Towards computer-automated mechatronic design and optimization using linear graphs and evolutionary computing

A comparison of literature between the linear graph (LG) and bond graph (BG) approaches shows that the surpassing of BGs to LGs in applications related to the modeling of mechatronic systems is driven primarily by a lack of available LG-based software. As a result, a robust software toolbox called LGtheory has been developed for automating the evaluation of LG models in the MATLAB programming environment. This thesis details the development of LGtheory, and the algorithms and procedures employed for the evaluation of LG models. In addition, demonstrations of this toolbox to a process for automating the design of electronic filter circuits, as well as, the modeling and simulation of the dynamics of a mobile robotic system are presented. The results of these demonstrations validate the accuracy of the LGtheory toolbox for modeling complex multi-domain systems, and provides the methodological basis for the automated design of mechatronic systems using LGs

Topology Considerations in Hybrid Electric Vehicle Powertrain Architecture Design.

Optimal system architecture (topology or configuration) design has been a challenging design problem because of its combinatorial nature. Parametric optimization studies make design decisions assuming a given architecture but there has been no general methodology that addresses design decisions on the system architecture itself. Hybrid Electric Vehicle (HEV) powertrains allow various architecture alternatives created by connecting the engine, motor/generators and the output shaft in different ways through planetary gear systems. Addition of clutches to HEV powertrains allows changing the connection arrangement (configuration) among the powertrain components during the vehicle operation. Architectures with this capability are referred to as multi-mode architectures while architectures with fixed configurations are referred to as single-mode architectures. HEV architecture optimization requires designing the powertrain’s configuration and its sizing simultaneously. Additionally, evaluation of an HEV architecture design depends on a power management (control) strategy that distributes the power demand to the engine and motor/generators. Including this control problem increases the complexity of the HEV architecture design problem. This dissertation focuses on a general methodology to make design decisions on HEV powertrain architecture and component sizes. The representation of the architecture design problem is critical to solving this problem. A new general representation capable of describing all architecture alternatives is introduced. Using the representation, all feasible configurations are generated where these feasible configurations are used to create single- and multi-mode HEV architectures. Single-mode and multi-mode architecture design problems considering fuel economy, vehicle performance and architecture complexity are formulated separately and solution strategies are developed. The high complexity of the resulting optimization problem does not allow us to claim true optimality rigorously; therefore, the terms ``promising" or ``near-optimal" are more accurate in characterizing our results. The results show that different architectures must be designed for different applications. The case studies designing architectures for some available vehicles from the market find the architectures already implemented in these vehicles under some design constraints. Alternative architectures that improve these designs under different design constraints are also demonstrated. Architectures for a new application that is not available in the market are also designed.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111412/1/bayrak_1.pd

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

Tools for Modelling and Identification with Bond Graphs and Genetic Programming

The contributions of this work include genetic programming grammars for bond graph modelling and for direct symbolic regression of sets of differential equations; a bond graph modelling library suitable for programmatic use; a symbolic algebra library specialized to this use and capable of, among other things, breaking algebraic loops in equation sets extracted from linear bond graph models. Several non-linear multi-body mechanics examples are pre- sented, showing that the bond graph modelling library exhibits well-behaved simulation results. Symbolic equations in a reduced form are produced au- tomatically from bond graph models. The genetic programming system is tested against a static non-linear function identification problem using type- less symbolic regression. The direct symbolic regression grammar is shown to have a non-deceptive fitness landscape: perturbations of an exact pro- gram have decreasing fitness with increasing distance from the ideal. The planned integration of bond graphs with genetic programming for use as a system identification technique was not successfully completed. A catego- rized overview of other modelling and identification techniques is included as context for the choice of bond graphs and genetic programming

SciTech News Volume 70, No. 2 (2016)

Table of Contents: Columns and Reports From the Editor 3 Division News Science-Technology Division 4 New Members 6 Chemistry Division 7 New Members11 Engineering Division 12 Aerospace Section of the Engineering Division 17 Reviews Sci-Tech Book News Reviews 1

Polynomial modeling for time-varying systems based on a particle swarm optimization algorithm

In this paper, an effective particle swarm optimization (PSO) is proposed for polynomial models for time varying systems. The basic operations of the proposed PSO are similar to those of the classical PSO except that elements of particles represent arithmetic operations and variables of time-varying models. The performance of the proposed PSO is evaluated by polynomial modeling based on various sets of time-invariant and time-varying data. Results of polynomial modeling in time-varying systems show that the proposed PSO outperforms commonly used modeling methods which have been developed for solving dynamic optimization problems including genetic programming (GP) and dynamic GP. An analysis of the diversity of individuals of populations in the proposed PSO and GP reveals why the proposed PSO obtains better results than those obtained by GP