Design of Quantitative Feedback Control System for the Three Axes Hydraulic Road Simulator

Kim, Jin-Wan; Xuan, Dongji; Kim, Young‐Bae

doi:10.3795/ksme-a.2008.32.3.280

Cited by 1 publication

(1 citation statement)

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“…In Kaddissi, Kenne´, and Saad (2007), system parameters were identified based on the recursive least squares method and nonlinear backstepping approach was studied for a hydraulic servo system. Quantitative feedback control was used for a three axis hydraulic road simulator to reproduce the random input signal (Kim, Xuan, and Kim 2008). It illustrated a tracking performance of the closed-loop control system, but it need to know the system's transfer function.…”

Section: Introductionmentioning

confidence: 99%

Acceleration amplitude-phase regulation for electro-hydraulic servo shaking table based on LMS adaptive filtering algorithm

Yao

Jiang

et al. 2012

International Journal of Control

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Electro-hydraulic servo shaking table usually requires good control performance for acceleration replication. The poles of the electro-hydraulic servo shaking table are placed by three-variable control method using pole placement theory. The system frequency band is thus extended and the system stability is also enhanced. The phase delay and amplitude attenuation phenomenon occurs in electro-hydraulic servo shaking table corresponding to an acceleration sinusoidal input. The method for phase delay and amplitude attenuation elimination based on LMS adaptive filtering algorithm is proposed here. The task is accomplished by adjusting the weights using LMS adaptive filtering algorithm when there exits phase delay and amplitude attenuation between the input and its corresponding acceleration response. The reference input is weighted in such a way that it makes the system output track the input efficiently. The weighted input signal is inputted to the control system such that the output phase delay and amplitude attenuation are all cancelled. The above concept is used as a basis for the development of amplitude-phase regulation (APR) algorithm. The method does not need to estimate the system model and has good real-time performance. Experimental results demonstrate the efficiency and validity of the proposed APR control scheme.

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Section: Introductionmentioning

confidence: 99%