Control of smart non-linear base-isolated structures using optimal adaptive neural network-based PID controller

Document Type : Research Article

Authors

1 Department of Electrical Engineering, Technical and Vocational University (TVU), Tehran, Iran

2 Department of Civil Engineering, Birjand University of Technology, Birjand, Iran

Abstract

This paper aims to propose an adaptive control approach for the PID controller known as ANN-OPID controller with simultaneous use of the advantages of the classical PID controller and neural networks so that it can provide better seismic performance than the optimal PID controller tuned by the teaching–learning-based optimization (TLBO) algorithm. In this approach, the structural dynamic is estimated using a neural network block and hence the parameters of the PID controller are adjusted adaptively. The seismic performance evaluation of the proposed controller is compared with the conventional optimal PID controller for an 8-story smart base-isolated structure subjected to various near-field and far-field earthquakes. Overall, the results obtained for the studied structure subjected to six earthquakes show that the TLBO-PID controller leads to a reduction of 24% and 25% in the maximum base displacement and its root mean square (RMS), an increase of 24% and 11% in the maximum acceleration and its RMS of superstructure floors and an increase of 6% and 6% in the maximum drift and its RMS of superstructure floors. However, the proposed ANN-OPID controller approach causes a reduction of 35% and 33% in the maximum base displacement and its RMS, a reduction of 9% and 7% in the maximum superstructure acceleration and its RMS, and a reduction of 5% and 6% in the maximum drift and its RMS of superstructure floors. Consequently, the proposed ANN-OPID controller can give a simultaneous reduction of the base displacement, acceleration, and drift of superstructure floors, while the TLBO-PID controller reduces the base displacement at the cost of an increase in acceleration and drift of superstructure floors.

