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This study is concerned with the development of a new data-driven adaptive model-based predictive controller (MBPC) with input constraints. The proposed methods employ subspace identification technique and a singular value decomposition (SVD)-based optimisation strategy to formulate the control algorithm and incorporate the input constraints. Both direct adaptive model-based predictive controller...
In a steel plant, reheating furnaces are used for heating the steel slabs to a temperature of approximately 1200degC before rolling. Reheating furnaces consumes a lot of energy in steel plants. For competitive advantage it is important to improve the heating quality of slab and reduce the energy consumption as much as possible. This paper explores the potential of nonlinear model predictive control...
This paper investigates the application of multivariable PID controllers to a wastewater treatment process. Four multivariable PID control schemes are investigated. The methods considered are those suggested by Davison, Penttinen-Koivo, Maciejowski and a new method proposed in this paper. All of the methods are suitable for multi-input multi-output (MIMO) control loops that experience loop interaction...
This paper considers a method for improved operational robustness in applications where clusters of uninhabitated underwater vehicles (UUVs) are deployed for the purpose of achieving a shared common mission. These applications are typically characterized by their strict requirement for coordination between the individual UUVs. The proposed method is based on the assumption that the shared mission...
This paper explores the use of a multivariate statistics approach to monitor and diagnose the performance of a steam heated drying process. The results presented in this paper are a first stage investigation into the capabilities and limitations of these methods when applied to this particular process. The results show that, despite the non-linear behaviour of the drier process, the model predictions...
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