Shaking table testing is a common experimental method in earthquake engineering for performance assessment of structures subjected to dynamic excitations. As most shaking tables are driven by servo hydraulic actuators to meet the potentially significant force stroke demand, the review is restricted to hydraulic shaking tables. The purpose of the control systems of hydraulic shaking tables is to reproduce reference signals with low distortion. Accurate control of actuators is vital to the effectiveness of such apparatus. However, the system dynamics of a shaking table and the specimens to be tested on the shaking table are usually very complex and nonlinear. Achieving the control goal can prove to be challenging. A variety of closed- and open-loop control algorithms has been developed to solve different control problems. With the focus placed on the control schemes for hydraulic shaking tables, the paper reviews algorithms that are currently used in the testing industry, as well as those which are the subject of academic and industrial research. It is by no means a complete survey but provides key reference for further development.
CuyperJDVerhaegenM (2002) State space modelling and stable dynamic inversion for trajectory tracking on an industrial seat test rig. Journal of Vibration and Control8(7): 1033–1050.
2.
CuyperJDVeraegenMSweversJ (2003) Offline feed-forward and H∞ feedback control on a vibration rig. Control Engineering Practice11(3): 129–140.
3.
ElbayomyKMJiaoZXZhangHQ (2008) PID controller optimization by GA and its performances on the electro-hydraulic servo control system. Chinese Journal of Aeronautics21(4): 378–384.
4.
GhazaliRSamYMRahmatMFHashimWIMZulfatmanZ (2010) Sliding mode control with PID sliding surface of an electro-hydraulic servo system for position tracking control. Australian Journal of Basic and Applied Sciences4(10): 4749–4759.
5.
Gizatullin AO and Edge KA (2006) Adaptive control for a multi-axis hydraulic test rig. In: Proceedings of the Institution of Mechanical Engineers, Part I, Journal of Systems and Control Engineering vol. 221(2), pp. 183–198.
6.
Guan GF (2007) Control strategy of hydraulically driven 6-DOF vibration test system, PhD dissertation, Harbin Institute of Technology, China.
7.
Guo BT, Liu HY, Luo Z and Wang F (2009) Study of PID neural network for hydraulic system. In: Proceedings of IEEE International Conference on Automation and Logistics, Shenyang, China, Aug. 5–7, pp. 228–232.
8.
Horiuchi T, Dozono Y and Konno T (2001) Improvement of accuracy of seismic acceleration waveforms of shaking tables by compensating for the reaction force in real time. In: Proceedings of 16th International Conference on Structural Mechanics in Reactor Technology, Washington, DC, Aug. 12–17, pp.1085–1090.
9.
IshakNTajjudinMIsmailHRahimanMHFSamYMAdnanR (2012) PID studies on position tracking control of an electro-hydraulic actuator. International Journal of Control Science and Engineering2(5): 120–126.
10.
JiXDKajiwaraKNagaeTEnokidaRNakashimaM (2009) A substructure shaking table test for reproduction of earthquake responses of high-rise buildings. Earthquake Engineering and Structural Dynamics38(12): 1381–1399.
11.
Keiichi O, Nobuyuki O, Tsuneo K and Heki S (2004) Construction of E-Defense (3-D full-scale earthquake testing facility). In: Proceedings of 13th World Conference on Earthquake Engineering, Vancouver, BC, Canada, Aug. 1–6, pp. 189–203.
12.
KuehnJEppDPattenWN (1999) High-fidelity control of a seismic shake table. Earthquake Engineering & Structural Dynamics28(11): 1235–1254.
13.
LandauID (1979) Adaptive Control: the Model Reference Approach, New York: Dekker.
14.
LeeSKParkECMinKWParkJH (2007) Real-time substructuring technique for the shaking table test of upper substructures. Engineering Structures29(9): 2219–2232.
15.
MaddaloniGRyuKPReinhormAM (2011) Simulation of floor response spectra in shaking table experiments. Earthquake Engineering and Structural Dynamics40(6): 591–604.
16.
NakataN (2010) Acceleration trajectory tracking control for earthquake simulators. Engineering Structures32(8): 2229–2236.
17.
NeildSAStotenDPDruryDWaggDJ (2005) Control issues relating to real-time substructuring experiments using a shaking table. Earthquake Engineering and Structural Dynamics34(9): 1171–1192.
18.
Newell DP, Dai HL, Sain MK, Quast P and Spencer BF (1995) Nonlinear modeling and control of a hydraulic seismic simulator. In: Proceedings of the American Control Conference, Seattle, WA, June 21–23, pp. 801–805.
19.
Nowak RF, Kusner DA, Larson RL and Thoen BK (2000) Utilizing modern digital signal processing for improvement of large scale shaking table performance. In: Proceedings of the 12th World Conference on Earthquake Engineering, Auckland, New Zealand, Jan. 30– Feb. 4, pp. 2035–2042.
