Amirkabir University of Technology Amirkabir Journal of Mechanical Engineering 2008-6032 52 8 2019 04 28 Design of a Hybrid Adaptive Neuro-Fuzzy Inference System Proportional–Integral– Derivative Controller for Vibration Mitigation of a Structure against Earthquake Design of a Hybrid Adaptive Neuro-Fuzzy Inference System Proportional–Integral– Derivative Controller for Vibration Mitigation of a Structure against Earthquake 2293 2316 3385 10.22060/mej.2019.15513.6141 FA Seyed Mahdi Hadad Baygi dept. of electrical engineering, Khorasan Institute of Higher Education, Mashhad, Iran 0000-0001-6678-3149 Javad Faraji Dept.of electrical engineering, Khorasan Institute of Higher Education, Mashhad, Iran Ali Karsaz dept.of electrical engineering, Khorasan Institute of Higher Education, mashhad, Iran Journal Article 2018 12 26 This paper proposes a new hybrid controller based on combining adaptive neuro-fuzzy inference system method and proportional–integral–derivative controller, for vibration mitigation of structural system. The proposed controller although has the proportional–integral–derivative controller features, create a fuzzy inference system that has fewer bugs and errors than neural networks in calculations. The whale optimization algorithm is used for optimum tuning of the proposed method and also for identification of parameters related to the experimental structure. Considering four well-known earthquake real data the performance of the proposed controller is evaluated. Then the results are compared with two other controllers namely, fuzzy logic control and adaptive neuro-fuzzy inference system, which are designed for a four-degree of freedom building. The simulation results show that the proposed controller performs better than other strategies which are developed. The results obtained from the simulation show the better performance of the suggested method than the other control methods in reducing the displacement and acceleration of all floors. The results show that the maximum acceleration related to the building’s floors while using proposed method has improvement of 36.3% for the El Centro, 35.4% for the Northridge, 27.7% for the Athens and 22.5% for the Mexico City earthquakes regarding fuzzy control and adaptive neuro-fuzzy inference system control. This paper proposes a new hybrid controller based on combining adaptive neuro-fuzzy inference system method and proportional–integral–derivative controller, for vibration mitigation of structural system. The proposed controller although has the proportional–integral–derivative controller features, create a fuzzy inference system that has fewer bugs and errors than neural networks in calculations. The whale optimization algorithm is used for optimum tuning of the proposed method and also for identification of parameters related to the experimental structure. Considering four well-known earthquake real data the performance of the proposed controller is evaluated. Then the results are compared with two other controllers namely, fuzzy logic control and adaptive neuro-fuzzy inference system, which are designed for a four-degree of freedom building. The simulation results show that the proposed controller performs better than other strategies which are developed. The results obtained from the simulation show the better performance of the suggested method than the other control methods in reducing the displacement and acceleration of all floors. The results show that the maximum acceleration related to the building’s floors while using proposed method has improvement of 36.3% for the El Centro, 35.4% for the Northridge, 27.7% for the Athens and 22.5% for the Mexico City earthquakes regarding fuzzy control and adaptive neuro-fuzzy inference system control. https://mej.aut.ac.ir/article_3385_131f383b434fdf48079bff1e44e2d9a5.pdf