The conventional isolation structure with rubber bearings exhibits large deformation characteristics when subjected to infrequent earthquakes, which may lead to failure of the isolation layer. Although passive dampers can be used to reduce the layer displacement, the layer deformation and superstructure acceleration responses will increase in cases of fortification earthquakes or frequently occurring earthquakes. In addition to secondary damages and loss of life, such excessive displacement results in damages to the facilities in the structure. In order to overcome these shortcomings, this paper presents a structural vibration control system where the base isolation system is composed of rubber bearings with magnetorheological (MR) damper and are regulated using the innovative control strategy. The high-order single-step algorithm with continuity and switch control strategies are applied to the control system. Shaking table test results under various earthquake conditions indicate that the proposed isolation method, compared with passive isolation technique, can effectively suppress earthquake responses for acceleration of superstructure and deformation within the isolation layer. As a result, this structural control method exhibits excellent performance, such as fast computation, generic real-time control, acceleration reduction and high seismic energy dissipation etc. The relative merits of the continuity and switch control strategies are also compared and discussed.

An evolving encoding scheme is presented in this article for a fuzzy-based nonlinear system identification scheme, using the subtractive fuzzy C-mean clustering and a modified version of non-dominated sorting genetic algorithm. This method is able to automatically select the best inputs as well as the structure of the fuzzy model such as rules and membership functions. Moreover, three objective functions are considered to satisfy both accuracy and compactness of the model. The developed method is then employed to identify both forward and inverse models of a highly nonlinear structural control device, that is, magnetorheological damper. Experimental results showed that the proposed evolving Takagi–Sugeno–Kang fuzzy model can identify and grasp the nonlinear behaviour of magnetorheological damper very well with minimal number of inputs and fuzzy rules.

In the past decades, base isolation techniques have become increasingly popular for seismic protection of civil structures owing to its capability of decoupling buildings from harmful ground motion. However, it has been recognised recently that the traditional passive base isolation technique could encounter a serious problem during earthquakes due its incapability in adjusting the isolation frequency to cope with the unpredictability and diversity of earthquakes. To address this challenge, a great deal of research efforts have been conducted to improve traditional base isolation systems, most of which focused on hybrid supplementary devices (passive, active and semi-active types) for the isolators to control displacement or to dissipate seismic energy. On the other hand, the most effective approach to address the aforementioned challenge should lay on varying isolator stiffness in real-time to achieve real-time spontaneous decoupling. A recent advance of the development of an adaptive magneto-rheological elastomer base isolator has brought such idea to reality as the new magneto-rheological elastomer base isolator is capable to alter its stiffness significantly in real-time. In this article, an innovative smart base isolation system employing such magneto-rheological elastomer isolator is proposed and a novel frequency control algorithm is developed to shift the fundamental frequency of the structure away from the dominant frequency range of earthquakes. Such design enables the building to avoid resonant state in real-time according to the on-coming spectrum of the earthquakes. Extensive simulation has been conducted using a five-storey benchmark model with the isolation system, and testing results indicate that the proposed control system is able to significantly suppress both the floor accelerations and inter-storey drifts simultaneously under different earthquakes.

A novel semi-active control method for a seismically excited nonlinear benchmark building equipped with magnetorheological (MR) dampers is presented and evaluated in this paper. While Linear Quadratic Gaussian (LQG) controller is designed to estimate the optimal control force of a MR damper, the required voltage input for the damper to produce such control force is achieved by a proposed optimal Takagi- Sogeno(T-S) fuzzy inverse model. The proposed T-S fuzzy inverse model of dampers is derived using subtractive clustering, non-dominated sorting genetic algorithm II (NSGAII) and adaptive neuro-fuzzy inference systems (ANFIS). The effectiveness of this strategy is illustrated and verified using simulated response of a 20-storey full-scale nonlinear benchmark building excited by several historical earthquake records. The designed semi-active system is compared with the performances of active control as well as clipped optimal control (COC) systems, which are based on the same nominal controller as is used in this study. The results are discussed based on the evaluation criteria suggested for the benchmark problem by International Association for Structural Control and Monitoring (IASCM) for comparison with other algorithms and demonstrate the superiority of this scheme over other strategies