NEW RESULTS IN CONTROL SYNTHESIS FOR ELECTROHYDRAULIC SERVOS
Keywords:
electrohydraulic servo, robust linear control, control saturation, antiwindup compensation, fuzzy supervised neurocontrol, backstepping control, numerical simulationAbstract
This survey presents some recent results of the authors in the field of the control synthesis for electrohydraulic servos. Three are the methodologies of control theory herein considered. Firstly, an integrated methodology of robust control synthesis with antiwindup feedback compensation for linear model of electrohydraulic servo is developed. Secondly, in a strongly nonlinear framework, an integrated fuzzy supervised neurocontrol is proposed. This represents a control strategy which is in fact independent of mathematical model of the systems, thus achieving certain robustness and reducing complexity. At last, the backstepping is used for obtaining of control laws for asymptotic tracking of position or force references in the case of a certain model of an electrohydraulic servo. Conclusive numerical simulations are provided to verify the behaviour of the controlled systems by the proposed control laws.
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References
Åström, K. J. and Wittenmark, B. 1974. Computer
controlled systems. Theory and design. Prentice-
Hall, Englewood Cliffs, NJ.
Blackburn, J. E., Shearer, J. L. and Reethof, G.
Fluid power control. Tech. Press of Massachusetts
Institute of Technology and Wiley, New
York.
Bobrow, J. E. and Lum, K. 1996. Adaptive, high
band-width control of a hydraulic actuator, Transactions
of the ASME, Journal of Dynamic Systems,
Measurements and Control, 118, December, pp.
–720.
Davison, E. J. and Goldenberg, A. 1975. Robust control
of a general servomechanism problem: the servocompensator.
Automatica, 11, pp. 461-471.
Davison, E. J. 1976. The robust control of a servomechanism
problem for linear time-invariant multivariable
system. IEEE Transactions on Automatic
Control, 21, pp. 25-34.
Ermakov, S. A., Klaptsova, T. S. and Smirnov,
G. G. 1986. Synthesis of electrohydraulic tracking
systems with observers (in Russian), Pnevmatika i
Gidravlika. 12, Moskow, Mashinostroenie, pp. 45–
Frankena , J. F. and Sivan , R. 1979. A nonlinear optimal
control law for linear systems. International
Journal of Control, 30, pp. 159-178.Ghazi Zadeh, A., Fahim, A. M. and El-Gindy, M.
Neural network and fuzzy logic applications
to vehicle systems: literature survey. International
Journal of Vehicle Design, 18, pp. 132-193.
Hahn, H., Piepenbrink, A. and Leimbach, K.-D.
Input-output linearization control of an electro
servohydraulic actuator. Proceeding of 3rd IEEE
Conference on Control Applications, Glasgow, pp.
-1000.
Halanay, A., Safta, C. A., Ursu, I. and Ursu, F. 2004.
Stability of equilibria in a four–dimensional nonlinear
model of a hydraulic servomechanism. Journal
of Engineering Mathematics, 49, pp. 391–406.
Han, J. 1989. Control theory: it is a theory of model or
control? Systems Science and Mathematical Sciences,
, pp. 328–335.
Hanus, R., Kinnaert, M. and Henrotte, J.-L. 1987.
Conditioning technique: a general antiwindup and
bumpless transfer method. Automatica, 23, pp. 729-
Ingenbleek, R. and Schwarz, H. 1993. A nonlinear
discrete-time observer based control scheme and its
application to hydraulic drives. Proceedings of 2nd
European Control Conference, Groningen, the
Netherlands, July, pp. 215–219.
Jelali, M. and Schwarz, H. 1995. Continuos-time identification
of hydraulic servo-drive nonlinear models.
Proceedings of 3rd European Control Conference,
, Rome, Italy, pp. 1545-1549.
Jelali, M. and Kroll, A. 2003. Hydraulic servosystems.
Springer Verlag, Berlin.
Kliffken, M. G. 1997 Robust sampled-data control of
hydraulic flight control actuators, 5th Scandinavian
International Conference on Fluid Power,
SICFP’97, Linköping, Sweden, May 28-30.
Krikelis, N. J. and Barkas, S. K. 1984, Design of
tracking systems subject to actuator saturation. International
Journal of Control, 39, 4, pp. 667-682.
Krstić, M., Kanellakopoulos, I. and Kokotović, P.
Nonlinear and adaptive control design, Wiley
and Sons, New York.
Mihajlov, M., Nikolić, V. and Antić, D. 2002. Position
control of an electro-hydraulic servo system using
sliding mode control enhanced by fuzzy PI controller.
Facta Universitas. Series: Mechanical Engineering,
, pp. 1217-1230.
