Knowledge interaction with genetic programming in mechatronic systems design using bond graphs

This paper describes a unified network synthesis approach for the conceptual stage of mechatronic systems design using bond graphs. It facilitates knowledge interaction with evolutionary computation significantly by encoding the structure of a bond graph in a genetic programming tree representation. On the one hand, since bond graphs provide a succinct set of basic design primitives for mechatronic systems modeling, it is possible to extract useful modular design knowledge discovered during the evolutionary process for design creativity and reusability. On the other hand, design knowledge gained from experience can be incorporated into the evolutionary process to improve the topologically open-ended search capability of genetic programming for enhanced search efficiency and design feasibility. This integrated knowledge-based design approach is demonstrated in a quarter-car suspension control system synthesis and a MEMS bandpass filter design application.

[1]  Marc Parizeau,et al.  Open BEAGLE: A New Versatile C++ Framework for Evolutionary Computation , 2002, GECCO Late Breaking Papers.

[2]  Malcolm C. Smith.  ACHIEVABLE DYNAMIC RESPONSE FOR AUTOMOTIVE ACTIVE SUSPENSIONS. , 1995 .

[3]  Alan S. Perelson,et al.  System Dynamics: A Unified Approach , 1976, IEEE Transactions on Systems, Man, and Cybernetics.

[4]  Warren P. Seering,et al.  Synthesis of schematic descriptions in mechanical design , 1989 .

[5]  Pierre Borne,et al.  Pareto-optimality approach for flexible job-shop scheduling problems: hybridization of evolutionary algorithms and fuzzy logic , 2002, Math. Comput. Simul..

[6]  Neville Hogan,et al.  Impedance Control: An Approach to Manipulation: Part I—Theory , 1985 .

[7]  A. Preumont.  Vibration Control of Active Structures , 1997 .

[8]  N. Kyura,et al.  Mechatronics-an industrial perspective , 1996 .

[9]  G. W. Walker,et al.  Performance Limitations and Constraints for Active and Passive Suspensions: a Mechanical Multi-port Approach , 2000 .

[10]  Kun Wang,et al.  High-order medium frequency micromechanical electronic filters , 1999 .

[11]  Tzung-Pei Hong,et al.  Integrating fuzzy knowledge by genetic algorithms , 1998, IEEE Trans. Evol. Comput..

[12]  Carlos A. Coello Coello,et al.  Extracting and re-using design patterns from genetic algorithms using case-based reasoning , 2003 .

[13]  Robert W. Newcomb,et al.  Linear multiport synthesis , 1966 .

[14]  Hideyuki Takagi,et al.  Interactive evolutionary computation: fusion of the capabilities of EC optimization and human evaluation , 2001, Proc. IEEE.

[15]  James R. Rinderle,et al.  A transformational approach to mechanical design using a bond graph grammer , 1990 .

[16]  Jianjun Hu,et al.  System-Level Synthesis of MEMS via Genetic Programming and Bond Graphs , 2003, GECCO.

[17]  Neville Hogan,et al.  Controller design in the physical domain , 1991 .

[18]  H. D. L. Santos.  Introduction to Microelectromechanical(MEM)Microwave Systems , 1999 .

[19]  Bernhard Sendhoff,et al.  Knowledge Incorporation into Neural Networks From Fuzzy Rules , 2004, Neural Processing Letters.

[20]  Bruce H. Wilson,et al.  Using Bond Graphs to Synthesize Tree-structured Transfer Functions: Improved Frequency-Domain Analysis of Uncertain Systems , 1998 .

[21]  Neville Hogan,et al.  Impedance Control: An Approach to Manipulation , 1984, 1984 American Control Conference.

[22]  John R. Koza,et al.  Genetic Programming II , 1992 .

[23]  Jiachuan Wang,et al.  Interactive evolutionary solution synthesis in fuzzy set-based preliminary engineering design , 2003, J. Intell. Manuf..

[24]  Sushil J. Louis,et al.  Genetic learning for combinational logic design , 2005, Soft Comput..

[25]  Hu,et al.  Automated Design Methodology for Mechatronic Systems Using Bond Graphs and Genetic Programming , 2001 .

[26]  Jan F. Broenink.  Introduction to Physical Systems Modelling with Bond Graphs , 2000 .

[27]  John McPhee,et al.  On the use of linear graph theory in multibody system dynamics , 1996 .

[28]  Yong Zhou,et al.  Layout Synthesis of Accelerometers Master of , 1998 .

[29]  Peter J. Angeline,et al.  Genetic programming and emergent intelligence , 1994 .

[30]  Bernhard Sendhoff,et al.  Incorporation Of Fuzzy Preferences Into Evolutionary Multiobjective Optimization , 2002, GECCO.

[31]  Ian C. Parmee,et al.  Preferences and their application in evolutionary multiobjective optimization , 2002, IEEE Trans. Evol. Comput..