2001
DOI: 10.1098/rsta.2001.0862
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Adaptive control of shaking tables using the minimal control synthesis algorithm

Abstract: Traditional shaking-table testing has been limited by the effectiveness of conventional fixed-gain algorithms used in their control. These algorithms are normally based on linear models of the shaking table and specimen, whose parameters are assumed to be fixed for the duration of the test. Although the influence of the specimen in the overall system dynamics can be partly removed by fine-tuning the linear controller, this process cannot deal with nonlinear effects and is limited in scope by the expertise of t… Show more

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Cited by 77 publications
(65 citation statements)
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“…Adaptive gains are directly synthesized from online signals to cater for time-varying, unknown or nonlinear plant dynamics. This algorithm is particularly suitable for the control of dynamic test facilities [30], as in many cases the structural dynamics are not exactly known and the response characteristics can therefore be unpredictable. Adaptive gains can compensate for these problems in real-time, thus improving test accuracy.…”
Section: Adaptive Substructuring Control Using An Additional Mcsef Almentioning
confidence: 99%
“…Adaptive gains are directly synthesized from online signals to cater for time-varying, unknown or nonlinear plant dynamics. This algorithm is particularly suitable for the control of dynamic test facilities [30], as in many cases the structural dynamics are not exactly known and the response characteristics can therefore be unpredictable. Adaptive gains can compensate for these problems in real-time, thus improving test accuracy.…”
Section: Adaptive Substructuring Control Using An Additional Mcsef Almentioning
confidence: 99%
“…It was found that the general field of control engineering had itself been forced to address similar problems in non-linear robotics and had developed adaptive control, in which the strategy adapts to changing characteristics of the robot, in particular its non-linear behaviour. A significant contribution to this adaptive-control development was by Stoten and Gomez (2001), whose minimal control synthesis (MCS) algorithm, implemented at six European laboratories (Commissariat a l'Energie Atomique (CEA) Saclay and Joint Research Centre (JRC), Ispra were now partners), removed the four deficiencies listed above. This now opened up the following five new research areas, for which the six partners received a series of EC-funded research contracts that finally ended in May 2006:…”
mentioning
confidence: 99%
“…The MCS is widely used in electrohydraulic servo systems including the EHST. 2,18,37,40,[49][50][51][52][53] A block diagram of the MCS structure is given in Figure 8 …”
Section: Online Adaptive Controllermentioning
confidence: 99%