Publications

This paper presents an on-line learning failure-tolerant neural controller capable of controlling buildings subjected to severe earthquake ground motions. In the proposed scheme the neural controller aids a conventional H∞ controller designed to reduce the response of buildings under earthquake excitations. The conventional H∞ controller is designed to reduce the structural responses for a suite of severe earthquake excitations using specially designed frequency domain weighting filters. The neural controller uses a sequential learning radial basis function neural network architecture called extended minimal resource allocating network. The parameters of the neural network are adapted on-line with no off-line training. The performance of the proposed neural-aided controller is illustrated using simulation studies for a two degree of freedom structure equipped with one actuator on each floor. Results are presented for the cases of no failure and failure of the actuator on each of the two floors under several earthquake excitations. The study indicates that the performance of the proposed neural-aided controller is superior to that of the H∞ controller under no actuator failure conditions. In the presence of actuator failures, the performance of the primary H∞ controller degrades considerably, since actuator failures have not been considered for the design. Under these circumstances, the neural-aided controller is capable of controlling the acceleration and displacement structural responses. In many cases, using the neural-aided controller, the response magnitudes under failure conditions are comparable to the performance of the H∞ controller under no-failure conditions.

By introducing negative stiffness devices, this study further improves the maximum achievable damping ratio of conventional damped outrigger (CDO) structures with flexible perimeter columns. Dynamic characteristics of tall buildings with this novel negative stiffness damped outrigger (NSDO) are parametrically studied by solving the transcendental characteristic equations. An NSDO is able to improve the maximum achievable damping ratio to about 30% with less consumption of an outrigger damping coefficient (or a less amount of a viscous damper) as compared with a CDO. Numerical results showed that the NSDO is effective for both winds and earthquakes. For instance, an NSDO further decreases the maximum seismic interstory drift by 18.9% and reduces the total-wind-excited acceleration by 34.9%, with only a 20% outrigger damping consumption, as compared to a CDO. Because neither an NSDO nor CDO provides extra stiffness at low amplitudes of motion, an extra conventional outrigger (CO) is suggested to be placed at the top of a tall building when applying an NSDO in practical applications, and the effectiveness of an NSDO is also not compromised when an extra CO is placed.

Response of sliding isolated bridges with smart dampers in near fault earthquake ground motions is evaluated in this study. The smart damper used is a magnetorheological (MR) damper. A 1:20 scale single span sliding isolated bridge model with four sliding bearings and a MR damper is studied. New sliding mode controller is developed and implemented in real time. Several near fault ground motions recorded in the Northridge earthquake are used in the testing. Shake table test results of the scaled sliding isolated bridge model with MR damper are presented to demonstrate the effectiveness of the dampers. It is shown that the smart MR dampers can reduce displacements and forces in the piers further than the passive dampers. While these displacement reductions can be achieved by increasing the passive damping further, it can only be done at the expense of greater forces in the piers.

A newly developed structural damage monitoring technique is presented. The study focuses on capturing the initiation of multiple damages as they occur in a structure, which is similar to the concept of the fault detection filter. Previously, it has been shown that modified interaction matrix formulation provides a series of input error functions that generate a nonzero residual signal when the system experiences erroneous inputs. Error functions for each individual structural member are developed from the analogy between actuator failure and damageinduced residual force. When each individual error function is monitored, multiple damages as they occur in a structure can be simultaneously detected and isolated. Because the technique does not require frequency-domain measurements, it is readily applicable to online monitoring systems. This real-time technique also accommodates nonlinear breathing cracks and works for any type of excitation. A numerical simulation using a spring‐mass system and truss structure successfully demonstrates the proposed method.

In recent years, considerable attention has been paid to research and development of structural control devices, with particular emphasis on alleviation of wind and seismic response of buildings and bridges. In both areas, serious efforts have been undertaken in the last two decades to develop the structural control concept into a workable technology. Full-scale implementation of active control systems have been accomplished in several structures, mainly in Japan; however, cost effectiveness and reliability considerations have limited their wide spread acceptance. Because of their mechanical simplicity, low power requirements, and large, controllable force capacity, semiactive systems provide an attractive alternative to active and hybrid control systems for structural vibration reduction. In this paper we review the recent and rapid developments in semiactive structural control and its implementation in full-scale structures.

In civil, mechanical, and aerospace structures, full-field measurement has become necessary to estimate the precise location of precise damage and controlling purposes. Conventional full-field sensing requires dense installation of contact-based sensors, which is uneconomical and mostly impractical in a real-life scenario. Recent developments in computer vision-based measurement instruments have the ability to measure full-field responses, but implementation for long-term sensing could be impractical and sometimes uneconomical. To circumvent this issue, in this paper, we propose a technique to accurately estimate the full-field responses of the structural system from a few contact/non-contact sensors randomly placed on the system. We adopt the Compressive Sensing technique in the spatial domain to estimate the full-field spatial vibration profile from the few actual sensors placed on the structure for a particular time instant, and executing this procedure repeatedly for all the temporal instances will result in real-time estimation of full-field response. The basis function in the Compressive Sensing framework is obtained from the closed-form solution of the generalized partial differential equation of the system; hence, partial knowledge of the system/model dynamics is needed, which makes this framework physics-guided. The accuracy of reconstruction in the proposed full-field sensing method demonstrates significant potential in the domain of health monitoring and control of civil, mechanical, and aerospace engineering systems.

This paper addresses tracking-control of hysteretic systems using a gain-scheduled (GS) controller. Hysteretic system with variable stiffness and damping is represented as a quasi linear parameter varying (LPV) system. Designed controller is scheduled on the measured/estimated stiffness and damping in real-time. GS controller is constructed from the parameter dependent Lyapunov matrices, which are obtained as optimal solutions of linear matrix inequalities (LMIs) that ensures the feasibility solution for closed loop system performance. The proposed method is worked on semiactive independently variable stiffness (SAIVS) device. It is shown that the gain-scheduled controller developed for the quasi-LPV system results in excellent tracking performance even in the cases where robust-H∞ controller failed to function.