Over the last several years, a great amount of research work has been focused on the development of model predictive control techniques for the indoor climate control of buildings, but, despite the promising results, this technology is still not adopted by the industry. One of the main reasons for this is the increased cost associated with the development and calibration (or identification) of mathematical models of special structure used for predicting future states of the building. We propose a methodology to overcome this obstacle by replacing these hand-engineered mathematical models with a thermal simulation model of the building developed using detailed thermal simulation engines such as EnergyPlus. As designing better controllers requires interacting with the simulation model, a central part of our methodology is the control improvement (or optimisation) module, facilitating two simulation-based control improvement methodologies: one based in multi-criteria decision analysis methods and the other based on state-space identification of dynamical systems using Gaussian process models and reinforcement learning. We evaluate the proposed methodology in a set of simulation-based experiments using the thermal simulation model of a real building located in Portugal. Our results indicate that the proposed methodology could be a viable alternative to model predictive control-based supervisory control in buildings.

Abstract:The waterborne sector faces nowadays significant challenges due to several environmental, financial and other concerns. Such challenges may be addressed, among others, by optimising voyage plans, and diagnosing as early as possible engine failures that may lead to performance degradation. These two issues are addressed by the decision support system (DSS) presented herein, which focuses on the operation of merchant ships. For the development of voyage plans, a multicriteria decision problem is developed and handled with the PROMETHE method, while a multivariable control chart is used for the fault diagnosis problem. A MATLAB-based software implementation of the DSS has been developed adopting a modular architecture, while, in order to provide a generic software solution, the required input data are retrieved from dedicated web-services, following specific communication and data exchange protocols.

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