20.
PhillipsBMWierschemNESpencerBF (2014) Model-based multi-metric control of uniaxial shake tables. Earthquake Engineering & Structural Dynamics43(5): 681–699.
21.
Plummer AR (2007) Control techniques for structural testing: A review. In Proceedings of the Institution of Mechanical Engineers, Part I, Journal of Systems and Control Engineering vol. 221(2), pp. 139–169.
22.
Seki K, Iwasaki M, Kawafuku M, Hirai H and Yasuda K (2008) Improvement of control performance in shaking-tables by feedback compensation for reaction force. In: Proceedings of the 34th Annual Conference of the IEEE Industrial Electronics Society, Orlando, FL, Nov. 10–13, pp. 2551–2556.
23.
ShenGZhuZCZhangLTangYYangCFZhaoJS (2013) Adaptive feed-forward compensation for hybrid control with acceleration time waveform replication on electro-hydraulic shaking table. Control Engineering Practice21(8): 1128–1142.
24.
StehmanMNakataN (2013) Direct acceleration feedback control of shake tables with force stabilization. Journal of Earthquake Engineering17(5): 736–749.
25.
StotenDPGómezE (2001) Adaptive control of shaking tables using the minimal control synthesis algorithm. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences359(1786): 1697–1723.
26.
Stoten DP and Shimizu N (2007) The feedforward minimal control synthesis algorithm and its application to the control of shaking-tables. In: Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering vol. 221(3), pp. 423–444.
27.
Stoten DP, Neild SA, Wagg DJ and Drury D (2002) Dynamic substructuring via the adaptive MCS algorithm. In: Proceedings of Third World Conference on Structural Control, Como, Italy, April 7–11, pp. 819–825.
28.
Stoten DP, Tu JY and Li G (2009) Synthesis and control of generalized dynamically substructured systems. In: Proceedings of the Institution of Mechanical Engineers. Part I: Journal of Systems and Control Engineering vol. 223(3), pp. 71–392.
29.
Tagawa Y and Kajiwara K (2007) Controller development for the E-Defense shaking table. In: Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering vol. 221(2): pp. 171–181.
30.
WuZSYaoJJYueDH (2004) A self-tuning fuzzy PID controller and its application. Journal of Harbin Institute of Technology36(11): 1578–1580.
31.
Yang TY and Schellenberg A (2008) Using nonlinear control algorithms to improve the quality of shaking table tests. In: Proceedings of the 14th World Conference on Earthquake Engineering, Beijing, China, Oct. 12–17, pp. 1204–1211.
32.
Yang ZD (2009) Research on control technologies of simulation of vibration environment using hydraulic vibration table. PhD dissertation, Harbin Institute of Technology, China.
33.
Yao JJ (2007) Research on acceleration harmonic cancellation of electro-hydraulic servo shaking table, PhD dissertation, Harbin Institute of Technology, China.
34.
YaoJJWangCJ (2012) Model reference adaptive control for a hydraulic underwater manipulator. Journal of Vibration and Control18(6): 893–902.
35.
YaoJJDiDTJiangGLGaoS (2012) Acceleration amplitude-phase regulation for electro-hydraulic servo shaking table based on LMS adaptive filtering algorithm. International Journal of Control85(10): 1581–1592.
36.
YaoJJDiDTJiangGLGaoSYanH (2013) Identification of acceleration harmonic for an electro-hydraulic servo shaking table based on Kalman filter. Transactions of the Institute of Measurement and Control35(8): 986–996.
37.
YaoJJFuWHuSHHanJW (2011a) Amplitude phase control for electro-hydraulic servo system based on normalized least-mean-square adaptive filtering algorithm. Journal of Central South University of Technology18(3): 755–759.
38.
YaoJJHuSHFuWHanJW (2011b) Impact of excitation signal upon the acceleration harmonic distortion of an electro-hydraulic shaking table. Journal of Vibration and Control17(7): 1106–1111.
39.
YaoJJHuSHFuWHanJW (2011c) Harmonic cancellation for electro-hydraulic servo shaking table based on LMS adaptive algorithm. Journal of Vibration and Control17(12): 1862–1868.
40.
YaoJJWangLQJiangHZWuZSHanJW (2008a) Adaptive feed-forward compensator for harmonic cancellation in electro-hydraulic servo system. Chinese Journal of Mechanical Engineering21(1): 77–81.
41.
Yao JJ, Wang LQ, Wang CD, Zhang ZL and Jia P (2008b) ANN-based PID controller for an electro-hydraulic servo system. In: Proceedings of the IEEE International Conference on Automation and Logistics, Qingdao, China, Sept. 1–3, pp. 18–22.
