PhD Thesis

Fault-tolerant and Health-aware Predictive Control Schemes for Industrial Processes

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  • Started: 17/04/2015
  • Thesis project read: 03/06/2016


Merging the industrial processes, the MPC strategy and the LPV modeling, this work proposes the deep study of these approaches such that the performance of an industrial plant is improved taking into account the inherent nonlinearities of that system, the structural/parametric uncertainty included into the modeling methodology and the limitations of the control techniques in the sense on computational burden and robustness/stability guarantees involved. One of the main expected contributions of this work relies on the implementation of the designed/studied methodologies (of modeling and control) over a real pilot plant of an industrial process such as pasteurization pilot plant (PCT-23 MKII). The pasteurization system includes typical behaviors of industrial processes, where considering complex dynamical models with nonlinearities imply important challenges when a suitable control should be designed. This implementation and the obtained results will allow handling with di erent phenomena raised from the work with a real system, which also implies the generation of suitable solutions in order to tackle with such problems.