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In this paper, an improved feed-forward inverse control scheme is proposed for transient waveform replication (TWR) on an electro-hydraulic shaking table (EHST). TWR is to determine whether a test article can remain operational and retain its structural integrity when subjected to a specific shock and vibration environment. Feed-forward inverse transfer function compensation is a useful technique to improve the tracking accuracy of the TWR on the EHST system due to their inherent hydraulic dynamics. Whenever a feed-forward inverse transfer function is employed, it is critical to design the identification accuracy of the inverse transfer function. A combined control strategy, which combines a feed-forward inverse transfer function compensation approach with a simple internal model control (IMC) and a real-time feedback controller, is proposed to minimize the effect of the system uncertainty and modeling error, and further to improve the tracking accuracy of the TWR. Thus, the proposed control strategy combines the merits of feed-forward inverse transfer function compensation and IMC. The procedure of the proposed control strategy is programmed in MATLAB/Simulink, and then is compiled to a real-time PC with Microsoft Visual Studio.NET for implementation. Simulation and experimental results demonstrated the viability of the proposed combined control strategy.

Abstract. The purpose of shaking tables is to replicate the desired motion to specimen, which needs to ensure not only the synchronization precision of two tables, but the tracking precision for the desired signal. Due to the nonlinearity of system and eccentric of load masses, both tracking and synchronous accuracy are poor. To solve this problem, this article proposes a novel hybrid controller combined a hybrid fuzzy PD cross-coupled controller (CCC) with an adaptive inverse controller (AIC). Based on state variable error optimal control idea, a 2-stage parallel hybrid fuzzy logic controller (FLC) composed of fuzzy PD and accelerated fuzzy PD is proposed to CCC to reduce synchronization error. In order to improve the tracking accuracy, an AIC based on recursive extended least square (RELS) algorithm is used to estimate the close-loop inverse transfer functions of double shaking tables to adaptively tune the drive signals. The combination of hybrid fuzzy PD CCC and AIC has the advantage of integrating a superiority of the two control techniques for better control performance. The procedure of the proposed control scheme is programmed, and tests are carried out in various conditions. The test results demonstrated the viability of the proposed hybrid control scheme.

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