An NN-based approach for tuning servocontrollers

Neural networks (NN) are used in this paper to tune PI controllers for unknown plants, which may be nonlinear or open-loop unstable. A simple algorithm, which requires only knowledge of the plant output response direction, is used for training an NN controller, by employing the error between the ref...

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Bibliographic Details
Published in:Neural networks 1999-04, Vol.12 (3), p.513-518
Main Authors: Hemerly, Elder M., Nascimento, Cairo L.
Format: Article
Language:English
Subjects:
Adaptative systems
Adaptive control
Applied sciences
Artificial intelligence
Backpropagation
Computer science
control theory
systems
Connectionism. Neural networks
Control theory. Systems
Digital control
Exact sciences and technology
Neural network
PI controller
Process control
Process control. Computer integrated manufacturing
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Summary:Neural networks (NN) are used in this paper to tune PI controllers for unknown plants, which may be nonlinear or open-loop unstable. A simple algorithm, which requires only knowledge of the plant output response direction, is used for training an NN controller, by employing the error between the reference and the plant output. Once this controller achieves good performance, its input–output behavior is approximated by a controller with PI structure, thereby enabling the computation of proportional and integral gains. These gains are familiar to process engineers and can be directly inserted into most existing softwares for process control in industry. Computer simulations on an unstable nonlinear plant and experimental results on a thermal plant are presented to illustrate the usefulness of the proposed approach.
ISSN:0893-6080
1879-2782
DOI:10.1016/S0893-6080(98)00147-6