A Novel Method to Prevent Control System Instability Based on a Soft Computing Knowledge System
The aim of this study is to present a novel soft computing method to assure PID tuning parameters place the system into a stable region by applying the gain scheduling method. First the system is identified for each significant operation point. Then using transfer functions solid structures of stability are calculated to program artificial neural networks, whose object is to prevent system from transitioning to instability. The method is verified empirically under a data set obtained by a pilot plant.
KeywordsKBS Robust stability artificial neural networks soft computing
Unable to display preview. Download preview PDF.
- 1.Calvo-Rolle, J.L., Alonso-Alvarez, A., Ferreiro-Garcia, R.: Using Knowledge Engineering in a PID Regulator in Non Linear Process Control. Ingenieria Quimica 32, 21–28 (2007)Google Scholar
- 4.Astrom, K.J., Hagglund, T.: Advanced PID Control. Pearson Education, Madrid (2009)Google Scholar
- 5.Astrom, K.J., Wittenmark, B.: Adaptive Control. Addison Wesley Publis. Company, Reading (1989)Google Scholar
- 8.Bishop, C.M.: Neural Networks for Pattern Recognition, Oxford (1995)Google Scholar
- 13.Astrom, K.J., Hagglund, T.: Revisiting the Ziegler–Nichols tuning rules for PID control. Asian Journal of Control 4(4), 364–380 (2002)Google Scholar
- 14.Ljung, L.: System Identification - Theory For the User, 2nd edn. PTR Prent. Hall, N.J (1999)Google Scholar