Keywords

Main Subjects

References

[1] F. Naeim, J.M. Kelly, Design of seismic isolated structures: from theory to practice, John Wiley & Sons, (1999).
[2] H.J. Lee, G. Yang, H.J. Jung, B.F. Spencer, I.W. Lee, Semi‐active neurocontrol of a base‐isolated benchmark structure. Structural Control and Health Monitoring, 13(2‐3) (2006) 682-692.
[3] S. Nagarajaiah, S. Sahasrabudhe, Seismic response control of smart sliding isolated buildings using variable stiffness systems: an experimental and numerical study. Earthquake engineering & structural dynamics, 35(2) (2006) 177-197.
[4] M. Ramezani, M.S. Labafzadeh, Passive and semi-active vibration control of base-isolated structure under blast loading at medium to long distances, Amirkabir Journal of Civil Engineering, 54(2) (2022) 435-456.
[5] M. Seify Asghshahr, S. Rafiei, Seismic Response of Base-isolated Dual-system Reinforced Concrete Buildings at a Near-fault Site, Amirkabir Journal of Civil Engineering, 54(4) (2022) 1607-1630.
[6] R. Guclu, Sliding mode and PID control of a structural system against earthquake. Mathematical and Computer Modelling, 44(1-2) (2006) 210-217.
[7] N. Aguirre, F. Ikhouane, J. Rodellar, Proportional-plus-integral semiactive control using magnetorheological dampers, Journal of Sound and Vibration, 330(10) (2011) 2185-2200.
[8] S.M. Nigdeli, M.H. Boduroğlu, Active tendon control of torsionally irregular structures under near‐fault ground motion excitation, Computer‐Aided Civil and Infrastructure Engineering, 28(9) (2013) 718-736.
[9] S.M. Nigdeli, Effect of feedback on PID controlled active structures under earthquake excitations. Earthquakes and Structures, 6(2) (2014) 217-235.
[10] S. Etedali, S. Tavakoli, M.R. Sohrabi, Design of a decoupled PID controller via MOCS for seismic control of smart structures. Earthquakes and Structures, 10(5) (2016) 1067-1087.
[11] M. Arif Şen, M. Tinkir, M. Kalyoncu, Optimisation of a PID controller for a two-floor structure under earthquake excitation based on the bees algorithm. Journal of Low Frequency Noise, Vibration and Active Control, 37(1) (2018) 107-127.
[12] S. Etedali, A new modified independent modal space control approach toward control of seismic-excited structures, Bulletin of Earthquake Engineering, 15(10) (2017) 4215-4243.
[13] M. Shahi,  M.R. Sohrabi, S. Etedali, Seismic control of high-rise buildings equipped with ATMD including soil-structure interaction effects, Journal of Earthquake and Tsunami, 12(03) (2018) 1850010.
[14] J.P. Zand, J. Sabouri, J. Katebi, M. Nouri, A new time-domain robust anti-windup PID control scheme for vibration suppression of building structure, Engineering Structures, 244 (2021) 112819.
[15] S. Etedali, M.R. Sohrabi, S. Tavakoli, Optimal PD/PID control of smart base isolated buildings equipped with piezoelectric friction dampers. Earthquake Engineering and Engineering Vibration, 12(1) (2013) 39-54.
[16] S. Etedali, Sensitivity analysis on optimal PID controller for nonlinear smart base-isolated structures. International Journal of Structural Stability and Dynamics, 19(07) (2019) 1950080.
[17] A.A. Zamani, S. Tavakoli, S. Etedali, Control of piezoelectric friction dampers in smart base-isolated structures using self-tuning and adaptive fuzzy proportional–derivative controllers. Journal of Intelligent Material Systems and Structures, 28(10) (2017) 1287-1302.
[18] A.A. Zamani, S. Tavakoli, S. Etedali, J. Sadeghi, Adaptive fractional order fuzzy proportional–integral–derivative control of smart base-isolated structures equipped with magnetorheological dampers. Journal of Intelligent Material Systems and Structures, 29(5) (2018) 830-844.
[19] A.A. Zamani, S. Tavakoli, S. Etedali, J. Sadeghi, Online tuning of fractional order fuzzy PID controller in smart seismic isolated structures. Bulletin of Earthquake Engineering, 16(7) (2018) 3153-3170.
[20] D. Ma, , M. Song, P. Yu, J. Li, Research of RBF-PID control in maglev system, Symmetry, 12(11) (2020) 1780.
[21] Y. Zhong, X. Huang, P. Meng, F. Li, PSO-RBF neural network PID control algorithm of electric gas pressure regulator, In Abstract and Applied Analysis, Hindawi 2014 (2014).
[22] S. Etedali, A.A. Zamani, Semi-active control of nonlinear smart base-isolated structures using MR damper: sensitivity and reliability analyses. Smart Materials and Structures, 31(6) (2022) 065021.
[23] R.V. Rao, V.J. Savsani, D.P. Vakharia, Teaching–learning-based optimization: a novel method for constrained mechanical design optimization problems, Computer-aided design, 43(3) (2011) 303-315.
[24] S. Nagarajaiah, S. Narasimhan, Seismic control of smart base isolated buildings with new semiactive variable damper, Earthquake Engineering & Structural Dynamics, 36(6) (2007) 729-749.
[25] A.N. Sharkawy, Principle of neural network and its main types, Journal of Advances in Applied & Computational Mathematics, 7 (2020) 8-19.
[26] H. Yu, T. Xie, S. Paszczyñski, B.M. Wilamowski, Advantages of radial basis function networks for dynamic system design, IEEE Transactions on Industrial Electronics, 58(12) (2011) 5438-5450.
[27] P. Jeatrakul, K.W. Wong, Comparing the performance of different neural networks for binary classification problems, In 2009 Eighth International Symposium on Natural Language Processing, (2009) 111-115.
[28] Applied Technology Council, Quantification of building seismic performance factors, US Department of Homeland Security, FEMA, (2009).
Amirkabir Journal of Civil Engineering
Volume 55, Issue 8
November 2023
Pages 1661-1676

Files

Share

How to cite

Statistics