Abstract
When the plant to control is subject to large variations of its point of operation, or if some of its parameters are uncertain, the corresponding change in local dynamics prevents a single linear controller to yield a good performance, or even to globally stabilize the system. In order to tackle this issue, the approach followed in the present chapter consists of the identification of a bank of linear models that represent the plant dynamics in different regions of operation and/or different parameter ranges. To each of these so called local models a linear controller (named local controller) is associated that is designed such that, when connected to the plant, it yields the desired performance in the operating region/parameter range to which the local model is associated. To prevent instability that stems from fast switching a dwell time condition is imposed, meaning that, when a local controller is connected to the plant, it remains so for at least a minimum time interval. The application of this multiple model adaptive control (MMAC) strategy is illustrated by its experimental application to an air heating fan and a distributed collector solar field.
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Lemos, J.M., Neves-Silva, R., Igreja, J.M. (2014). Multiple Model Adaptive Control. In: Adaptive Control of Solar Energy Collector Systems. Advances in Industrial Control. Springer, Cham. https://doi.org/10.1007/978-3-319-06853-4_4
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DOI: https://doi.org/10.1007/978-3-319-06853-4_4
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