This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.

Coverage control for mobile sensing networks

According to an aspect of the disclosure, a home energy management system and method includes a network device disposed at a residence and a wireless home energy network capable of establishing communication with the network device. A server is disposed remotely from the residence and capable of generating a control action report to control the network devices. A controller is located at the residence and in communication with the server and configured to establish the wireless home energy network; initiate a plurality of operating status requests of the network device; receive device data in response to at least one of the operating status requests; generate a site report including the device data; initiate a communication of the site report to the remote server; and detect an availability of the control action report at the remote server in conjunction with the communication of the site report.

Energy management system and method

An energy distribution may include a server and one or more databases. The system may communicate with an energy provider to receive energy provider data, at least one information collector to receive information collector data such as individualized energy usage data, customer preferences, and customer or location characteristics, and the one or more databases for receiving data for optimization. The system may calculate a cost of service or avoided cost using at least one of the individualized energy usage data and a system generation cost at a nearest bus. The system may also forecast individualized demand by end-use, individualized demand by location, energy prices, or energy costs. The system may optimize energy distribution, energy use, cost of service, or avoided cost using the forecasted individualized demand by end-use, the forecasted individualized demand by location, the forecasted energy prices, and the forecasted energy costs.

Optimization of microgrid energy use and distribution

A thermostat for controlling an HVAC system is described, the thermostat having a user interface that is visually pleasing, approachable, and easy to use while also providing ready access to, and intuitive navigation within, a menuing system capable of receiving a variety of different types of user settings and/or control parameters. For some embodiments, the thermostat comprises a housing, a ring-shaped user-interface component configured to track a rotational input motion of a user, a processing system configured to identify a setpoint temperature value based on the tracked rotational input motion, and an electronic display coupled to the processing system. An interactive thermostat menuing system is accessible to the user by an inward pressing of the ring-shaped user interface component. User navigation within the interactive thermostat menuing system is achievable by virtue of respective rotational input motions and inward pressings of the ring-shaped user interface component.

Thermostat user interface

This paper addresses the problem of ensuring trustworthy computation in a linear consensus network. A solution to this problem is relevant for several tasks in multi-agent systems including motion coordination, clock synchronization, and cooperative estimation. In a linear consensus network, we allow for the presence of misbehaving agents, whose behavior deviate from the nominal consensus evolution. We model misbehaviors as unknown and unmeasurable inputs affecting the network, and we cast the misbehavior detection and identification problem into an unknown-input system theoretic framework. We consider two extreme cases of misbehaving agents, namely faulty (non-colluding) and malicious (Byzantine) agents. First, we characterize the set of inputs that allow misbehaving agents to affect the consensus network while remaining undetected and/or unidentified from certain observing agents. Second, we provide worst-case bounds for the number of concurrent faulty or malicious agents that can be detected and identified. Precisely, the consensus network needs to be 2k+1 (resp. k+1) connected for k malicious (resp. faulty) agents to be generically detectable and identifiable by every well behaving agent. Third, we quantify the effect of undetectable inputs on the final consensus value. Fourth, we design three algorithms to detect and identify misbehaving agents. The first and the second algorithm apply fault detection techniques, and affords complete detection and identification if global knowledge of the network is available to each agent, at a high computational cost. The third algorithm is designed to exploit the presence in the network of weakly interconnected subparts, and provides local detection and identification of misbehaving agents whose behavior deviates more than a threshold, which is quantified in terms of the interconnection structure.

/pdf/consensus-computation-in-unreliable-networks-a-system-2bkpshrmcp.pdf

Consensus Computation in Unreliable Networks: A System Theoretic Approach

A system for optimizing customer utility usage in a utility network of customer sites, each having one or more utility devices, where customer site is communicated between each of the customer sites and an optimization server having software for optimizing customer utility usage over one or more networks, including private and public networks. A customer site model for each of the customer sites is generated based upon the customer site information, and the customer utility usage is optimized based upon the customer site information and the customer site model. The optimization server can be hosted by an external source or within the customer site. In addition, the optimization processing can be partitioned between the customer site and an external source.

Energy optimization system

A key review of building integrated photovoltaic (BIPV) systems

A key review of wastewater source heat pump (WWSHP) systems

Heat exchanger applications in wastewater source heat pumps for buildings: A key review

We consider a gradient climbing problem where the objective is to steer a group of vehicles to the extrema of an unknown scalar field distribution while keeping a prescribed formation. We address this task by developing a scheme in which the leader performs extremum seeking for the minima or maxima of the field, and other vehicles follow according to passivity-based coordination rules. The extremum-seeking approach generates approximate gradients of the field locally by "dithering" sensor positions. We show that if there is sufficient time-scale separation between the fast dither and slow gradient motions of the leader vehicle, the followers only respond to the gradient motion, and filter out the dither component, while keeping the prescribed formation.

Emrah Biyik

Papers

Energy optimization system

A key review of building integrated photovoltaic (BIPV) systems

A key review of wastewater source heat pump (WWSHP) systems

Heat exchanger applications in wastewater source heat pumps for buildings: A key review

Gradient climbing in formation via extremum seeking and passivity-based coordination rules