Techno Press

Structural Engineering and Mechanics   Volume 61, Number 3, February10 2017, pages 347-357
Chaotic particle swarm optimization in optimal active control of shear buildings
Saeed Asil Gharebaghi and Ehsan Zangooei

Abstract     [Full Text]
    The applications of active control is being more popular nowadays. Several control algorithms have been developed to determine optimum control force. In this paper, a Chaotic Particle Swarm Optimization (CPSO) technique, based on Logistic map, is used to compute the optimum control force of active tendon system. A chaotic exploration is used to search the solution space for optimum control force. The response control of Multi-Degree of Freedom (MDOF) shear buildings, equipped with active tendons, is introduced as an optimization problem, based on Instantaneous Optimal Active Control algorithm. Three MDOFs are simulated in this paper. Two examples out of three, which have been previously controlled using Lattice type Probabilistic Neural Network (LPNN) and Block Pulse Functions (BPFs), are taken from prior works in order to compare the efficiency of the current method. In the present study, a maximum allowable value of control force is added to the original problem. Later, a twenty-story shear building, as the third and more realistic example, is considered and controlled. Besides, the required Central Processing Unit (CPU) time of CPSO control algorithm is investigated. Although the CPU time of LPNN and BPFs methods of prior works is not available, the results show that a full state measurement is necessary, especially when there are more than three control devices. The results show that CPSO algorithm has a good performance, especially in the presence of the cut-off limit of tendon force; therefore, can widely be used in the field of optimum active control of actual buildings.
Key Words
    Chaotic Particle Swarm Optimization; logistic map; instantaneous optimal active control; active tendon system; shear buildings; LPNN; BPFs
Saeed Asil Gharebaghi and Ehsan Zangooei : Civil Engineering Faculty, K. N. Toosi University of Technology, Tehran, Iran

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