parameters required detailed knowledge about the underlying land-use model and cannot be automated. In another case study decreases in crop yields and resulting losses in income from coffee cultivation were analyzed and quantified under the assumption of four different deforestation scenarios. For this task, an empirical model, describing the dependence of bee pollination and resulting coffee fruit set from the distance to the closest natural forest, was integrated. Land-use simulations showed, that depending on the magnitude and location of ongoing forest conversion, pollination services are expected to decline continuously. This results in a reduction of coffee yields of up to 18% and a loss of net revenues per hectare of up to 14%. However, the study also showed that ecological and economic values can be preserved if patches of natural vegetation are conservated in the agricultural landscape. -----------------------------------------------------------------------

Evolving Distributed Algorithms with Genetic Programming

Distributed systems are one of the most vital components of the economy. The most prominent example is probably the internet, a constituent element of our knowledge society. During the recent years, the number of novel network types has steadily increased. Amongst others, sensor networks, distributed systems composed of tiny computational devices with scarce resources, have emerged. The further development and heterogeneous connection of such systems imposes new requirements on the software development process. Mobile and wireless networks, for instance, have to organize themselves autonomously and must be able to react to changes in the environment and to failing nodes alike. Researching new approaches for the design of distributed algorithms may lead to methods with which these requirements can be met efficiently. In this thesis, one such method is developed, tested, and discussed in respect of its practical utility. Our new design approach for distributed algorithms is based on Genetic Programming, a member of the family of evolutionary algorithms. Evolutionary algorithms are metaheuristic optimization methods which copy principles from natural evolution. They use a population of solution candidates which they try to refine step by step in order to attain optimal values for predefined objective functions. The synthesis of an algorithm with our approach starts with an analysis step in which the wanted global behavior of the distributed system is specified. From this specification, objective functions are derived which steer a Genetic Programming process where the solution candidates are distributed programs. The objective functions rate how close these programs approximate the goal behavior in multiple randomized network simulations. The evolutionary process step by step selects the most promising solution candidates and modifies and combines them with mutation and crossover operators. This way, a description of the global behavior of a distributed system is translated automatically to programs which, if executed locally on the nodes of the system, exhibit this behavior. In our work, we test six different ways for representing distributed programs, comprising adaptations and extensions of well-known Genetic Programming methods (SGP, eSGP, and LGP), one bio-inspired approach (Fraglets), and two new program representations called Rule-based Genetic Programming (RBGP, eRBGP) designed by us. We breed programs in these representations for three well-known example problems in distributed systems: election algorithms, the distributed mutual exclusion at a critical section, and the distributed computation of the greatest common divisor of a set of numbers. Synthesizing distributed programs the evolutionary way does not necessarily lead to the envisaged results. In a detailed analysis, we discuss the problematic features which make this form of Genetic Programming particularly hard. The two Rule-based Genetic Programming approaches have been developed especially in order to mitigate these difficulties. In our experiments, at least one of them (eRBGP) turned out to be a very efficient approach and in most cases, was superior to the other representations.