Dynamic substructuring is an experimental technique which decomposes a complete dynamical system into a number of sub-components. Critical components are physically tested at full-size and the remaining components are simultaneously simulated in real-time. High-quality control is required to synchronize the responses of the physical and numerical components and to compensate for additional dynamics introduced by actuator systems within the physical substructures. This paper presents a new state-space approach for the analysis and synthesis of dynamically substructured systems and the associated synchronizing controller design. A new state-space substructured framework is also developed to support the synthesis of state-space dynamic models, which then leads to design and analysis of state-feedback, H∞, and adaptive controllers. This framework is applied to an experimental single-mode, quasi-motorcycle substructuring problem, for illustration of the concepts and for the comparison of controller performance. Implementation results demonstrated the improved performance resulting from the new approach and also the effectiveness of adaptive control in coping with uncertain and changing parameters within the physical substructures.
ChauK.ZhangY.JiangJ.ZhangD.A finite element - analytical method for electromagnetic field analysis of electric machines with free rotation. In Proceedings of the IEEE International Conference on Magnetics, San Diego, California, 8–12 May 2006, pp. 495–495 (IEEE Press, Piscataway, New Jersey).
2.
NakashimaM.MasaokaN.Real-time on-line test for MDOF systems. Earthq. Engng Struct. Dyn., 1999, 28, 393–420.
3.
TagawaY.FukuiK.Inverse dynamics calculation of nonlinear model using low sensitivity compensator. In Proceedings of the Conference on Dynamics and design, Akita, Japan, 1994, pp. 185–188.
4.
WilliamsD. M.Numerical modelling of real-time sub-structure testing. DPhil Thesis, Department of Engineering Science, University of Oxford, UK, 2000.
5.
ChansonH.Turbulent air-water flows in hydraulic structures: dynamic similarity and scale effects. Environ. Fluid Mech., 2009, 9(2), 125–142.
6.
BoesR. M.HagerW. H.Two-phase flow characteristics of stepped spillways. J. Hyd. Engng, 2003, 129(9), 661–670.
7.
TakanashiK.NakashimaM.Japanese activities on online testing. Trans. ASME, J. Engng Mech., 1987, 113(7), 1014–1032.
8.
MahinS. A.ShingP. B.Pseudodynamic method for seismic testing. J. Struct. Engng, 1985, 111, 1482–1503.
9.
BursiO. S.WaggD.Modern testing techniques for structural systems: dynamics and control, 2008 (Springer, Wien, New York).
10.
PintoA. V.PegonP.MagonetteG.TsionisG.Pseudo-dynamic testing of bridges using non-linear substructuring. Earthq. Engng Struct. Dyn., 2004, 33(11), 1125–1146.
11.
PegonP.PintoA. V.Pseudo-dynamic testing with substructuring at the ELSA Laboratory. Earthq. Engng Struct. Dyn., 2000, 29(7), 905–925.
12.
HoriuchiT.InoueM.KonnoT.NamitaY.Real-time hybrid experimental system with actuator delay compensation and its application to a piping system with energy absorber. Earthq. Engng Struct. Dyn., 1999, 28, 1121–1141.
13.
StotenD. P.HydeR. A.Adaptive control of dynamically substructured systems: the single-input single-output case. Proc. IMechE, Part I: J. Systems and Control Engineering, 2006, 220, 63–79.
14.
BlakeboroughA.WilliamsM. S.DarbyA. P.WilliamsD. M.The development of real-time substructure testing. Phil. Trans. R. Soc., 2001, 359, 1869–1891.
15.
AghiliF.A mechatronic testbed for revolute-joint prototypes of a manipulator. IEEE Trans. Robot., 2006, 22(6), 1265–1273.
16.
MartinA.EmamiM. R.An architecture for robotic hardware-in-the-loop simulation. In Proceedings of the IEEE International Conference on Mechatronics and automation, Luoyang, China, 25–28 June 2006, pp. 2162–2167 (IEEE Press, Piscataway, New Jersey).
17.
TriguiR.JeanneretB.MalaquinB.BadinF.PlasseC.Hardware in the loop simulation of a diesel parallel mild-hybrid electric vehicle. In Proceedings of the Conference on Vehicle power and propulsion, Arlington, Texas, 9–12 September 2007, pp. 448–455 (IEEE).
18.
VamsidharS.FernandesB. G.Hardware-in-the-loop simulation based design and experimental evaluation of DTC strategies. In Proceedings of the 35th Annual IEEE Power electronics specialists conference, Mumbai, India, 20–25 June 2004, pp. 3615–3621 (IEEE Press, Piscataway, New Jersey).
19.
BacicM.On hardware-in-the-loop simulation. In Proceedings of the 44th IEEE Conference on Decision and control, and the European control conference 2005, Seville, Spain, 12–15 December 2005, pp. 3194–3198 (IEEE).
