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Keywords: neural networks
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Journal Articles
Article Type: Research-Article
J. Dyn. Sys., Meas., Control. October 2021, 143(10): 101002.
Paper No: DS-20-1472
Published Online: May 13, 2021
... operational regimes in: (i) an experimental Rijke-tube apparatus and (ii) an experimental combustion system apparatus. Results of the proposed TL have been validated by comparison with those of two shallow neural networks (NNs)-based TL and another NN having an additional long short-term memory (LSTM) layer...
Journal Articles
Article Type: Research-Article
J. Dyn. Sys., Meas., Control. April 2015, 137(4): 041018.
Paper No: DS-13-1136
Published Online: April 1, 2015
... Chen. 26 03 2013 06 11 2014 09 01 2015 In this paper, the problems of determining the robust exponential stability and estimating the exponential convergence rate for recurrent neural networks (RNNs) with parametric uncertainties and time-varying delay are studied...
Journal Articles
Article Type: Research-Article
J. Dyn. Sys., Meas., Control. March 2013, 135(2): 021009.
Paper No: DS-11-1319
Published Online: November 7, 2012
.... Editor: Warren E. Dixon. 15 10 2011 18 08 2012 This paper presents an adaptive output-feedback control method based on neural networks for flexible link manipulator which is a nonlinear nonminimum phase system. The proposed controller comprises a linear, a neuro-adaptive...
Journal Articles
Article Type: Technical Briefs
J. Dyn. Sys., Meas., Control. March 2012, 134(2): 024502.
Published Online: December 30, 2011
... fluid power control systems neural networks Pneumatic systems are very well suited to perform high speed, medium force tasks that only require two stop positions. They present a high power to weight ratio, require low maintenance and use a clean form of energy. However, when the task requires...
Journal Articles
Article Type: Research Papers
J. Dyn. Sys., Meas., Control. November 2011, 133(6): 061014.
Published Online: November 11, 2011
...A. Karami-Mollaee; N. Pariz; H. M. Shanechi In this paper, position control of servomotors is addressed. A radial basis function neural network is employed to identify the unknown nonlinear function of the plant model, and then a robust adaptive law is developed to train the parameters...
Journal Articles
Article Type: Research Papers
J. Dyn. Sys., Meas., Control. November 2011, 133(6): 061008.
Published Online: November 11, 2011
...Jaho Seo; Amir Khajepour; Jan P. Huissoon The objective of this research is to identify a dynamic model that describes the temperature distribution in a die with uncertain dynamics using a neural network (NN) approach. By using data sets obtained from a finite element analysis (FEA) of the thermal...
Journal Articles
Article Type: Research Papers
J. Dyn. Sys., Meas., Control. July 2009, 131(4): 041003.
Published Online: April 29, 2009
... for which the passivity property does not hold, the manipulator is also underactuated, that is, the control input does not drive the link directly, but through the flexible dynamics. Our work offers another possible solution to this open problem. We use three-layer neural networks to represent the system...
Journal Articles
Article Type: Technical Briefs
J. Dyn. Sys., Meas., Control. July 2007, 129(4): 527–533.
Published Online: February 12, 2007
...G. Colin; Y. Chamaillard; G. Bloch; A. Charlet This paper describes a real-time control method for non-linear systems based on model predictive control. The model used for the prediction is a neural network because of its ability to represent non-linear systems, its ability to be differentiated...