A novel constrained genetic algorithm for the optimization of active bar placement and feedback gains in intelligent truss structures

Authors:
Wenying Chen;Shaoze Yan;Keyun Wang;Fulei Chu
Affiliations:
Department of Precision Instruments and Mechanology, Tsinghua University, Beijing, P.R. China and Beijing Special Vehicle Research Institution, Beijing, P.R. China;Department of Precision Instruments and Mechanology, Tsinghua University, Beijing, P.R. China;Beijing Special Vehicle Research Institution, Beijing, P.R. China;Department of Precision Instruments and Mechanology, Tsinghua University, Beijing, P.R. China
Venue:
ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
Year:
2006

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Genetic algorithms + data structures = evolution programs (3rd ed.)

Genetic algorithms + data structures = evolution programs (3rd ed.)
Optimal placement of active members for truss structure using genetic algorithm

ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part II

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Abstract

In this paper, a novel constrained genetic algorithm is proposed and also successfully applied to the optimization of the active bar placement and feedback gains in intelligent truss structures. Based on the maximization of energy dissipation due to active control action, a mathematical model with constrains is initially developed. Then, according to the characteristics of the optimal problem, a new problem-specific encoding scheme, some special "genetic" operators and a problem-dependent repair algorithm are proposed and discussed. Numerical example of a 72-bar space intelligent truss structure is presented to demonstrate the rationality and validity of this methodology, and some useful conclusions are obtained.