Panasian, H. V. 1986. Reduced order observers applied
to state and parameter estimation of hydromechanical
servoactuators. Journal of Guidance,
Control and Dynamics, 9, pp. 249–251.
Park, J. K. and Choi, C.-H. 1993. A compensation
method for improving the performance of multi
variable control systems with saturating actuators.
Control-Theory and Advanced Technology, 9, pp.
-322.
Plummer, A. R. 1997. Feedback linearization for acceleration
control of electrohydraulic actuators.
Proceedings of the Institution of Mechanical Engineers,
, Part 1, pp. 395–406.
Richard, E. and Outbib, R. 1995. Feedback stabilization
of an electrohydraulic system. Proceedings of
rd European Control Conference, Rome, Italy,
September, pp. 330–334.
Sepulchre, R., Janković, M. and Kokotović, P. 1997.
Constructive nonlinear control, Springer-Verlag,
London.
Tyan, F. and Bernstein, S. 1994. Antiwindup compensator
synthesis for systems with saturating actuators.
Proc. of 33rd Conference on Decision and Control,
Lake Buena Vista, FL, pp. 150-155.
Tzes, A. and Peng, P.-Y. 1997. Fuzzy neural network
control for DC-motor micromaneuvering. Transactions
of the ASME, Journal of Dynamic Systems,
Measurement and Control, 119, pp. 312-315.
Ursu, I. 1984. Theoretical and experimental data concerning
qualification testing and flight clearance for
aircraft servomechanism SMHR. National Institute
for Scientific and Technical Creation – INCREST
Report, N-5303, Bucharest.
Ursu, I., Popescu, F., Vladimirescu, M. and Costin,
R. 1994. On some linearization methods of the generalized
flow rate characteristic of the hydraulic
servomechanism. Revue Roumaine des Sciences
Technique, Série de Mécanique Appliquée, 39, pp.
-217.
Ursu, I., Vladimirescu, M. and Ursu, F. 1996. About
aeroservoelasticity criteria for electrohydraulic
servo-mechanisms synthesis. Proceedings of ICAS’
, Sorrento, Italy, pp. 2335-2344.
Ursu, I., Tecuceanu, G., Ursu, F., Sireteanu, T. and
Vladimirescu, M. 1998. Aircraft Engineering and
Aerospace Technology, 70, 4, pp. 259–264.
Ursu, I., Ursu F., Sireteanu, T. and Stammers, C. W.
Artificial intelligence based synthesis of
semiactive suspension systems. Shock and Vibration
Digest, 32, pp. 3-10.
Ursu, I., Ursu, F. and Iorga, L. 2001. Neuro-fuzzy
synthesis of flight controls electrohydraulic servo.
Aircraft Engineering and Aerospace Technology,
, pp. 465-471.
Ursu, F. and Ursu, I. 2001. Robust synthesis with antiwindup
compensation for electrohydraulic servoactuating
primary flight controls. Preprints of the
th IFAC Symposium on Automatic Control in
Aerospace, Bologna-Forli, September, 2−7, pp.
-202.Ursu, I. and Ursu, F. 2002. Active and semiactive control.
Romanian Academy Publishing House, Bucharest.
Ursu, I. and Popescu, F. 2003. Nonlinear control synthesis
for position and force electrohydraulic servos.
Proceedings of the Romanian Academy, Series A, 4,
, pp. 115–120.
Vemuri, V. 1993. Artificial neural networks in control
applications. In Advances in Computers, edited by
M. C. Yovits, Academic Press, 36, pp. 203-332.
Vossoughi, G. and Donath, M. 1995. Dynamic feedback
linearization for electrohydraulically actuated
control systems. Transactions of the ASME, Journal
of Dynamic Systems, Measurements and Control,
, December, pp. 468–477.
Zhou, K. Doyle, J. K. and Glover, K. 1996. Robust
and optimal control, Prentice Hall, New Jersey.
Yen, J., Langari, R. and Zadeh, L. A. Eds. 1995. Industrial
applications of fuzzy control and intelligent
systems. New York, IEEE Press.
Wang, L. 1994. Adaptive fuzzy systems and control −
design and stability analysis, Englewood Cliffs,
New Jersey, Prentice Hall.
Wang, P. K. C. 1963. Analytical design of electrohydraulic
servomechanism with near time-optimal response.
IEEE Transactions on Automatic Control
AC-8, pp. 15-27.
Wang, L-X. and Kong, H. 1994. Combining mathematical
model and heuristics into controllers: an
adaptive fuzzy control approach. Proceedings of the
rd IEEE Conference on Decision and Control,
Buena Vista, Florida, December 14-16, 4, pp. 4122-
