Verified Interval-Based Predictive and Variable-Structure Control for Solid Oxide Fuel Cell Systems: VerIPC-SOFC

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Interval methods provide powerful tools for parameter identification, where the development of approaches for real-time capable robust control and state estimation has gained much attention in recent years. Such control and estimation procedures are especially based on variable-structure and model-predictive techniques as well as on sensitivity-based approaches. The applicants at the Chair or Mechatronics at the University of Rostock have already succeeded in demonstrating the efficiency of such novel methods and implementations for selected applications in both simulation and laboratory experiments.In contrast to a laboratory environment, the use of interval methods is not yet widely spread in real-life industrial applications. The most important reason for this fact is the large amount of application-dependent implementations that are necessary if interval methods are to be used for the offline control synthesis and for the online control implementation. Therefore, the first two funding periods of this project were focused on the implementation of general routines for identification, control, and state estimation by means of interval techniques. Here, the focus was on the safe operation of high-temperature fuel cells in non-stationary phases. Based on low-dimensional control-oriented models for the nonlinear dynamics of SOFCs, techniques were derived for a guaranteed parameter identification and subsequently validated with experimental data. This identification, leading to tolerance bounds for the non-measurable quantities due to the application of interval methods, is capable of identifying structural ambiguities in the system's parameterization and of providing this information to a guaranteed stabilizing control design.To implement robust control techniques despite this uncertainty and to detect operating conditions and degradation effects as soon as possible, which are crucial for the overall system lifetime, interval algorithms are developed for the real-time control of uncertain dynamic systems. So far, the focus was on interval-based control techniques for single-input single-output systems, which shall now be generalized to tasks in which multiple input and output variables are of interest.Based on such multi-variable control techniques, it is desired to optimize the overall system efficiency from an energetic point of view. For that purpose, peripheral system components such as the gas preheaters and catalytic converters for the exhaust gas need to be integrated into the dynamic system model as well as in the interval-based control design. All modeling and control procedures shall be verified numerically in simulations and validated experimentally on an available SOFC test rig. To make to developed software routines available to a broad audience and to highlight the way how interval methods can be applied efficiently to real-life control applications, it is planned to publish the developed source codes in a generalized form.