In this paper, a reasoning-based intelligent system makes use of fuzzy control approach, which is designed for thermal comfort applications by using an embedded microcontroller system. In general, it is not possible to implement the mathematical thermal comfort models in actual environment. Thermal comfort usually depends on four environmental parameters and two personal parameters. Normally, o...

The ever-increasing energy consumption of data centers is becoming a crucial problem nowadays. This paper discusses the benefits and challenges of coordinating dynamic server provisioning and thermal dynamics for energy control of data centers. A model predictive control approach, considering the computational and thermal characteristics of a data center and their interactions, together with dy...

We investigate data-driven, simple-to-implement residential environmental models that can serve as the basis for energy saving algorithms in both retrofits and new designs of buildings. Despite nonlinearity underlying dynamics, using Koopman operator theory framework this study we show a linear second order model embedding, captures physics occur inside single or multi zone space does well when...

Model Predictive control is an advanced control technique that has been used to optimize thermal comfort in buildings. Nowadays, the new buildings are characterized by an important inertia as well as low power heating systems. Since the thermal losses are very low, taking into account the intermittent occupancies in the control strategy is questionable. More precisely, in this paper, two model ...