Attitude synchronous tracking control of double shaking tables based on hybrid fuzzy logic cross-coupled controller and adaptive inverse controller

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.