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Some Applications of Neural Network Technology to Fluid Power Systems
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Abstract
In many areas, neural network technology has made a successful transition from theory to practical application, primarily due to the advances that have been made in computer technology and digital signal processing. Research at the University of Saskatchewan over the past few years has focused on applying neural network technology to fluid power systems. This paper will examine four projects that have been initiated by the authors and their graduate students which use neural networks for purposes of open loop pattern following, multiple input - multiple output control, indirect measurement of actuator displacement, and hydraulic component identification. A brief introduction to static and dynamic neural networks is given. Descriptions of the individual project objectives, the experimental implementation of neural networks to achieve these objectives, and some typical experimental results are considered. The results of these studies indicate that the use of neural networks for hydraulic systems shows significant potential for a variety of applications in the fluid power industry and for its customers in the off-highway vehicle business.
A unique contribution of the paper is a discussion of the philosophy of this research approach by an (with respect to the University of Saskatchewan) “at arms length” industrial supplier of custom designed electronic sensors and electrohydraulic control systems for OEM (Phoenix International). This company has been attracted to the neural network approach because these networks do not demand system linearity, perform well in noisy data environments, and can be quickly implemented in rather elegant real-time control solutions through the use of microcontrollers and digital signal processors. A discussion on the potential and conversion of this, and other similar type of research, to commercially viable products is forwarded.
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Burton, R., Ukrainetz, P., Schoenau, G., Sargent, C. et al., "Some Applications of Neural Network Technology to Fluid Power Systems," SAE Technical Paper 972768, 1997, https://doi.org/10.4271/972768.Also In
References
- Hornik, K. 1991 Approximation of Capabilities of Multilayer Feedforward Networks Neural Networks 4 251 257
- Narendra, K. S. Parthasarathy, K. 1990 Identification and Control of Dynamical Systems Using Neural Networks IEEE Trans. Neural Networks 1 4 27
- Chen, S. Cowan, C. F. N. Billings, S. A. Grant, P. M. 1990 Parallel Recursive Error Algorithm for Training Layered Neural Networks Int. J. Control 51 6 1215 1228
- Xu, X. P. Sargent, C. M. Burton, R. T. 1996 Experimental Identification of a Flow Orifice Using a neural Network and the Conjugate Gradient Method Journal of Dynamic Systems Measurements and Control 118 June 272 277
- Chen, S. Billings, S. A. 1992 Neural Networks for Dynamical System Modeling and Identification Int. J. Control 55 1 193 224
- Burton R.T Sargent, C.M. Schoenau, G.J. Anderson, D. 1993 The use of Multiple Independent Gains for a repetitive Low Frequency Duty Cycle in a Hydraulic System Proceedings of the second JHPS International Symposium on Fluid Power Tokyo, Japan Sept
- Zhang, H. Ukrainetz, P.R. Nikiforuk, P.N. Burton, R.T. 1996 Implementation of Neural Network Approach in MIMO Electrohydraulic Servosystem Control Proceedings of the UKACC International Conference on Control, '96 University of Exeter UK Sept. 1468 1473
- Chen, Y. Schoenau, G.J. Burton, R.T. 1997 Indirect Measurement of Actuator Position using a Neural Network Based Predictor Proceedings of the Fifth Scandinavian International Conference on Fluid Power, SICFP'97 Linkoping, Sweden May
- Chan, R.K. Burton, R.T. Schoenau, G.J. Ukrainetz, P.R. 1982 Indirect Feedback Using a Microprocessor-Based Controller to Control the Drift Associated with the Positioning of a Hydraulic Actuator Proceedings of the 28th International Instrumentation Symposium 28 Las Vegas 631 643
- Xu, X.P. 1997 Experimental Modeling of a Hydraulic Load Sensing Pump using Neural Networks Ph.D. Thesis University of Saskatchewan Saskatoon, Saskatchewan, Canada
- Schneider, D. Zieringer, C. 1991 Make-or-Buy-Strategien fuer F&E: transaktionskostenorientierte Ueberlegungen Wiesbaden, Germany
- Comerford, R. 1994 Mecha…what ? Reprint from IEEE Spectrum 31 8 August
- Neuffer, K. Engelsdorf, K. Brehm, W. 1996 Electronic Transmission Control - From Stand Alone Components to Mechatronic Systems SAE-Paper 960430
- Keenan, T. 1997 Safety Rules at SAE WARD'S Auto World 33 3 March 102