DESIGN OPTIMIZATION FOR A SUPPORT FOR THE STORAGE RING QUADRUPOLE MAGNET IN A SYNCHROTRON RADIATION FACILITY

High brilliance photon beam production requires high gradient magnets. High gradient magnets initiate large magnetic forces to be borne by supports to keep them in position. The objective of this study was to design a support for the CLS 2.0 quadrupole magnet that suppresses vibrations with the goals of the minimal amount of materials and low cost as compared to the existing system. The motivation of this study was associated with upgrading the CLS 2.0’s electron beam, specifically the beam size which will be more than a hundred times smaller than that of the current CLS. The optimization goals of the support design were : (1) Maximizing the natural frequency of the whole magnet system (magnet + supports) and (2) Minimizing the weight of the frame, while meeting the constraints: (1) Static deflection less than 10 microns. (2) Stress developed should be less than the yield stress of the frame material (3) Natural frequency of the system should be more than 50Hz. Such a problem, when translated to the optimization problem, is a large problem as too many design parameters are involved, which makes the “All-In-One (AIO)” strategy of optimization infeasible. This study adopted a divide-and-conquer strategy, i.e., to properly decompose the whole problem into a set of small problems and then optimize them separately. By applying this novel design process, the frame was successfully designed, and the verification showed satisfactory results. The contribution of this work lies in the field of computational design, and specifically, it provides a case demonstration of the divide-and-concur strategy usefulness while optimizing the design for large problems

Power Flow Modelling of Dynamic Systems - Introduction to Modern Teaching Tools

As tools for dynamic system modelling both conventional methods such as transfer function or state space representation and modern power flow based methods are available. The latter methods do not depend on energy domain, are able to preserve physical system structures, visualize power conversion or coupling or split, identify power losses or storage, run on conventional software and emphasize the relevance of energy as basic principle of known physical domains. Nevertheless common control structures as well as analysis and design tools may still be applied. Furthermore the generalization of power flow methods as pseudo-power flow provides with a universal tool for any dynamic modelling. The phenomenon of power flow constitutes an up to date education methodology. Thus the paper summarizes fundamentals of selected power flow oriented modelling methods, presents a Bond Graph block library for teaching power oriented modelling as compact menu-driven freeware, introduces selected examples and discusses special features.Comment: 12 pages, 9 figures, 4 table

A Proposed Approach to Mechatronics Design and Implementation Education-Oriented Methodology

Mechatronics engineer is expected to design engineering systems with synergy and integration toward constrains like higher performance, speed, precision, efficiency, lower costs and functionality. The key element in success of a mechatronics engineering education-program, and correspondingly, Mechatronics engineering graduates, is directly related to a well-structured mechatronic system design course and the applied structural design methodology. Guidelines for structural design methodology and tools for the development process of mechatronic products, that can be applied in educational process is highly required. This paper proposes mechatronics systems design education-oriented methodology, which aims to integrate multidisciplinary knowledge, in various stages through the design process and development of mechatronics product. The proposed mechatronics design methodology is described, discussed and applied with the help of example student final year graduation project; design and implementation of mechatronics mobile robotic guidance system in the from of smart wheelchair- Mechatronics Motawif, to help and support people with disabilities and special needs to perform specific predetermined tasks, particularly, performing Al Omrah and motion around holy Kaba, Makka. Keywords: Mechatronics, Design methodology, Parallel design, Synergistic integration, Modeling/ Simulation, Prototyping, Mobile robot, Motawif

