Multiobjective Design Optimization of Electrostatic Rotary Microactuators Using Evolutionary Algorithms

  • Paolo Di Barba
  • Sławomir Wiak
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4029)


An example of soft computing applied to electrical engineering is presented and discussed. Attention is focused on the design techniques of MicroElectroMechanical Systems. In particular, the criterion of Pareto optimality is used to identify the optimal shape design of a rotary electrostatic microactuator. Accordingly, two algorithms of evolutionary optimization are presented and compared. The requirements in terms of know-how and computing facilities fit the resources of a research-and-development center of an industrial company.


Pareto Front Multiobjective Optimisation Pareto Optimal Front Torque Ripple Optimal Shape Design 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Wiak, S., Smółka, K., Rudnicki, M.: Modelling and Optimisation of an Intelligent Electrostatic Comb Accelerometer. In: Wiak, S., Krawczyk, A., Trlep, M. (eds.) Computer Engineering in Applied Electromagnetism, pp. 99–104. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  2. 2.
    Wiak, S., Cader, A., Drzymała, P., Welfle, H.: Virtual Modeling and Optical Design of Intelligent Micro-accelerometers. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds.) ICAISC 2004. LNCS (LNAI), vol. 3070, pp. 942–947. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  3. 3.
    Gardner, J.W., Varadan, V.K., Awadelkarim, O.O.: Microsensor MEMS and Smart Devices. Wiley, Chichester (2001)Google Scholar
  4. 4.
    Deb, K.: Multi-Objective Optimisation using Evolutionary Algorithms. Wiley, Chichester (2001)Google Scholar
  5. 5.
    Di Barba, P.: Silicon Electrostatic Microactuators: Numerical Models and Design Optimization. PhD Dissertation, Technical University of Ł?dź, Academic Year (2000-2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Paolo Di Barba
    • 1
  • Sławomir Wiak
    • 2
  1. 1.Department of Electrical EngineeringUniversity of PaviaPaviaItaly
  2. 2.Institute of Mechatronics and Information SystemsTechnical University of ŁódźŁódźPoland

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