Predictive Adaptive Control of water level in canal pools

A case study on the use of a predictive adaptive algorithm to control pool level in a pilot water distribuition canal is described. The algorithm is a modification of the basic MUSMAR controller that includes parallel integral action and, in the case of multiple pools, feedforward action to coordinate the gates. Experimental results in the case of a single pool and simulations for multiple pools are presented. The contributions of the paper stem from the explicitation of rules for tuning the adaptive controller in a practical situation and from the coordination of different pools using reduced complexity controllers and feedforward in a multivariable settin

Model-free adaptive iterative learning control of melt pool width in wire arc additive manufacturing

© 2020, Springer-Verlag London Ltd., part of Springer Nature. Wire arc additive manufacturing (WAAM) is a Direct Energy Deposition (DED) technology, which utilize electrical arc as heat source to deposit metal material bead by bead to make up the final component. However, issues like the lack of assurance in accuracy, repeatability and stability hinder the further application in industry. Therefore, a Model Free Adaptive Iterative Learning Control (MFAILC) algorithm was developed to be applied in WAAM process in this study. The dynamic process of WAAM is modelled by adaptive neuro fuzzy inference system (ANFIS). Based on this ANFIS model, simulations are performed to demonstrate the effectiveness of MFAILC algorithm. Furthermore, experiments are conducted to investigate the tracking performance and robustness of the MFAILC controller. This work will help to improve the forming accuracy and automatic level of WAAM