Universal process control using artificial neural networks

Details Universal process control using artificial neural networks Universal process control using artificial neural networks

1990-10-11

1992-10-27

Fleming, Michael R.

Boots, shoes, and leggings

395906, 364148, 364165, G06F 1546

Patent

active

051596601

ABSTRACT:
Adaptive control for a wide variety of complex processes is provided by an ANN controller with input and hidden layers having a plurality of neurons, and an output layer with a single neuron. The inputs to the ANN are a time sequence of error values, and the neuron paths are weighted as a function of these error values and the present-time process output. The present-time error value may be added to the output layer of the ANN to provide faster response to sudden input changes. The controller of this invention can efficiently handle processes with nonlinear, time-varying, coupled and variable-structure behaviors as well as process parameter and/or structure uncertainties. Large steady-state gains in the process can be compensated by attenuating the ANN block output.

REFERENCES:
patent: 4054780 (1977-10-01), Bartley et al.
patent: 4133011 (1987-01-01), Kurzwell, Jr.
patent: 4195337 (1980-03-01), Bertrand et al.
patent: 4197576 (1980-04-01), Sanchez
patent: 4639853 (1987-01-01), Rake et al.
patent: 4698745 (1987-10-01), Hiroi et al.
patent: 4730259 (1988-03-01), Gallant
patent: 4852053 (1989-07-01), Turrie
patent: 4882526 (1989-11-01), Iino et al.
patent: 5016188 (1991-05-01), Lan
Psaltis et al., "A Multilayered Neural Network Controller", IEEE Control Systems Mag., Apr. 1988, pp. 17-21.
Miller et al., "Real-Time Dynamic Control of an Industrial Manipulator Using a Neural-Network-Based Learning Controller", IEEE Trans. on Robotics and Automation, vol. 6(1), Feb. 1990, pp. 1-9.
Hale, F. J., Introduction to Control System Analysis and Design, Prentice-Hall Inc., 1973, pp. 1-23.
Narendra et al., "Identification and Control of Dynamical Systems Using Neural Networks", IEEE Trans. Neural Networks, vol. 1(1), Mar. 1990, pp. 4-27.
"Neural Network Models for the Learning Control of Dynamical Systems With Application to Robotics" by F. Pourboghrat & M. R. Sayeh, Southern Illinois University.
"A Neural Network Methodology for Process Fault Diagnosis" by V. Vankatasubramania King Chan, Laboratory for Intelligent Process Systems, School of Chem. Eng. Purdue.
"Neural Network Architectures for Robotic Applications" by Sun-Yuan Kung and Jeng-Neng Hwang, members IEEE.

Affiliated with

Also associated with

Rating

Universal process control using artificial neural networks does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Universal process control using artificial neural networks, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Universal process control using artificial neural networks will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFUS-PAI-O-911786