While compressive sensing (CS) has been one of the most vibrant research fields in the past few y... more While compressive sensing (CS) has been one of the most vibrant research fields in the past few years, most development only applies to linear models. This limits its application in many areas where CS could make a difference. This paper presents a novel extension of CS to the phase retrieval problem, where intensity measurements of a linear system are used to recover a complex sparse signal. We propose a novel solution using a lifting technique – CPRL, which relaxes the NP-hard problem to a nonsmooth semidefinite program. Our analysis shows that CPRL inherits many desirable properties from CS, such as guarantees for exact recovery. We further provide scalable numerical solvers to accelerate its implementation. 1
ABSTRACT Blind system identification is known to be an ill-posed problem and without further assu... more ABSTRACT Blind system identification is known to be an ill-posed problem and without further assumptions, no unique solution is at hand. In this contribution, we are concerned with the task of identifying an ARX model from only output measurements. We phrase this as a constrained rank minimization problem and present a relaxed convex formulation to approximate its solution. To make the problem well posed we assume that the sought input lies in some known linear subspace.
ABSTRACT Blind system identification is known to be a hard ill-posed problem and without further ... more ABSTRACT Blind system identification is known to be a hard ill-posed problem and without further assumptions, no unique solution is at hand. In this contribution, we are concerned with the task of identifying an ARX model from only output measurements. Driven by the task of identifying systems that are turned on and off at unknown times, we seek a piecewise constant input and a corresponding ARX model which approximates the measured outputs. We phrase this as a rank minimization problem and present a relaxed convex formulation to approximate its solution. The proposed method was developed to model power consumption of electrical appliances and is now a part of a bigger energy disaggregation framework. Code will be made available online.
Proceedings of the 3rd international conference on High confidence networked systems - HiCoNS '14, 2014
ABSTRACT Utility companies have many motivations for modifying energy consumption patterns of con... more ABSTRACT Utility companies have many motivations for modifying energy consumption patterns of consumers such as revenue decoupling and demand response programs. We model the utility company-consumer interaction as a principal-agent problem and present an iterative algorithm for designing incentives while estimating the consumer's utility function.
2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2012
ABSTRACT We introduce a model for the operational costs of an electric distribution utility. The ... more ABSTRACT We introduce a model for the operational costs of an electric distribution utility. The model focuses on two of the new services that are enabled by the Advanced Metering Infrastructure (AMI): (1) the fine-grained anomaly detection that is possible thanks to the frequent smart meter sampling rates (e.g., 15 minute sampling intervals of some smart meter deployments versus monthly-readings from old meters), and (2) the ability to shape the load thanks to advanced demand-response mechanisms that leverage AMI networks, such as direct-load control. We then study two security problems in this context. (1) In the first part of the paper we formulate the problem of electricity theft detection (one of the use-cases of anomaly detection) as a game between the electric utility and the electricity thief. The goal of the electricity thief is to steal a predefined amount of electricity while minimizing the likelihood of being detected, while the electric utility wants to maximize the probability of detection and the degree of operational cost it will incur for managing this anomaly detection mechanism. (2) In the second part of the paper we formulate the problem of privacy-preserving demand response as a control theory problem, and show how to select the maximum sampling interval for smart meters in order to protect the privacy of consumers while maintaining the desired load shaping properties of demand-response programs.
52nd IEEE Conference on Decision and Control, 2013
ABSTRACT Energy disaggregation, also known as non-intrusive load monitoring (NILM), is the task o... more ABSTRACT Energy disaggregation, also known as non-intrusive load monitoring (NILM), is the task of separating aggregate energy data for a whole building into the energy data for individual appliances. Studies have shown that simply providing disaggregated data to the consumer improves energy consumption behavior. However, placing individual sensors on every device in a home is not presently a practical solution. Disaggregation provides a feasible method for providing energy usage behavior data to the consumer which utilizes currently existing infrastructure. In this paper, we present a novel framework to perform the energy disaggregation task. We model each individual device as a single-input, single-output system, where the output is the power consumed by the device and the input is the device usage. In this framework, the task of disaggregation translates into finding inputs for each device that generates our observed power consumption. We describe an implementation of this framework, and show its results on simulated data as well as data from a small-scale experiment.
Electroactive Polymer Actuators and Devices (EAPAD) 2011, 2011
ABSTRACT Because of size and complexity concerns, implementing feedback control for ionic polymer... more ABSTRACT Because of size and complexity concerns, implementing feedback control for ionic polymer-metal composite (IPMC) actuators is often difficult or costly in many of their envisioned biomedical and robotic applications. It is thus of interest to develop open-loop control strategies for these actuators. Such strategies, however, are susceptible to change of IPMC dynamics under varying environmental conditions, a predominant example being the temperature. In this paper we present a novel approach to open-loop control of IPMC actuators in the presence of ambient temperature changes. First, a method is proposed for modeling the temperature-dependent actuation dynamics. The empirical frequency response of an IPMC actuator, submerged in a water bath with controlled temperature, is obtained for a set of temperatures. For each temperature, a transfer function of a given structure is found to fit the measured data. A temperature-dependent transfer function model is then derived by curve-fitting each zero or pole as a simple polynomial function of the temperature. Open-loop control is then realized by inverting the model at a given temperature based on the auxiliary temperature measurement. However, the obtained model for IPMC actuators is of non-minimum phase and cannot be inverted directly. A stable but non-causal algorithm is adopted to implement the inversion. Furthermore, a finite-preview algorithm is proposed to enable near real-time tracking of desired outputs. Experimental results show that the proposed approach is effective in improving the tracking performance of IPMC actuators under varying temperatures.
