Time delay study for semi-active control of coupled adjacent structures using MR damper

Javad Katebi,Samira Mohammady Zadeh 국제구조공학회 2016 Structural Engineering and Mechanics, An Int'l Jou Vol.58 No.6

The pounding phenomenon in adjacent structures happens in severing earthquakes that can cause great damages. Connecting neighboring structures with active and semi-active control devices is an effective method to avoid mutual colliding between neighboring buildings. One of the most important issues in control systems is applying online control force. There will be a time delay if the prose of producing control force does not perform on time. This paper proposed a time-delay compensation method in coupled structures control, with semi-active Magnetorheological (MR) damper. This method based on Newmark’s integration is adopted to mitigate the time-delay effect. In this study, Lyapunov's direct approach is employed to compute demanded voltage for MR dampers. Using Lyapunov's direct algorithm guarantees the system stability to design a controller based on feedback. Because of the strong nonlinearity of MR dampers, the equation of motion of coupled structures becomes an involved equation, and it is impossible to solve it with the common time step methods. In present paper modified Newmark-Beta integration based on the instantaneous optimal control algorithm, used to solve the involved equation. In this method, the response of a coupled system estimated base on optimal control force. Two MDOF structures with different degrees of freedom are finally considered as a numeric example. The numerical results show, the Newmark compensation is an efficient method to decrease the negative effect of time delay in coupled systems; furthermore, instantaneous optimal control algorithm can estimate the response of structures suitable.

A novel multi-feature model predictive control framework for seismically excited high-rise buildings

Javad Katebi,Afshin Bahrami Rad,Javad Palizvan Zand 국제구조공학회 2022 Structural Engineering and Mechanics, An Int'l Jou Vol.83 No.4

In this paper, a novel multi-feature model predictive control (MPC) framework with real-time and adaptive performances is proposed for intelligent structural control in which some drawbacks of the algorithm including, complex control rule and non-optimality, are alleviated. Hence, Linear Programming (LP) is utilized to simplify the resulted control rule. Afterward, the Whale Optimization Algorithm (WOA) is applied to the optimal and adaptive tuning of the LP weights independently at each time step. The stochastic control rule is also achieved using Kalman Filter (KF) to handle noisy measurements. The Extreme Learning Machine (ELM) is then adopted to develop a data-driven and real-time control algorithm. The efficiency of the developed algorithm is then demonstrated by numerical simulation of a twenty-story high-rise benchmark building subjected to earthquake excitations. The competency of the proposed method is proven from the aspects of optimality, stochasticity, and adaptivity compared to the KF-based MPC (KMPC) and constrained MPC (CMPC) algorithms in vibration suppression of building structures. The average value for performance indices in the near-field and far-field (El earthquakes demonstrates a reduction up to 38.3% and 32.5% compared with KMPC and CMPC, respectively.

A generalized ANFIS controller for vibration mitigation of uncertain building structure

Javad Palizvan Zanda,Javad Katebi,Saman Yaghmaei-Sabegh 국제구조공학회 2023 Structural Engineering and Mechanics, An Int'l Jou Vol.87 No.3

A novel combinatorial type-2 adaptive neuro-fuzzy inference system (T2-ANFIS) and robust proportional integral derivative (PID) control framework for intelligent vibration mitigation of uncertain structural system is introduced. The fuzzy logic controllers (FLCs), are designed independently of the mathematical model of the system. The type-1 FLCs, have a limited ability to reduce the effect of uncertainty, due to their fuzzy sets with a crisp degree of membership. In real applications, the consequent part of the fuzzy rules is uncertain. The type-2 FLCs, are robust to the fuzzy rules and the process parameters due to the fuzzy degree of membership functions and footprint of uncertainty (FOU). The adaptivity of the proposed method is provided with the optimum tuning of the parameters using the neural network training algorithms. In our approach, the PID control force is obtained using the generalized type-2 neuro-fuzzy in such a way that the stability and robustness of the controller are guaranteed. The robust performance and stability of the presented framework are demonstrated in a numerical study for an eleven-story seismically-excited building structure combined with an active tuned mass damper (ATMD). The results indicate that the introduced type-2 neuro-fuzzy PID control scheme is effective to attenuate plant states in the presence of the structured and unstructured uncertainties, compared to the conventional, type-1 FLC, type-2 FLC, and type-1 neuro-fuzzy PID controllers.

