Given restrictions that comfort conditions in the interior of a building are satisfied, it becomes obvious that the problem of energy conservation is a multidimensional one. Scientists from a variety of fields have been working on this problem for a few decades now; however, essentially it remains an open issue. In the beginning of this article, we define the whole problem in which the topics are: energy, comfort and control. Next, we briefly present the conventional control systems in buildings and their advantages and disadvantage. We will also see how the development of intelligent control systems has improved the efficiency of control systems for the management of indoor environment including user preferences. This paper presents a survey exploring state of the art control systems in buildings. Attention will be focused on the design of agent-based intelligent control systems in building environments. In particular, this paper presents a multi-agent control system (MACS). This advanced control system is simulated using TRNSYS/MATLAB. The simulation results show that the MACS successfully manage the user’s preferences for thermal and illuminance comfort, indoor air quality and energy conservation.

Advanced control systems engineering for energy and comfort management in a building environment—A review

Buildings all around the world consume a significant amount of energy, which is more or less one-third of the total primary energy resources. This has raised concerns over energy supplies, rapid energy resource depletion, rising building service demands, improved comfort life styles along with the increased time spent in buildings; consequently, this has shown a rising energy demand in the near future. However, contemporary buildings’ energy efficiency has been fast tracked solution to cope/limit the rising energy demand of this sector. Building energy efficiency has turned out to be a multi-faceted problem, when provided with the limitation for the satisfaction of the indoor comfort index. However, the comfort level for occupants and their behavior have a significant effect on the energy consumption pattern. It is generally perceived that energy unaware activities can also add one-third to the building’s energy performance. Researchers and investigators have been working with this issue for over a decade; yet it remains a challenge. This review paper presents a comprehensive and significant research conducted on state-of-the-art intelligent control systems for energy and comfort management in smart energy buildings (SEB’s). It also aims at providing a building research community for better understanding and up-to-date knowledge for energy and comfort related trends and future directions. The main table summarizes 121 works closely related to the mentioned issue. Key areas focused on include comfort parameters, control systems, intelligent computational methods, simulation tools, occupants’ behavior and preferences, building types, supply source considerations and countries research interest in this sector. Trends for future developments and existing research in this area have been broadly studied and depicted in a graphical layout. In addition, prospective future advancements and gaps have also been discussed comprehensively.

A review on optimized control systems for building energy and comfort management of smart sustainable buildings

A new exact, explicit, and computationally efficient solution for three-dimensional (3-D) position estimation based on range measurements from three stations is proposed. The simple polynomial-type form of the new algorithm facilitates the performance analysis. Formulae are provided for both the variance and the bias of the position estimates. The systematic error is a joint effect of both the measurement noise and the system nonlinearity and its magnitude cannot be ignored if highly accurate localization is required. Performance evaluation results are presented for various conditions.

Efficient solution and performance analysis of 3-D position estimation by trilateration

Buildings account for nearly 40% of global energy consumption. About 40% and 15% of that are consumed, respectively, by HVAC and lighting. These energy uses can be reduced by integrated control of active and passive sources of heating, cooling, lighting, shading and ventilation. However, rigorous studies of such control strategies are lacking since computationally tractable models are not available. In this paper, a novel formulation capturing key interactions of the above building functions is established to minimize the total daily energy cost. To obtain effective integrated strategies in a timely manner, a methodology that combines stochastic dynamic programming (DP) and the rollout technique is developed within the price-based coordination framework. For easy implementation, DP-derived heuristic rules are developed to coordinate shading blinds and natural ventilation, with simplified optimization strategies for HVAC and lighting systems. Numerical simulation results show that these strategies are scalable, and can effectively reduce energy costs and improve human comfort.

Building Energy Management: Integrated Control of Active and Passive Heating, Cooling, Lighting, Shading, and Ventilation Systems

Predictive control techniques for energy and indoor environmental quality management in buildings

Design of a fuzzy system for living space thermal-comfort regulation

Thermal-comfort degradation by a visual comfort fuzzy-reasoning machine under natural ventilation

A new aircraft geometric height computation system based on a secondary surveillance radar (SSR) and an omni-directionat radar has recently been presented. One interesting aspect of this system is that it employs a simple analytical method to estimate and compensate for observable systematic errors, mainly created by the aircraft transponder. Herein, this off-line processing algorithm is extended to cover non-level flights by augmenting the aircraft vertical motion model.

Computation of aircraft geometric height under radar surveillance for non-level flights

The authors address the subject of aircraft geometric-height estimation, based on measurements from three distance-measuring equipment (DME) stations. A new improved height computation algorithm is presented, which is computationally efficient and mathematically tractable. The simple form of the new algorithm leads to easy derivation of analytic expressions for both the standard deviation and inherent systematic errors. Evaluation results are presented for representative conditions. The appropriate form of the Kalman filtering algorithm is proposed for producing bias-free and more accurate height estimates.

Advances in aircraft-height estimation using distance-measuring equipment

The objective here is the analysis of a systematic error inherently existing in aircraft geometric height monitoring under radar surveillance. This error is caused by the nonlinear processing of noisy measurements. The geometric height system under investigation uses mixed-type radar data, since the height is computed by referring range raw measurements to horizontal trajectory smoothed data. >

Inherent bias assessment in height computation employing mixed-type radar data

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