This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Utilization of Artificial Neural Networks in the Control, Identification and Condition Monitoring of Hydraulic Systems - An Overview
Technical Paper
2000-01-2591
ISSN: 0148-7191, e-ISSN: 2688-3627
Annotation ability available
Sector:
Language:
English
Abstract
There has been considerable interest and activity in the area of application of the artificial neural network (ANN) to hydraulic systems. The pattern recognition capabilities of the ANN has led to an early investigation in areas where the neural networks could be trained using signals that were at least statistically similar to those signals which the trained ANN would be exposed during operation. The dynamic and encompassing nature of hydraulic system signals poses more of a challenge to ANN training and implementation than one of only pattern recognition. However, in the past decade, there has been considerable activity and progress in the application of ANN techniques for hydraulic systems control, identification and condition monitoring.
This paper provides an overview of work in this area. The ANN has proven to be a valuable addition to the current existing techniques. The learned behavior capability is a definite asset in the control of the nonlinear, complex systems encountered in the fluid power area. Training is a fundamental requirement for the ANN and this is very often accomplished using a simulation model of the system. ANN based controllers have demonstrated superior performance when compared to conventional PID controllers although these controllers are often an integral part of the training regime or in system operation with the ANN playing a supervisory role. In adaptive control, the ANN can be used to replace the plant model where the ability to emulate or mimic a nonlinear system plays a crucial role. As well, the control algorithm can utilize ANN capability. Fuzzy based controllers also have an approximate reasoning or intelligence capability based on a qualitative description of their dependencies. ANN techniques have been successfully employed in a form of parameter adjustment to enhance the performance of these controllers. Condition monitoring is perhaps a more natural application of the ANN where the pattern recognition capability can be fully utilized in a “stand alone” fashion. Simulation models have been successfully used to train the ANN for fault detection in physical systems.
Recommended Content
Authors
Topic
Citation
Schoenau, G., Stecki, J., and Burton, R., "Utilization of Artificial Neural Networks in the Control, Identification and Condition Monitoring of Hydraulic Systems - An Overview," SAE Technical Paper 2000-01-2591, 2000, https://doi.org/10.4271/2000-01-2591.Also In
References
- McCulloch W.S. Pitts W. 1943 A Logical Calculus of the Ideas Immanent in Nervous Activity Bulletin of Mathematical Physics 5 115 123
- Widrow B. Lear M.A. 1990 30 Years of Adaptive Neural Networks: Perception, Madaline and Back Propagation Proceedings of IEEE 78 9
- Narendra K. Mackhopadhyay S. 1982 Intelligent Control Using Neural Networks Proceedings of the IEEE Journal of Control Systems 32 2
- Hart A.M. Burton R.T. Sargent C.M. Schoenau G.J. 1991 Preliminary Attempts to Control a Hydraulic Circuit Using an Artificial Neural Network Proceedings of the Fourth International Workshop on Systems, Modelling and Control University of Bath Sept “Systems, Modelling and Control” Research Studies Press Ltd., John Wiley and Son's Inc. 1991
- Burton R.T. Sargent C.M. Schoenau G.J. 1992 Using an Artificial Neural Network to Control a Hydraulic Circuit Proceedings of the 1992 International Fluid Power Exposition and Conference (IFPE '92) Chicago March
- Liu C. Dransfield P. Stecki J.S. 1992 Neural Nets - Their Potential for Intelligent Control of Fluid Power Drives Proceedings of 10 th Aachen Fluidtechniques Colloqium Aachen, Germany 407 417
- Daley S. Wang H. 1993 On the Application of Neural Networks to the Monitoring of a Simlated Hydraulic Rotary Drive System Sixth Bath International Fluid Power Workshop - Modelling and Simulation Bath, UK.
