The embodiments described herein include one embodiment that provides a control method that includes connecting a first controller to a control system; receiving control system configuration data from a database, in which the configuration data comprises holistic state data of a second controller in the control system; and configuring operation of the first controller based at least in part on the configuration data received.

There is a need for more effective and efficient data modeling and/or data visualization solutions. This need can be addressed by, for example, solutions for performing data modeling and/or data visualization in an effective and efficient manner. In one example, solutions for generating a data model with dynamic relational awareness are disclosed. In another example, solutions for processing data retrieval queries using data models with dynamic relational awareness are disclosed. In yet another example, solutions for generating data visualizations using data models with dynamic relational awareness are disclosed. In a further example, solutions for integrating external data objects into data models with dynamic relational awareness are disclosed.

A computing system obtains image data representing images. Each of the images is captured at different time points of a physical environment. The physical environment comprises a first object and a second object. The computing system executes a control system to augment the physical environment. The control system detects a group forming in the images. The control system tracks an aspect of a movement, of a given object, in the group. The control system simulates the physical environment and the movement, of the given object, in the group in a simulated environment. The control system evaluates simulated actions in the simulated environment for a predefined objective for the physical environment. The predefined objective is related to an interaction between objects in the group. The control system generates based on evaluated simulated actions and autonomously from involvement by any user of the control system, an indication to augment the physical environment.

The embodiments described herein include one embodiment that provides a control method that includes connecting a first controller to a control system; receiving control system configuration data from a database, in which the configuration data comprises holistic state data of a second controller in the control system; and configuring operation of the first controller based at least in part on the configuration data received.

A wind turbine control unit includes an upsampling module that receives a first control signal that includes a current control sample value and a predicted control trajectory. The upsampling module also calculates a second control signal in dependence on the current control sample value and the predicted control trajectory. The second control signal has a higher frequency than the first control signal. The upsampling module further outputs the second control signal for controlling an actuator.

A powered balancing mobility device that can provide the user the ability to safely navigate expected environments of daily living including the ability to maneuver in confined spaces and to climb curbs, stairs, and other obstacles, and to travel safely and comfortably in vehicles. The mobility device can provide elevated, balanced travel.

A wind turbine system comprising a nacelle mounted on a tower, a rotor having a plurality of blades and a boundary layer control system configured to control airflow through blade surface openings in each of the blades. The wind turbine system includes a control system configured to: monitor an operational speed parameter of the wind turbine, and activate the boundary layer control system if it is determined that the operational speed parameter exceeds a predetermined speed parameter threshold; monitor tower motion and to activate the boundary layer control system based on a determination of excessive tower motion; monitor for a wind turbine shutdown condition, activate the boundary layer control system if it is determined that the shutdown condition has been identified; monitor the aerodynamic loads on the blades, and activate the boundary layer control system based on a determination of excessive blade loads.

An automated system for controlling a patient's blood glucose, including a blood glucose sensor and a processing and control unit, wherein the processing and control unit is configured to calculate, from a first mathematical model f.sub.CR specific to the patient and taking into account a single blood glucose value G.sup.r measured by the sensor, a factor CR representative of the patient's insulin sensitivity.

A multiple fluid model tool for multi-dimensional fluid modeling of a biological structure is presented. For example, a system includes a modeling component, a machine learning component, and a three-dimensional health assessment component. The modeling component generates a three-dimensional model of a biological structure based on multi-dimensional medical imaging data. The machine learning component predicts one or more characteristics of the biological structure based on input data and a machine learning process associated with the three-dimensional model. The three-dimensional health assessment component that provides a three-dimensional design environment associated with the three-dimensional model. The three-dimensional design environment renders physics modeling data of the biological structure based on the input data and the one or more characteristics of the biological structure on the three-dimensional model.

Devices and methods of allocating distributed energy resources (DERs) to loads connected to a microgrid based on the cost of the DERs are provided. The devices and methods may determine one or more microgrid measurements. The devices and methods may determine one or more real-time electricity prices associated with utility generation sources. The devices and methods may determine one or more forecasts. The devices and methods may determine a cost associated with one or more renewable energy sources within the microgrid. The devices and methods may determine an allocation of the renewable sources to one or more loads in the microgrid.