Intelligent fuzzy optimal control of building structures

Abstract This paper describes an optimal adaptive and predictive control system and its digital simulations for a five-degree-of-freedom system subjected to earthquake loading. In this system, an active mass driver system and an equivalent variable mass system are employed as an active control method. Prediction of earthquake input and structural identification are performed by using neural networks based on the error back-propagation method. To get appropriate training data for structural identification, the genetic algorithm is employed. Optimization is performed by means of macimizing decision. In maximizing decision, optimal target control variables are determined by using assumed membership functions of target responses. Results of digital simulations show the effectiveness of the proposed control system.

[1]  B.M. Flax.  Intelligent buildings , 1991, IEEE Communications Magazine.

[2]  Mohamed Abdel-Rohman,et al.  Research Topics for Practical Implementation of Structural Control , 1987 .

[3]  James T. P. Yao,et al.  CONCEPT OF STRUCTURAL CONTROL , 1972 .

[4]  Richard Bellman,et al.  Decision-making in fuzzy environment , 2012 .

[5]  Akinori Tani,et al.  OPTIMAL ADAPTIVE AND PREDICTIVE CONTROL SYSTEM OF BUILDINGS BY MULTI-LAYERED NEURAL NETWORK AND FUZZY THEORY , 1994 .

[6]  Akinori Tani,et al.  Optimal Adaptive and Predictive Control System of Buildings by Neural Network and Fuzzy Theory , 1993 .

[7]  I. Matsuba,et al.  Application of neural sequential associator to long-term stock price prediction , 1991, [Proceedings] 1991 IEEE International Joint Conference on Neural Networks.

[8]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[9]  Ebrahim Mamdani,et al.  Applications of fuzzy algorithms for control of a simple dynamic plant , 1974 .

[10]  Satish Nagarajaiah,et al.  Hybrid Control of Structures Using Fuzzy Logic , 1996 .

[11]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[12]  Michael I. Jordan,et al.  Generic constraints on underspecified target trajectories , 1989, International 1989 Joint Conference on Neural Networks.

[13]  Geoffrey E. Hinton,et al.  Learning representations by back-propagating errors , 1986, Nature.

[14]  Jamshid Ghaboussi,et al.  Active Control of Structures Using Neural Networks , 1995 .

[15]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[16]  T. T. Soong,et al.  An Overview of Active Structural Control under Seismic Loads , 1991 .

[17]  Lucia Faravelli,et al.  Use of Adaptive Networks in Fuzzy Control of Civil Structures , 1996 .

[18]  Michael Moortgat,et al.  Structural control , 1997 .