Adaptive Nonlinear Model Predictive Control of an Engine Air Path. Issue 10 (2021)

• Record Type: Journal Article
• Authors: Florian Meier, Max Haugeneder; Adelberger, Daniel; Re, Luigi del
• Is Part Of: IFAC-PapersOnLine. Volume 54:Issue 10(2021)
• Page Start: 114
• Page End: 119
• Publication Date: 2021
• Subjects: automotive control -- system identification -- adaptive control -- predictive control; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2021.10.150
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: It is well known that high performing control based on a nominal model may underperform when system parameters change e.g. due to wear. Adaptive controls are a well established way to tackle this problem, but their usage is not trivial, especially when they are used for complex nonlinear systems with constraints like the air path of a combustion engine. In particular, excitation can be insufficient for the update of a model with many parameters. Against this background, we extend and test an approach based on directional forgetting on a production engine, showing that this approach is viable for practical applications.