Earthquake Engineering and Structural Dynamics

Caughey, T. K.

doi: 10.1002/(SICI)1096-9845(1998110)27:11<1125::AID-EQE791>3.0.CO;2-Spmid: N/A

Spencer, B. F.; Dyke, S. J.; Deoskar, H. S.

doi: 10.1002/(SICI)1096-9845(1998110)27:11<1127::AID-EQE774>3.0.CO;2-Fpmid: N/A

This paper presents the overview and problem definition for a benchmark structural control problem. The structure considered—chosen because of the widespread interest in this class of systems—is a scale model of a three‐storey building employing an active mass driver. A model for this structural system, including the actuator and sensors, has been developed directly from experimentally obtained data and will form the basis for the benchmark study. Control constraints and evaluation criteria are presented for the design problem. A simulation program has been developed and made available to facilitate comparison of the efficiency and merit of various control strategies. A sample control design is given to illustrate some of the design challenges. © 1998 John Wiley & Sons, Ltd.

Spencer, B. F.; Dyke, S. J.; Deoskar, H. S.

doi: 10.1002/(SICI)1096-9845(1998110)27:11<1141::AID-EQE775>3.0.CO;2-Spmid: N/A

In a companion paper (Spencer et al.), an overview and problem definition was presented for a well‐defined benchmark structural control problem for a model building configured with an Active Mass Driver (AMD). A second benchmark problem is posed here based on a high‐fidelity analytical model of a three‐storey, tendon‐controlled structure at the National Center for Earthquake Engineering Research (NCEER). The purpose of formulating this problem is to provide another setting in which to evaluate the relative effectiveness and implementability of various structural control algorithms. To achieve a high level of realism, an evaluation model is presented in the problem definition which is derived directly from experimental data obtained for the structure. This model accurately represents the behaviour of the laboratory structure and fully incorporates actuator/sensor dynamics. As in the companion paper, the evaluation model will be considered as the real structural system. In general, controllers that are successfully implemented on the evaluation model can be expected to perform similarly in the laboratory setting. Several evaluation criteria are given, along with the associated control design constraints. © 1998 John Wiley & Sons, Ltd.

Young, Peter M.; Bienkiewicz, Bogusz

doi: 10.1002/(SICI)1096-9845(1998110)27:11<1149::AID-EQE776>3.0.CO;2-1pmid: N/A

In this paper we develop a robust controller design for the Active Mass Driver (AMD) benchmark problem. The design process is based around the D–K iteration procedure for (complex) μ synthesis, together with a balanced truncation procedure to reduce the controller order. The final design is a third‐order linear controller, which utilizes only four accelerometer measurements, and has desirable rolloff properties (i.e. small required bandwidth, and a high degree of robustness). Despite the simplicity of the controller, it is able to yield quite good performance, while using only modest control authority. © 1998 John Wiley & Sons, Ltd.

Johnson, E. A.; Voulgaris, P. G.; Bergman, L. A.

doi: 10.1002/(SICI)1096-9845(1998110)27:11<1165::AID-EQE777>3.0.CO;2-8pmid: N/A

Reduced‐order, multiobjective optimal controllers are developed for the Notre Dame structural control building model benchmark. Standard H2/LQG optimal control excels at noise and disturbance rejection, but may have difficulty with actuator saturation and plant uncertainty. The benchmark problem is adapted to a multiobjective optimal control framework, using l1 and H∞ constraints to improve controller performance, especially attempting to reduce peak responses, avoid saturation, and improve robustness to unmodelled dynamics. The tradeoffs between H2 performance, output peak magnitudes, and robust stability are examined. Several optimal controllers and their performance on the benchmark are given. © 1998 John Wiley & Sons, Ltd.

Balas, Gary J.

doi: 10.1002/(SICI)1096-9845(1998110)27:11<1189::AID-EQE778>3.0.CO;2-Spmid: N/A

The structured singular value (μ) synthesis technique is used to design controllers for the Active Mass Damper (AMD) Benchmark problem. The motivation for using μ synthesis is its ability to directly incorporate performance and robustness objectives into a multivariable control design framework. In addition to stated performance objectives, robustness of the controllers to high‐frequency unmodelled dynamics (the neglected high‐frequency modes of the evaluation model), modelling error in the actuator dynamics and variations in the first structural natural frequency and damping value are considered in the design. The resulting controller achieves similar performance levels on the nominal evaluation model and the evaluation model with significant variations in its first natural frequency and damping values. © 1998 John Wiley & Sons, Ltd.