Improvements on the bees algorithm for continuous optimisation problems

This work focuses on the improvements of the Bees Algorithm in order to enhance the algorithm’s performance especially in terms of convergence rate. For the first enhancement, a pseudo-gradient Bees Algorithm (PG-BA) compares the fitness as well as the position of previous and current bees so that the best bees in each patch are appropriately guided towards a better search direction after each consecutive cycle. This method eliminates the need to differentiate the objective function which is unlike the typical gradient search method. The improved algorithm is subjected to several numerical benchmark test functions as well as the training of neural network. The results from the experiments are then compared to the standard variant of the Bees Algorithm and other swarm intelligence procedures. The data analysis generally confirmed that the PG-BA is effective at speeding up the convergence time to optimum. Next, an approach to avoid the formation of overlapping patches is proposed. The Patch Overlap Avoidance Bees Algorithm (POA-BA) is designed to avoid redundancy in search area especially if the site is deemed unprofitable. This method is quite similar to Tabu Search (TS) with the POA-BA forbids the exact exploitation of previously visited solutions along with their corresponding neighbourhood. Patches are not allowed to intersect not just in the next generation but also in the current cycle. This reduces the number of patches materialise in the same peak (maximisation) or valley (minimisation) which ensures a thorough search of the problem landscape as bees are distributed around the scaled down area. The same benchmark problems as PG-BA were applied against this modified strategy to a reasonable success. Finally, the Bees Algorithm is revised to have the capability of locating all of the global optimum as well as the substantial local peaks in a single run. These multi-solutions of comparable fitness offers some alternatives for the decision makers to choose from. The patches are formed only if the bees are the fittest from different peaks by using a hill-valley mechanism in this so called Extended Bees Algorithm (EBA). This permits the maintenance of diversified solutions throughout the search process in addition to minimising the chances of getting trap. This version is proven beneficial when tested with numerous multimodal optimisation problems

Concurrent, Integrated and Multicriteria Design Support for Mechatronic Systems

RÉSUMÉ Les systèmes mécatroniques sont une combinaison coopérative de composantes mécaniques, électroniques, de contrôle et logiciels. Dans les dernières décennies, Ils ont trouvé diverses applications dans l'industrie et la vie quotidienne. En raison de leur aspect multi-physique, du nombre élevé de leurs composantes et des interconnexions dynamiques entre les différents domaines impliqués dans leur fonctionnement, les dispositifs mécatroniques sont souvent considérés comme hautement complexes ce qui rend la tâche de les concevoir très difficile pour les ingénieurs. Cette complexité inhérente a attiré l’attention de la communauté de recherche en conception, en particulier dans le but d’atteindre une conception optimale des systèmes multi-domaines. Ainsi, cette thèse, représente une recherche originale sur le développement d'un paradigme de conception systématique, intégrée et multi-objectifs pour remplacer l'approche de conception séquentielle traditionnelle qui tend à traiter les différents domaines de la mécatronique séparément. Dans le but d'augmenter l'efficacité, la fiabilité, la facilité de contrôle et sa flexibilité, tout en réduisant la complexité et le coût effectif, ainsi que l'intégration systèmes, cette thèse présente de nouvelles approches pour la conception concurrente et optimale des systèmes mécatroniques aux stades de design conceptuel et détaillé. Les modèles mathématiques et les fondements qui soutiennent cette pensée sont présentés dans cette thèse. Les contributions des travaux de recherche de ce doctorat ont commencé par l'introduction d'un vecteur d'indices appelé le profile mécatronique multicritère (PMM) utilisé pour l'évaluation des concepts lors de la conception des systèmes mécatroniques. Les intégrales floues non linéaires de la théorie de décisions multicritères sont utilisées pour agréger les critères de conception et pour gérer les interactions possibles entre elles. Ensuite, une méthodologie de conception conceptuelle systématique est proposée et formulée. Le soutien à l'intégration d'outils d’aide à la décision multicritère dans le processus de conception est un autre objectif de cette thèse où un certain nombre de cadres de travail sont proposés pour aider les ingénieurs concepteurs à évaluer l’importance de certains critères et des paramètres d'interaction. Ces cadres de travail ne s'appliquent pas uniquement l'évaluation de la conception et de la conception optimales, mais aussi à la détermination des possibles façons d'améliorer les concepts développés. Des méthodes basées sur l’exploitation de données ainsi que des algorithmes d'optimisation sémantique sont utilisées pour identifier les paramètres flous avec le peu d’information disponibles sur les différents choix de concepts et les préférences des concepteurs.----------ABSTRACT Mechatronic systems are a combination of cooperative mechanical, electronics, control and software components. They have found vast applications in industry and everyday life during past decades. Due to their multi-physical aspect, the high number of their components, and the dynamic inter-connections between the different domains involved, mechatronic devices are often considered to be highly complex which makes the design task very tedious and non-trivial. This inherent complexity, has attracted a great deal of attention in the research community, particularly in the context of optimal design of multi-domain systems. To this end, the present thesis represents an original investigation into the development of a systematic, integrated and multi-objective design paradigm to replace the traditional sequential design approach that tends to deal with the different domains separately. With the aim of increasing efficiency, reliability, controllability and flexibility, while reducing complexity and effective cost, and finally facilitating system integration, this thesis presents new approaches towards concurrent and optimal design of mechatronic systems in conceptual and detailed design stages. The mathematical models and foundations which support this thinking are presented in the thesis. The contributions of our research work start with introducing an index vector called Mechatronic Multi-criteria Profile (MMP) used for concept evaluation in design of mechatronic systems. Nonlinear fuzzy integrals from multicriteria decision theory are utilized to aggregate design criteria and for handling possible interactions among them. Then, a systematic conceptual design methodology is proposed and formulated. Supporting the incorporation of multicriteria decision making tools into the design process, is another focus of this work where a number of frameworks are proposed to help the designers with assessment of criteria importance and interaction parameters. These frameworks are not only applicable in optimal design and design evaluation procedures, but also for determining possible ways for design improvements. Both data-driven methods as well as semantic-based optimization algorithms are used to identify the fuzzy parameters with limited available information about the design alternatives and designer preferences. Moreover, a fuzzy-based multi-objective approach has been undertaken for proposing and formulating a detailed design methodology. A unified performance evaluation index is introduced by the means of Choquet integrals and then optimized using a constrained particle swarm optimization (PSO) algorithm

