Reliability‐based robust control for uncertain dynamical systems using feedback of incomplete noisy response measurements

A reliability‐based output feedback control methodology is presented for controlling the dynamic response of systems that are represented by linear state‐space models. The design criterion is based on a robust failure probability for the system. This criterion provides robustness for the controlled system by considering a probability distribution over a set of possible system models with a stochastic model of the excitation so that robust performance is expected. The control command signal can be calculated using incomplete response measurements at previous time steps without requiring state estimation. Examples of robust structural control using an active mass driver on a shear building model and on a benchmark structure are presented to illustrate the proposed method. Copyright © 2003 John Wiley & Sons, Ltd.     

A design‐variable‐based inelastic hysteretic model for beam–column connections

This paper presents a design‐variable‐based inelastic hysteretic model for beam–column connections. It has been well known that the load‐carrying capacity of connections heavily depends on the types and design variables even in the same connection type. Although many hysteretic connection models have been proposed, most of them are dependent on the specific connection type with presumed failure mechanisms. The proposed model can be responsive to variations both in design choices and in loading conditions. The proposed model consists of two modules: physical‐principle‐based module and neural network (NN)‐based module in which information flow from design space to response space is formulated in one complete model. Moreover, owing to robust learning capability of a new NN‐based module, the model can also learn complex dynamic evolutions in response space under earthquake loading conditions, such as yielding, post‐buckling and tearing, etc. Performance of the proposed model has been demonstrated with synthetic and experimental data of two connection types: extended‐end‐plate and top‐ and seat‐angle with double‐web‐angle connection. Furthermore, the design‐variable‐based model can be customized to any structural component beyond the application to beam–column connections. Copyright © 2007 John Wiley & Sons, Ltd.     

Rosenbrock‐based algorithms and subcycling strategies for real‐time nonlinear substructure testing

In this paper, Rosenbrock‐based algorithms originally developed for real‐time testing of linear systems with dynamic substructuring are extended for use on nonlinear systems. With this objective in mind and for minimal overhead, both two‐ and three‐stages linearly implicit real‐time compatible algorithms were endowed with the Jacobian matrices requiring only one evaluation at the beginning of each time step. Moreover, these algorithms were improved with subcycling strategies. In detail, the paper briefly introduces Rosenbrock‐based L‐Stable Real‐Time (LSRT) algorithms together with linearly implicit and explicit structural integrators, which are now commonly used to perform real‐time tests. Then, the LSRT algorithms are analysed in terms of linearized stability with reference to an emulated spring pendulum, which was chosen as a nonlinear test problem, because it is able to exhibit a large and relatively slow nonlinear circular motion coupled to an axial motion that can be set to be stiff. The accuracy analysis on this system was performed for all the algorithms described. Following this, a coupled spring‐pendulum example typical of real‐time testing is analysed with respect to both stability and accuracy issues. Finally, the results of representative numerical simulations and real‐time substructure tests, considering nonlinearities both in the numerical and the physical substructure, are explored. These tests were used to demonstrate how the LSRT algorithms can be used for substructuring tests with strongly nonlinear components. Copyright © 2010 John Wiley & Sons, Ltd.     

A risk‐based life cycle cost strategy for optimal design and evaluation of control methods for nonlinear structures

The lack of direct correspondence between control objectives and hazard risks over the lifetime of systems is a key shortcoming of current control techniques. This along with the inability to objectively analyze the benefits and costs of control solutions compared with conventional methods has hindered widespread application of control systems in seismic regions. To address these gaps, this paper offers 2 new contributions. First, it introduces risk‐based life cycle–cost (LCC) optimal control algorithms, where LCC is incorporated as the performance objective in the control design. Two strategies called risk‐based linear quadratic regulator and unconstrained risk‐based regulator are subsequently proposed. The considered costs include the initial cost of the structure and control system, LCC of maintenance, and probabilistically derived estimates of seismic‐induced repair costs and losses associated with downtime, injuries, and casualties throughout the life of the structure. This risk‐based framework accounts for uncertainties in both system properties and hazard excitations and uses outcrossing rate theory to estimate fragilities for various damage states. The second contribution of this work is a risk‐based probabilistic framework for LCC analysis of existing and proposed control strategies. The proposed control designs are applied to the nonlinear model of a 4‐story building subjected to seismic excitations. Results show that these control methods reduce the LCC of the structure significantly compared with the status quo option (benefits of up to $1 351 000). The advancements offered in this paper enhance the cost‐effectiveness of control systems and objectively showcase their benefits for risk‐informed decision making.     

Direct finite element method for nonlinear earthquake analysis of 3‐dimensional semi‐unbounded dam–water–foundation rock systems

A direct finite element method for nonlinear earthquake analysis of 2‐dimensional dam–water–foundation rock systems has recently been presented. The analysis procedure uses standard viscous‐damper absorbing boundaries to model the semi‐unbounded foundation‐rock and fluid domains and specifies the seismic input as effective earthquake forces at these boundaries. Presented in this paper is a generalization of the direct finite element method with viscous‐damper boundaries to 3‐dimensional dam–water–foundation rock systems. Step‐by‐step procedures for determining the effective earthquake forces starting from a ground motion specified at a control point on the foundation‐rock surface is developed, and several numerical examples are computed and compared with independent benchmark solutions to demonstrate the effectiveness of the analysis procedure for modeling 3‐dimensional systems.     

Probabilistic estimation of maximum inelastic displacement demands for performance‐based design

A probabilistic approach to estimate maximum inelastic displacement demands of single‐degree‐of‐freedom (SDOF) systems is presented. By making use of the probability of exceedance of maximum inelastic displacement demands for given maximum elastic spectral displacement and the mean annual frequency of exceedance of elastic spectral ordinates, a simplified procedure is proposed to estimate mean annual frequencies of exceedance of maximum inelastic displacement demands. Simplifying assumptions are thoroughly examined and discussed. Using readily available elastic seismic hazard curves the procedure can be used to compute maximum inelastic displacement seismic hazard curves and uniform hazard spectra of maximum inelastic displacement demands. The resulting maximum inelastic displacement demand spectra provide a more rational way of establishing seismic demands for new and existing structures when performance‐based approaches are used. The proposed procedure is illustrated for elastoplastic SDOF systems having known‐lateral strength located in a region of high seismicity in California. Copyright © 2007 John Wiley & Sons, Ltd.