most citedAdaptive Contraction-based Control of Uncertain Nonlinear Processes using Neural Networks

1 citations · 1 across the 2 of their papers we have counts for

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2 papers

eess.SY2022

A Contraction-constrained Model Predictive Control for Nonlinear Processes using Disturbance Forecasts

Ryan McCloy, Lai Wei, Jie Bao

Model predictive control (MPC) has become the most widely used advanced control method in process industry. In many cases, forecasts of the disturbances are available, e.g., predic…

eess.SY2022★ 1 cited

Adaptive Contraction-based Control of Uncertain Nonlinear Processes using Neural Networks

Lai Wei, Ryan McCloy, Jie Bao

Driven by the flexible manufacturing trend in the process control industry and the uncertain nature of chemical process models, this article aims to achieve offset-free tracking fo…