Satish Narayanan

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Current climate control systems often rely on building regulation maximum occupancy numbers for maintaining proper temperatures. However, in many situations, there are rooms that are used infrequently, and may be heated or cooled needlessly. Having knowledge regarding occupancy and being able to accurately predict usage patterns may allow significant(More)
Multiscale approaches to accelerate the convergence of decentralized consensus problems are introduced. Consecutive consensus iterations are executed on several scales to achieve fast convergence for networks with poor connectivity. As an example the proposed algorithm is applied to the decentralized Kalman filtering problem for estimation of contaminants(More)
We introduce the sensor-utility-network (SUN) method for occupancy estimation in buildings. Based on inputs from a variety of sensor measurements, along with historical data regarding building utilization, the SUN estimator produces occupancy estimates through the solution of a recedinghorizon convex optimization problem. State-of-the-art on-line occupancy(More)
The paper develops application of techniques from robust and universal hypothesis testing for anomaly detection and change-point detection in dynamic, interconnected systems. This theory is extended using the concept of projected Markov models originally proposed by Claude Shannon. Also presented is a detailed application to anomaly detection from people(More)
Predictive-control methods have been recently employed for demand-response control of building and districtlevel HVAC systems. Such approaches rely on models and parameter estimates to meet comfort constraints and to achieve the theoretical system-efficiency gains. In this paper we present a methodology that establishes achievable targets for controlmodel(More)
The paper presents field demonstration results from the implementation of a model predictive control formulation to optimize the operation of a variable volume, dual-duct, multi-zone HVAC unit serving an existing mid-size commercial building. This full-scale study is used to estimate the benefits of advanced building control technologies that can be(More)
In this paper we propose a Lagrangian Coherent Structures (LCS) based approach to modeling and estimation of contaminant transport and mixing in large indoor spaces in buildings. Specifically, we show how the knowledge of LCS can be exploited to enhance Proper Orthogonal Decomposition (POD) based model reduction, sensor placement and comparing effect of(More)