Advances in Evolutionary Algorithms

With the recent trends towards massive data sets and significant computational power, combined with evolutionary algorithmic advances evolutionary computation is becoming much more relevant to practice. Aim of the book is to present recent improvements, innovative ideas and concepts in a part of a huge EA field

Uma contribuição à sistematização da obtenção de modelos matemáticos lineares para controle usando softwares de modelagem

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia de Automação e Sistemas, Florianópolis, 2019.O modelo de um sistema é uma representação, seja ela mental, física, gráfica ou matemática, realizada por observações do mundo real de acordo com certos padrões. A modelagem de sistemas é de extrema importância para o desenvolvimento da ciência e tecnologia. Sempre foi um desafio projetar, através de modelos matemáticos, sistemas e dados. Desde a Antiguidade, o ser humano procura descrever matematicamente sistemas experimentais para ajudá-lo a compreender os fenômenos reais e, assim, resolver questões relacionadas a eles. Com objetivo de desenvolver uma metodologia para gerar a modelagem matemática de sistemas dinâmicos, simples ou avançados, é proposto um estudo de caso para o Veículo Individual Compacto (VIC), utilizando conceitos relacionados ao método de modelagem em espaço de estados. Assim, este trabalho propõe uma contribuição à sistematização da obtenção de modelos matemáticos lineares para controle, apresentando os seus detalhes, evidenciando as ferramentas computacionais utilizadas, as estruturas dos métodos desenvolvidos na pesquisa, e os procedimentos adotados para a obtenção de um modelo que reduzem drasticamente a complexidade da modelagem. O caso em análise valida o método proposto, através dos resultados gerados, que podem ser utilizados futuramente em processos de otimização e análise de robustez, entre outros.Abstract: The model of a system is a representation that could be mental, physical, graphical or mathematically done by observing the real world, following certain standards. Systems modeling is of utmost importance for the development of science and technology. It has always been a challenge to conceive, through mathematical models, the systems and the observed data. Since early days, the humanity has been trying to describe mathematically experimental systems, to help to understand the real phenomena and solve some questions related to them. To aim to develop a methodology for generate the mathematical modeling of dynamic systems, whether simple or advanced, it is presented a case study here, faced to the Individual Compact Vehicle (ICV). This work proposes a contribution to the systematization of obtaining linear mathematical models for control, based on state space modeling method. The details of the methodology and the computational tools used are shown, as well the structures of the methods developed into this research, and the procedures adopted to obtain a model, which drastically reduce the complexity of modeling. The case study validates the methodology and suggests that results can be used for optimization, and robustness analysis, for example, as a further topic

Computational Approaches to Explainable Artificial Intelligence:Advances in Theory, Applications and Trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9 International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications

Computational approaches to Explainable Artificial Intelligence: Advances in theory, applications and trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9 International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications