B-splines neural network assisted PID autotuning

✍ Scribed by António E. Ruano; Ana B. Azevedo

• Publisher: John Wiley and Sons
• Year: 1999
• Tongue: English
• Weight: 180 KB
• Volume: 13
• Category: Article
• ISSN: 0890-6327
• DOI: 10.1002/(sici)1099-1115(199906)13:4<291::aid-acs548>3.0.co;2-e

✦ Synopsis

This paper describes an extension of previous work on the subject of neural network proportional, integral and derivative (PID) autotuning. Basically, neural networks are employed to supply the three PID parameters, according to the integral of time multiplied by the absolute error (ITAE) criterion, to a standard PID controller. These networks were previously trained o!-line, remaining "xed thereafter.

In order to make this approach adaptive, one additional neural network is used here to model the relation between the PID parameters and the plant identi"cation measures to the ITAE value. This model will be afterwards employed in an on-line minimization routine which "nds the optimal PID parameters; these will be used to adapt, on-line, the neural networks responsible for the PID parameters.