Optimal deep machine learning framework for vibration mitigation of seismically-excited uncertain building structures

Afshin Bahrami Rad,Javad Katebi,Saman Yaghmaei-Sabegh 국제구조공학회 2023 Structural Engineering and Mechanics, An Int'l Jou Vol.88 No.6

Deep extreme learning machine (DELM) and multi-verse optimization algorithms (MVO) are hybridized for designing an optimal and adaptive control framework for uncertain buildings. In this approach, first, a robust model predictive control (RMPC) scheme is developed to handle the problem uncertainty. The optimality and adaptivity of the proposed controller are provided by the optimal determination of the tunning weights of the linear programming (LP) cost function for clustered external loads using the MVO. The final control policy is achieved by collecting the clustered data and training them by DELM. The efficiency of the introduced control scheme is demonstrated by the numerical simulation of a ten-story benchmark building subjected to earthquake excitations. The results represent the capability of the proposed framework compared to robust MPC (RMPC), conventional MPC (CMPC), and conventional DELM algorithms in structural motion control.

A developed model predictive control scheme for vibration attenuation of building structures

Afshin Bahrami Rad,Mahdi Nouri,Javad Katebi,Seyyed Arash Mousavi Ghasemi 국제구조공학회 2021 Smart Structures and Systems, An International Jou Vol.27 No.4

Model predictive control (MPC) is an optimal control algorithm in which the current control action is obtained by solving an optimization problem in the presence of hard and soft constraints in the finite time horizons sequentially. In most cases, neglecting the effects of the external loads in predicting the future responses of the structures lead to inaccurate control action. Therefore, it could be beneficial to consider the effects of external loads in the future within the MPC to improve its accuracy. In this paper, a developed model predictive control (DMPC) scheme is introduced. For this purpose, a forecasting seismic excitation model is formulated by two sequential autoregressive (AR) models. One of those estimates the future output of the seismic excitation and the second one enhances the estimation accuracy. Then, the efficiency of the presented approach is demonstrated by the numerical study of two benchmark buildings equipped with an active tuned mass damper (ATMD). The performance of the proposed MPC is finally compared with the conventional and ideal MPCs. The numerical outputs prove the competency and higher conformity of the proposed MPC with the ideal one almost in all of the cases. Twelve benchmark performance indices are also utilized for determining the superiority of the method. The average conformity values for all of the performance indices for the proposed method in the three- and nine-story buildings are by up to 17.75% and 9% more than the values in conventional one, respectively.

Computational optimized finite element modelling of mechanical interaction of concrete with fiber reinforced polymer

Khosro Shahpoori Arani,Yousef Zandi,Binh Thai Pham,M.A. Mu’azu,Javad Katebi,Mohammad Mohammadhassani,Seyedamirhesam Khalafi,Edy Tonnizam Mohamad,Karzan Wakil,Majid Khorami 사단법인 한국계산역학회 2019 Computers and Concrete, An International Journal Vol.23 No.1

This paper presents a computational rational model to predict the ultimate and optimized load capacity of reinforced concrete (RC) beams strengthened by a combination of longitudinal and transverse fiber reinforced polymer (FRP) composite plates/sheets (flexure and shear strengthening system). Several experimental and analytical studies on the confinement effect and failure mechanisms of fiber reinforced polymer (FRP) wrapped columns have been conducted over recent years. Although typical axial members are large-scale square/ rectangular reinforced concrete (RC) columns in practice, the majority of such studies have concentrated on the behavior of small-scale circular concrete specimens. A high performance concrete, known as polymer concrete, made up of natural aggregates and an orthophthalic polyester binder, reinforced with non-metallic bars (glass reinforced polymer) has been studied. The material is described at micro and macro level, presenting the key physical and mechanical properties using different experimental techniques. Furthermore, a full description of non-metallic bars is presented to evaluate its structural expectancies, embedded in the polymer concrete matrix. In this paper, the mechanism of mechanical interaction of smooth and lugged FRP rods with concrete is presented. A general modeling and application of various elements are demonstrated. The contact parameters are defined and the procedures of calculation and evaluation of contact parameters are introduced. The method of calibration of the calculated parameters is presented. Finally, the numerical results are obtained for different bond parameters which show a good agreement with experimental results reported in literature.