D'Amato, Fernando J.; Rotea, Mario A.

doi: 10.1002/(SICI)1096-9845(1998110)27:11<1203::AID-EQE779>3.0.CO;2-Bpmid: N/A

In this work we give a methodology for controller design and analysis which accounts for design criteria such as: (a) optimal system response to external disturbances, (b) robustness to modelling uncertainty, and (c) constraints on the controller order. The methodology is applied to a structural control benchmark problem sponsored by the ASCE Committee on Structural Control. The structural system considered consists of a scale model of a three‐storey building employing an active mass driver to suppress ground motion disturbances. The methodology proved effective for obtaining a satisfactory low‐order controller for this class of problems. © 1998 John Wiley & Sons, Ltd.

Bani‐Hani, Khaldoon; Ghaboussi, Jamshid

doi: 10.1002/(SICI)1096-9845(1998110)27:11<1225::AID-EQE780>3.0.CO;2-Tpmid: N/A

Methodology for active structural control using neural networks has been proposed by Ghaboussi and his co‐workers in the past several years. The control algorithm in the mathematically formulated methods is replaced by a neural network controller (neuro‐controller). Neuro‐controllers have been developed and applied in linear and nonlinear structural control. Neuro‐controllers are trained with the aid of the emulator neural networks. The emulator neural network is trained to learn the transfer function between the actuator signal and the sensor reading and it uses that past values of these quantities to predict the future values of the sensor readings. In this paper, we apply the previously developed neuro‐control method in the benchmark problem of the active tendon system. The emulator neural network is developed and trained using the evaluation model given in the benchmark problem which is considered to be the true representation of the active tendon system. However, a reduced‐order model has been developed and used, along with the emulator neural network, to train the neuro‐controller. The evaluation model represents the three story steel frame structure, including the actuator dynamics. The absolute acceleration of the first floor and the actuator piston displacement are used as feedback. Three neuro‐controllers, with different control criteria, have been developed and their performances have been evaluated with the prescribed performances indexes. The robustness of the neuro‐controllers in the presence of some severe uncertainties, has also been evaluated. © 1998 John Wiley & Sons, Ltd.

Wu, J. C.; Yang, J. N.; Agrawal, A. K.

doi: 10.1002/(SICI)1096-9845(1998110)27:11<1247::AID-EQE781>3.0.CO;2-Ipmid: N/A

In this paper, both the methods of continuous sliding mode control (CSMC) and continuous sliding mode control with compensators (CSMC&C) have been applied to two benchmark structures, namely, a building model equipped with an active mass driver system, and a building model equipped with an active tendon system. The CSMC&C strategy is a modification of CSMC to facilitate the design of static output feedback controllers and to provide a systematic tuning of the control effort. Due to the structural identification scheme used in the benchmark problems, in which the state variables are fictitious, one cannot take the full advantages of static output feedback controllers. As a result, an observer is used in CSMC, whereas a low‐pass filter is incorporated for each measurement in CSMC&C. The purpose of using low‐pass filters in CSMC&C is to transform the benchmark problems into strictly proper systems. The main advantage of the CSMC&C method is that the on‐line computational effort is reduced since the dimension of filters and compensator is much smaller than that of an observer. Simulation results based on the CSMC and CSMC&C methods are presented and compared with that of the LQG method. Robustness of stability and noise rejection for each controller design are also illustrated by examining the loop transfer function. Simulation results for the benchmark problems indicate that the control performances for LQG, CSMC and CSMC&C are quite comparable. © 1998 John Wiley & Sons, Ltd.

Battaini, M.; Casciati, F.; Faravelli, L.

doi: 10.1002/(SICI)1096-9845(1998110)27:11<1267::AID-EQE782>3.0.CO;2-Dpmid: N/A

The authors are engaged in a long‐term research project studying the potential of fuzzy control strategies for active structural control in civil engineering applications. The advantage of this approach is its inherent robustness and its ability to handle the non‐linear behaviour of the structure. Moreover, the computations for driving the controller are quite simple and can easily be implemented into a fuzzy chip. In this paper attention is focused on the response of a three‐storey frame, subjected to earthquake excitation, controlled by an active mass driver located on the top floor. The design and the implementation of the controller driving the AMD system are discussed. © 1998 John Wiley & Sons, Ltd.