- Newton .A. 1994 Application of a Neural Network Controller to Control a Rotary Drive System with High Power Efficiency Seventh Bath International Fluid Power Workshop - Innovations in Fluid Power Bath, UK
- Daley S. Newton D.A. 1994 Intelligent Control of an Electrohydraulic Rotary Drive System Proceedings of International IEE Conference on Control Coventry, UK 699 704
- Newton D.A. 1994 Design and Implementation of a Neural Network Controlled Electrohydraulic Drive Journal of Systems and Control Engineering, IMechE 208 1 31 42
- Masters T. 1993 Practical Neural Network Recipies in C++ Academic Press
- Anderson D. Schoenau G.J. Burton R.T. Sargent C.M. 1996 A Comparison of PID and Neural Network Control of a Hydraulic Actuator Proceedings of the Sixth Conference on Control Singapore Oct.
- Qian W. Schoenau G. J. Burton R.T. Ukrainetz P.R. 1998 Measured Performance of PID and Neural Net Control of a Hydraulic Actuator Proceedings of the 1998 IMACS International Conference on Circuits, Systems and Computers Greece Oct. 607 611
- Qian W. Burton R.T. Schoenau G.J. Ukrainetz P.R. 1998 A Comparison of a PID Controller to a Neural Network Controller in a Hydraulic System with Nonlinear Friction Proceedings of the 1998 ASME International Mechanical Engineering Congress and Exposition Anaheim CA Nov. 5 91 98
- Qian W. Burton R. Schoenau G. 2000 Model Based Evaluation of Neural Net Control of an Inertial System with Nonlinear Friction Proceedings of the IFPE 2000 Exposition for Power Transmission April
- Hatch D.J. Sarnai M. Stecki J.S. 1995 Neural Network Modeling and Control of Fluid power Systems Proceedings of the Fourth Scandanavian International Conference on Fluid Power Tampere, Finland 1 94 104
- Noritusugu T. Fukuzono K. 1996 Force Control of Pneumatic Servo System Using a Neural Network, Third
- Sun W. He H. Zhou E. Zhou S. 1997 PWM Oil Temperature Control In Hydraulic System Based on MNN Neural Network Proceedings of the ASME International Mechanical Engineering Congress and Exposition Dallas, Texas 4 67 70
- Nishumi T. Konami S. Watton J. 1998 Neural Network Control of an Electro-Hydraulic Actuator Using On-Line Training Second Tampere International Conference on Machine Automation Tampere, Finland
- Hountras A. Antoniadis I. Kanarachos A. 1999 Implementation of N-Step Ahead Neurocontrol on a 3-Axes Heavy Duty Hydraulic Manipulator Mechatronics 9 3 235 270
- Hornik K. Stinchcombe M. White H.W. 1989 Multilayer Feed Forward Networks are Universal Approximators Neural Networks 2 5 359 366
- Xu X.P. Sargent C.M. Burton R.T. 1994 Experimental Identification of Flow Orifice Using Neural Network and the Conjugate Gradient Method Transactions of the ASME, Journal of Dynamic Systems, Measurement and Control 118 2 June 272 277
- Xu X.P. Burton R.T. Sargent C.M. Ukrainetz P.R. 1997 Neural Network Simulation of a Load Sensing Pump Proceedings of the Fifth Scandinavian International Conference on Fluid Power Linkoping, Sweden May
- Watton J. Xue Y. 1995 An Alternative Approach to Fluid Power Circuit Design Using ARMAN, ADAN and ANN Component Modeling 8 th Bath International Workshop Bath, UK
- Watton J. Kwon K.S. 1996 Neural Network Modeling of Fluid Power Control Systems Using Internal State Variables Mechatronics 6 7 817 827
- Huang A. Rong Y. Zhang Z. Hu J. 1997 Identification and Adaptive Control for an Electro-Hydraulic Servo System Using Neural Networks Proceedings of the 1997 International Conference on Intelligent Processing Systems Beijing, China 688 692
- Narenda K.S. Annaswamy A.M. 1989 Stable Adaptive Systems Prentice Hall Englewood Cliffs, N.J.
