Genetic Programming and Creative Design of Mechatronic Systems

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Book{Li:2009:book,
  author =       "Shaobo Li and Jianjun Hu",
  title =        "Genetic Programming and Creative Design of Mechatronic
                 Systems",
  publisher =    "China Machine Press",
  year =         "2009",
  email =        "hujianju@gmail.com",
  keywords =     "genetic algorithms, genetic programming, bond graphs,
                 evolutionary design",
  isbn13 =       "9787111254157",
  URL =          "http://product.dangdang.com/product.aspx?product_id=20470877",
  abstract =     "Mechatronic product design is a multi-domain design
                 problem, which is different from the common design of
                 mechanical, electronic or hydraulic systems in
                 isolation. In a multi-domain system, there are many
                 energy conversion behaviors among energy sources of
                 different types. The designer often faces the challenge
                 of proposing an innovative solution that satisfies a
                 multitude of design objectives and constraints as
                 perfectly as practical. Traditionally, innovative
                 design of mechatronic products relies on engineers who
                 explore and accumulate experience over a long period of
                 time, and is incremental in nature. In 2005, the
                 authors were funded by the National Natural Science of
                 China under Grant 50575047 to investigate Creative
                 Design of Mechatronic Systems Based on Genetic
                 Programming. This book, which arises from that study
                 and preceding work by the authors and their colleagues,
                 covers several fields such as sustainable evolutionary
                 algorithms, bond graph theory, modeling and simulation
                 of bond graphs, genetic programming, scalable
                 evolutionary synthesis of dynamic system, and related
                 concepts. An innovative design method for mechatronic
                 products, based on genetic programming and simulation
                 of bond graphs, is presented. In this method, the model
                 of a mechatronic product is expressed as a bond graph
                 and genetic programming is used to search for the best
                 individual (representing the best system) in the design
                 space. A unique advantage of evolutionary synthesis is
                 its capability to produce innovative designs, starting
                 from a nearly blank sheet of paper, rather than relying
                 solely on expert knowledge and thereby, sometimes, not
                 discovering solutions that are radically different from
                 those already existing. Evolutionary synthesis can find
                 an innovative solution by searching in an open-ended
                 design space, subject only to the constraints imposed
                 by the designer based on the real requirements for the
                 system. This book is the first monograph on creative
                 design of mechatronic products using genetic
                 programming and bond graphs published in China. It
                 includes 11 chapters. Chapter 1 introduces the
                 background of the research, methods and techniques for
                 creative design of mechatronic systems, and the
                 objectives of the research; Chapter 2 mainly describes
                 two evolutionary algorithms GA and GP; Chapter 3
                 describes a sustainable GA; Chapter 4 presents
                 sustainable GP, including a sustainable evolutionary
                 model based on the HFC concept; Chapter 5 describes
                 sustainable SA (Simulated Annealing) based on the HFC
                 model; Chapter 6 introduces basic knowledge such as the
                 theory of bond graphs and system modeling and
                 simulation with bond graphs, including modular modeling
                 of mechatronic systems using bond graphs; Chapter 7
                 concerns evolutionary synthesis based on bond graphs
                 and GP, describing basic and advanced methods; Chapter
                 8 introduces GP-based design using Open BEAGLE, which
                 includes basic grammar, a class library, and program
                 design; Chapter 9 is an analysis of an example
                 evolutionary synthesis of an analog circuit; Chapter 10
                 presents an example of evolutionary synthesis of a
                 vibration absorber; and Chapter 11 concludes the book
                 with an analysis of an example of evolutionary
                 synthesis of a MEMS system.",
  abstract =     "The research in this book spans several fields,
                 including large-scale scientific computation,
                 simulation of mechatronic and control systems,
                 computational intelligence and genetic programming
                 technology, automated design, and parameter
                 optimization. By employing genetic programming and
                 simulation of dynamic systems in a bond graph
                 expression, this book provides a systematic exposition
                 of automated design of hybrid mechatronic systems that
                 include mechanical, electronic and control systems. The
                 research results in this book include a systematic
                 method for creative design of modern mechatronic
                 products. Based on GP, the hybrid topology algorithm,
                 mixing bond graphs with control block diagrams and
                 circuit diagrams, has many advantages, such as
                 searching structures in an open-ended way and
                 simultaneously searching for the optimal parameters of
                 the components of the structure. This hybrid searching
                 method breaks through the restrictions of the classical
                 parametric optimization of designs based on GA. And it
                 also implements automated design of complicated
                 systems. This hybrid search algorithm can evolve some
                 complicated mechatronic products with designs that are
                 superior to those done by human designers, in areas
                 such as circuits, controllers, vibration absorbers,
                 etc. The design theory, methods, and prototype systems
                 for evolutionary computation based on GP can also
                 potentially improve design practice for other types of
                 engineering systems. The important advances described
                 in this book give it profound academic value and
                 application significance.

                 The content of this book is easy to understand. It can
                 be used as a guide for creative design theory and
                 practice. It also will be a practical toolbox for
                 students in mechanical engineering, computer science
                 and related majors. Of course, it will also be a good
                 choice as teaching reference book for postgraduate
                 students or doctoral students. I enthusiastically
                 recommend it for study by persons interested in
                 studying the automated design of mechatronic
                 systems.

                 Erik D. Goodman Professor and Design Coordinator,
                 Electrical and Computer Engineering Professor,
                 Mechanical Engineering Michigan State University Vice
                 President for Technology, Red Cedar Technology, Inc.
                 Founding Chair, ACM Special Interest Group on Genetic
                 and Evolutionary Computation",
}

Genetic Programming entries for Shaobo Li Jianjun Hu

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