Adaptive control of distributed collector solar fields

Distributed collector solar fields are spatially distributed technical systems which aim at collecting and storing energy from solar radiation. They are formed by mirrors which concentrate direct incident sunlight in a pipe where an oil is able to accumulate thermic energy flows. From the control point of view, the objective consists of making the outlet oil temperature to track a reference signal by manipulating the oil flow, in the possible presence of fast disturbances caused by passing clouds. Significant levels of uncertainty motivate the use of adaptive methods. A confrontation between data-driven and model-driven adaptive control algorithms for distributed collector solar fields is made using experimental results and algorithm structure. A trade-off is shown to exist; i.e. by incorporating more information about plant dynamics, the control algorithms yield an increased performance, but they become plant dependent.

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