Data-driven methods for building control - A review and promising future directions
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Model predictive control (MPC) is a very effective approach to control nonlinear systems, especially when the systems are high dimensional and/or constrained. MPC formulates the problem of input trajectory generation as an optimization problem. However, du ...
Abstract Predictive control and feedback linearization are two popular approaches for the control of nonlinear systems. In this paper, a cascade combination of the two metho ds is proposed, where control based on input- output feedback linearization forms ...
Optimization arises naturally when process performance needs improvement. This is often the case in industry because of competition – the product has to be proposed at the lowest possible cost. From the point of view of control, optimization consists in de ...
Model Predictive Control has been implemented on a large drainage canal system in the Netherlands. This water system can be represented as a reservoir with uncertain inflow due to rainfall runoff and a water level that has to be kept within a certain range ...
The adoption of stricter effluent requirements by the European Union rises large problems for small communities having few economical and technical resources. These problems motivate the synthesis of advanced optimisation-based controllers in order to enha ...
Institut National Polytechnique de Lorraine (INPL)2001
In this work, we investigated the interplay and the influence of lighting and blind control models on the heating, cooling, and lighting energy loads of an office room. By including different stochastic models for occupancy and appliances, we built a compl ...
Solid Oxide Fuel Cells (SOFC) are energy conversion devices that produce electrical energy via the reaction of a fuel with an oxidant. Although SOFCs have become credible alternatives to non-renewable energy sources, efforts are still needed to extend thei ...