20.
KoehlerC.MayerA.HerkersdorfA.Determining the fidelity of hardware-in-the-loop simulation coupling systems. In Proceedings of the IEEE International Workshop on Behavioral modeling and simulation, 25–26 September 2008, pp. 13–18 (IEEE Press, Piscataway, New Jersey).
21.
MacDiarmidM.BacicM.Quantifying the accuracy of hardware-in-the-loop simulations. In Proceedings of the American control conference, New York, 9–13 July 2007, pp. 5147–5152 (IEEE).
22.
LawrenceD. A.Stability and transparency in bilateral teleoperation. In Proceedings of the 31st IEEE Conference on Decision and control, 16–18 December 1992, vol. 3, pp. 2649–2655 (IEEE Press, Piscataway, New Jersey).
23.
RenW.SteurerM.WoodruffS.Accuracy evaluation in power hardware-in-the-loop (PHIL) simulation center for advanced power systems. In Proceedings of the Summer computer simulation conference, San Diego, California, 15–18 July 2007, pp. 489–493 (Society for Computer Simulation International, San Diego, California).
24.
WuB.DengL.WangZ.YangX.Stability analysis of central difference method for dynamic real-time substructure testing. In Proceedings of the American control conference, St. Louis, Missouri, 10–12 June 2009, pp. 5216–5221 (IEEE).
25.
DarbyA. P.BlakeboroughA.WilliamsM. S.Improved control algorithm for real-time substructure testing. Earthq. Engng Struct. Dyn., 2001, 30, 431–448.
Gonzalez-BuelgaA.WaggD. J.NeildS. A.Parametric variation of a coupled pendulum-oscillator system using real-time dynamic substructuring. Struct. Control Health Monitor., 2007, 14, 991–1012.
StotenD. P.TuJ. Y.LiG.Synthesis and control of generalised dynamically substructured systems. Proc. IMechE, Part I: J. Systems and Control Engineering, 2009, 223, 371–392.
30.
TuJ. Y.StotenD. P.LiG.HydeR. A.A state-space approach for the control of dynamically substructured systems. In Proceedings of the Third IEEE Conference on Systems and control, Saint Petersburg, Russia, 8–10 July 2009, pp. 1093–1098 (IEEE Press, Piscataway, New Jersey).
31.
HatanoT.StotenD. P.TuJ. Y.A demonstration system for dynamically substructured systems and their control. UKACC International Conference on Control, 2010.
32.
GawthropP. J.WallaceM. I.WaggD. J.Bond-graph based substructuring of dynamical systems. Earthq. Engng Struct. Dyn., 2005, 34(6), 687–703.
StotenD. P.TuJ. Y.LiG.Adaptive control of generalised dynamically substructured systems. In Proceedings of the 17th IFAC World congress, Seoul, Korea, 6–11 July 2008, pp. 14090–14095 (Elsevier, Oxford, UK).
35.
KautskyJ.NicholsN. K.Robust pole assignment in linear state feedback. Int. J. Control, 1985, 41, 1129–1155.
36.
HydeR. A.GloverK.ShanksG. T.VSTOL first flight on an H∞ control law. Comput. Control Engng J., 1995, 6(1), 11–16.
37.
JungM.GloverK.ChristenU.Comparison of uncertainty parameterisations for H∞ robust control of turbocharged diesel engines. Control Engng Pract., 2005, 13, 15–25.
DoyleJ. C.GloverK.KhargonekarP. P.FrancisB. A.State-space solution to standard H2 and H∞ control problems. IEEE Trans. Autom. Control, 1989, 34(8), 831–847.
40.
SkogestadS.PostlethwaiteI.Multivariable feedback control: analysis and design, second edition, 2005 (John Wiley & Sons, Chichester, UK).
StotenD. P.BenchoubaneH.Robustness of a minimal controller synthesis algorithm. Int. J. Control, 1990, 51(4), 851–861.
43.
WaggD. J.StotenD. P.Substructuring of dynamical systems via the adaptive minimal control synthesis algorithm. Earthq. Engng Struct. Dyn., 2001, 30(6), 865–877.
44.
HodgsonS. P.A unified MCS based approach to the adaptive position and interaction control of robotic manipulators. PhD Thesis, Department of Mechanical Engineering, University of Bristol, 1993.
45.
HodgsonS. P.StotenD. P.Passivity-based analysis of the minimal control synthesis algorithm. Int. J. Control, 1996, 63(1), 67–84.
46.
LandauI. D.Adaptive control - the model reference approach, 1979 (Marcel Dekker, New York).
47.
PopovV. M.Hyperstability of automatic control systems, 1973 (Springer-Verlag, Berlin, Germany).