While compressive sensing (CS) has been one of the most vibrant research fields in the past few y... more While compressive sensing (CS) has been one of the most vibrant research fields in the past few years, most development only applies to linear models. This limits its application in many areas where CS could make a difference. This paper presents a novel extension of CS to the phase retrieval problem, where intensity measurements of a linear system are used to recover a complex sparse signal. We propose a novel solution using a lifting technique – CPRL, which relaxes the NP-hard problem to a nonsmooth semidefinite program. Our analysis shows that CPRL inherits many desirable properties from CS, such as guarantees for exact recovery. We further provide scalable numerical solvers to accelerate its implementation. 1
ABSTRACT Blind system identification is known to be an ill-posed problem and without further assu... more ABSTRACT Blind system identification is known to be an ill-posed problem and without further assumptions, no unique solution is at hand. In this contribution, we are concerned with the task of identifying an ARX model from only output measurements. We phrase this as a constrained rank minimization problem and present a relaxed convex formulation to approximate its solution. To make the problem well posed we assume that the sought input lies in some known linear subspace.
ABSTRACT Blind system identification is known to be a hard ill-posed problem and without further ... more ABSTRACT Blind system identification is known to be a hard ill-posed problem and without further assumptions, no unique solution is at hand. In this contribution, we are concerned with the task of identifying an ARX model from only output measurements. Driven by the task of identifying systems that are turned on and off at unknown times, we seek a piecewise constant input and a corresponding ARX model which approximates the measured outputs. We phrase this as a rank minimization problem and present a relaxed convex formulation to approximate its solution. The proposed method was developed to model power consumption of electrical appliances and is now a part of a bigger energy disaggregation framework. Code will be made available online.
Proceedings of the 3rd international conference on High confidence networked systems - HiCoNS '14, 2014
ABSTRACT Utility companies have many motivations for modifying energy consumption patterns of con... more ABSTRACT Utility companies have many motivations for modifying energy consumption patterns of consumers such as revenue decoupling and demand response programs. We model the utility company-consumer interaction as a principal-agent problem and present an iterative algorithm for designing incentives while estimating the consumer's utility function.
2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2012
ABSTRACT We introduce a model for the operational costs of an electric distribution utility. The ... more ABSTRACT We introduce a model for the operational costs of an electric distribution utility. The model focuses on two of the new services that are enabled by the Advanced Metering Infrastructure (AMI): (1) the fine-grained anomaly detection that is possible thanks to the frequent smart meter sampling rates (e.g., 15 minute sampling intervals of some smart meter deployments versus monthly-readings from old meters), and (2) the ability to shape the load thanks to advanced demand-response mechanisms that leverage AMI networks, such as direct-load control. We then study two security problems in this context. (1) In the first part of the paper we formulate the problem of electricity theft detection (one of the use-cases of anomaly detection) as a game between the electric utility and the electricity thief. The goal of the electricity thief is to steal a predefined amount of electricity while minimizing the likelihood of being detected, while the electric utility wants to maximize the probability of detection and the degree of operational cost it will incur for managing this anomaly detection mechanism. (2) In the second part of the paper we formulate the problem of privacy-preserving demand response as a control theory problem, and show how to select the maximum sampling interval for smart meters in order to protect the privacy of consumers while maintaining the desired load shaping properties of demand-response programs.
52nd IEEE Conference on Decision and Control, 2013
ABSTRACT Energy disaggregation, also known as non-intrusive load monitoring (NILM), is the task o... more ABSTRACT Energy disaggregation, also known as non-intrusive load monitoring (NILM), is the task of separating aggregate energy data for a whole building into the energy data for individual appliances. Studies have shown that simply providing disaggregated data to the consumer improves energy consumption behavior. However, placing individual sensors on every device in a home is not presently a practical solution. Disaggregation provides a feasible method for providing energy usage behavior data to the consumer which utilizes currently existing infrastructure. In this paper, we present a novel framework to perform the energy disaggregation task. We model each individual device as a single-input, single-output system, where the output is the power consumed by the device and the input is the device usage. In this framework, the task of disaggregation translates into finding inputs for each device that generates our observed power consumption. We describe an implementation of this framework, and show its results on simulated data as well as data from a small-scale experiment.
Electroactive Polymer Actuators and Devices (EAPAD) 2011, 2011
ABSTRACT Because of size and complexity concerns, implementing feedback control for ionic polymer... more ABSTRACT Because of size and complexity concerns, implementing feedback control for ionic polymer-metal composite (IPMC) actuators is often difficult or costly in many of their envisioned biomedical and robotic applications. It is thus of interest to develop open-loop control strategies for these actuators. Such strategies, however, are susceptible to change of IPMC dynamics under varying environmental conditions, a predominant example being the temperature. In this paper we present a novel approach to open-loop control of IPMC actuators in the presence of ambient temperature changes. First, a method is proposed for modeling the temperature-dependent actuation dynamics. The empirical frequency response of an IPMC actuator, submerged in a water bath with controlled temperature, is obtained for a set of temperatures. For each temperature, a transfer function of a given structure is found to fit the measured data. A temperature-dependent transfer function model is then derived by curve-fitting each zero or pole as a simple polynomial function of the temperature. Open-loop control is then realized by inverting the model at a given temperature based on the auxiliary temperature measurement. However, the obtained model for IPMC actuators is of non-minimum phase and cannot be inverted directly. A stable but non-causal algorithm is adopted to implement the inversion. Furthermore, a finite-preview algorithm is proposed to enable near real-time tracking of desired outputs. Experimental results show that the proposed approach is effective in improving the tracking performance of IPMC actuators under varying temperatures.
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