Multi-objective Performance Evaluation of Controllers for a Thermal Process
Most engineering systems are multivariable in nature, where more than one input controls more than one output. The challenge arises in controlling these types of systems due to interaction among inputs and outputs. In an attempt to optimise the performance of these processes, many performance objectives need to be considered simultaneously. In most cases, these objectives often conflict hence a need for Multi-objective Optimisation (MOO) analysis. In this paper MOO design for Model Predictive Control (MPC) and Proportional Integral (PI) control are investigated for a multivariable process. The Pareto sets for both controllers is generated using Pareto Differential Evolution (PDE) and then compared using n-dimensional visualization tool, Level Diagrams to evaluate which controller is best for the process. Solutions which provide a preferred performance are then selected and tested experimentally on a thermal process.
We would like to thank iThemba LABS for the financial support.
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