Evolutionary Algorithms
Tuning Model Base Predictive Control
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Evolutionary algorithms have proven to be an enormously powerful and successful problem-solving strategy for optimisation problems. This book presents a novel application for implementing Evaluation Algorithm to tune Model Base Predictive Control (MBPC), MBPC systems require accurate models if high performance is to be attained. Most chemical processes are nonlinear in nature, which makes developing precise models challenging. Indeed, there are no procedures available for tuning MBPC that offer robust performance in the presence of model uncertainty. Using of Evolution Algorithms offer the opp...
Evolutionary algorithms have proven to be an enormously powerful and successful problem-solving strategy for optimisation problems. This book presents a novel application for implementing Evaluation Algorithm to tune Model Base Predictive Control (MBPC), MBPC systems require accurate models if high performance is to be attained. Most chemical processes are nonlinear in nature, which makes developing precise models challenging. Indeed, there are no procedures available for tuning MBPC that offer robust performance in the presence of model uncertainty. Using of Evolution Algorithms offer the opportunity of incorporating multiple objective functions to tune and optimise MBPC in term of H-two, H-infinity and LQC design. This resulted in increased stability robustness and the satisfaction of the performance objectives.
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