- Zhang H. Ukrainetz P.R. Nikiforuk P.N. Burton R.T. 1997 Neural Adaptive Control of a MIMO Electrohydraulic Servosystem Proceedings of the 1997 ASME International Mechanical Engineering Congress and Exposition 4 63 Dallas Nov. 16-21 7 12
- Nishiumi T. Watton J. 1997 Model Reference Adaptive Control of an Electrohydraulic Motor Drive Using an Artificial Neural Network Compensator Journal of Systems and Control Engineering, IMechE 211 2 111 122
- Yang H. Yang J. Zhang J. Sha D. 1997 Real Time Adaptive Control for a VVVF Hydraulic Elevator Using Neural Nets Proceedings of the IEEE International Conference on Intelligent Processing Systems Beijing, China 1 2 1 5
- He Y.B. Sun J.Y. Xue M.G. Sheng W. Liu Y.Q. Yan G.R. 1997 Neural Network Adaptive Predictive Controller for Electro-Hydraulic Servo Structural Testing System Second International Symposium on Test and Measurement Beijing, China 294 297
- Berenji H.R. Kheedkar P. 1992 Learning and Tuning Fuzzy Logic Controllers through Reinforcements Transactions of IEEE on Neural Networks 3 5
- Shih M.C. Lee K.C. 1995 Hydraulic Servo Cylinder Position Control Using a Hybrid Neuro-Fuzzy Controller Proceedings of the Fourth Scandanavian International Conference on Fluid Power Tampere, Finland 1 105 118
- Gao J. Jianchen W. 1997 Fuzzy Neural Network Controller In the Electrohydraulic Position Control System Proceedings of the IEEE International Conference on Intelligent Processing Systems Beijing, China 1 2 58 63
- Park Y.J. Hyung S. 1996 Neuro-Fuzzy Control of an Electro-Hydraulic Fin Position Servo System Proceedings of the 1996 ASME International Mechanical Engineering Congress and Exposition Atlanta, GA 101 106
- Shih M.C. Tsai C.P. 1995 Servohydraulic Cylinder Position Control Using a Neuro-Fuzzy Controller Mechatronics 5 5 497 512
- Lu X.F. Burton R.T. Schoenau G.J. 1995 A Neural Network Based Incipient Fault Detection System for an Axial Piston Hydraulic Pump Proceedings of the 1995 IASTED International Conference, SIP-95 Las Vegas November 147 150
- Lu X.F. Burton R.T. Schoenau G.J. 1994 Feasibility Study on the Use of a Neural Network to Detect and Locate Excess Piston Wear in an Axial Piston Pump Innovations in Fluid Power , Seventh Bath International Fluid Power Workshop RSP Research Studies Press Ltd. Publishers Bath, England Sept.
- Ramden T. Krus P. Palmberg J.O. 1995 Fault Diagnosis of Complex Fluid Power Systems Using Neural Networks Proceedings of the Fourth Scandanavian International Conference on Fluid Power Tampere, Finland 1 706 718
- Crowther W.J. Edge K.A. Burrows C.R. Atkinson R.M. Woollons D.J. 1998 Fault Diagnosis of a Hydraulic Actuator Circuit Using Neural Networks - An Output Vector Classification Approach Proc.ImechE, Journal of Systems and Control Engineering 212 1 57 68
- Atkinson R.M. Woollons D.J. Tasson S. Crowther W.J. Burrows C.R. Edge K.A. 1996 Fault Diagnosis in Electro-hydraulic Systems Using Neural Networks BHR Group Conference on Profitable Condition Monitoring 275 285
- Atkinson R.M. Woolons D.J. Crowther W.J. Burrows C.R. Edge K.A. 1996 A Neural Network Approach to Fault Diagnosis in Electro-Hydraulic Systems Proceedings of COMADEM'96 Sheffield, UK 125 133
- Watton J. Stewart J.C. 1996 Co-operating Expert and Artificial Neural Networks for Fault Diagnosis of Electro-hydraulic Cylinder Position Control Systems Third JHPS International Symposium Yokohama, Japan 217 222
- Zhavaehi M. 1997 On-line Condition Monitoring and Fault Detection in Hydraulic System Components Using Parameter Estimation and Pattern Classification University of British Columbia Vancouver, Canada