NEES @ UC San Diego

Controller

The LHPOST is controlled by the proven yet advanced technology MTS 469D digital control system, which is an integrated control solution including all computer hardware, software, transducers, data acquisition electronics, and cabling necessary for system operation. The system provides shake table tuning, system operation, and test execution in real time. The MTS Seismic Digital Control Software provides an advanced graphical user interface (GUI). Full functionality is provided through the GUI for system tuning, test set-up and operation, table data acquisition, and advanced high-level adaptive control for high fidelity earthquake waveform reproduction. The control software includes a set of high-level fixed control techniques such as Three-Variable Control (TVC: displacement, velocity, and acceleration) for high fidelity reproduction across a wide bandwidth, Delta Pressure Stabilization (DPS) for effectively dampening oil column compliance to allow for higher gains settings across a wider bandwidth, Servo-valve Flow Linearization (SFL) for effectively removing the inherent non-linearities present in all servo- hydraulic systems, and Resonance Canceling Non-Linear Notch Filters for extended system response in the presence of significant specimen and system resonances. The MTS 469D control system also includes a set of adaptive control techniques such as Amplitude Phase Control (APC) for automatic correction of amplitude and phase errors during sine wave testing, Adaptive Harmonic Cancellation (AHC) for control and elimination of harmonic distortions during sine wave testing, Adaptive Inverse Control (AIC) for reducing linear distortions during random waveform testing, and On Line Iteration (OLI) for reducing the effects of non-linear distortion causes during random waveform testing when the highest levels of waveform fidelity are required. AIC and OLI control techniques are described in more detail here.

NEHRPNSFNEEScommNEESIAS Accredited

The Large High-Performance Outdoor Shake Table is supported in part by the George E. Brown, Jr. Network for Engineering Simulation (NEES) program of the National Science Foundation under Award Number CMMI-0927178.

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