Constraint neuro-model based predictive control

Soufian, Majeed; Rahman, Adel A.; Soufian, Mustapha; Mokbe, A. A.

Abstract

Constraints are always present in the real life process. Control of processes without considering the constraints can lead to sub-optimal behaviour and may result in instability and violation of safety. Lack of a solid and applicable closed loop control theory in dealing with constraints cause that in the usual process-controlpractice either to ignore the constraints or the constraints are dealt with ad-hoc fix ups using split range controllers, overrides, min-max selectors with some logic and etc.

Citation

Soufian, M., Rahman, A. A., Soufian, M., & Mokbe, A. A. (2004). Constraint neuro-model based predictive control. In A. Lotfi, & J. M. Garibaldi (Eds.), Applications and Science in Soft Computing (279-286). https://doi.org/10.1007/978-3-540-45240-9_38

• Presentation Conference Type: Conference Paper (Published)
• Conference Name: 4th International Conference on Recent Advances in Soft Computing
• Start Date: Dec 12, 2002
• End Date: Dec 13, 2002
• Acceptance Date: May 5, 2003
• Publication Date: Jan 1, 2004
• Deposit Date: May 15, 2017
• Publisher: Springer
• Volume: 24
• Pages: 279-286
• Series Title: Advances in Intelligent and Soft Computing
• Series ISSN: 1867-5662
• Book Title: Applications and Science in Soft Computing
• Chapter Number: Part V - Soft Computing Applications
• ISBN: 9783540408567
• DOI: https://doi.org/10.1007/978-3-540-45240-9_38
• Keywords: Artificial Neural Network Model; Model Predictive Control; Sequential Quadratic Programming; Integrate Square Error; Generalise Predictive Control
• Public URL: http://researchrepository.napier.ac.uk/Output/845157