An agricultural system including an agricultural baler and a control unit. The agricultural baler includes a baler driveline; a rotatable flywheel; and a rotary input shaft connected by way of the baler driveline to the rotatable flywheel. The driveline includes one or more clutches for controllably transferring rotary drive between the input shaft and the flywheel. The control unit is configured to receive input-power-data indicative of a drive power available at the rotary input shaft; and determine a clutch-control-signal for controlling an amount of torque transferred from the input shaft to the flywheel bye the one or more clutches, based on the input-power-data.

A method and an apparatus for dynamically determining a yaw control precision. The method comprises: during a predetermined time period, collecting a plurality of wind speed data and a plurality of wind direction data, and processing the collected plurality of wind speed data and plurality of wind direction data; on the basis of the processed wind speed data and wind direction data, establishing a model of the corresponding relationship between wind speed, wind direction angle change, yaw control precision, yaw fatigue, and power loss; and, on the basis of the current wind speed data, wind direction data, predetermined yaw fatigue range, and predetermined power loss range, by means of the corresponding relationship model, determining the yaw control precision corresponding to the current wind speed and current wind direction angle change.

Systems, methods, techniques and apparatuses of power network state estimation are disclosed. One exemplary embodiment is a method for state estimation in a power network comprising receiving a set of supervisory control and data acquisition (SCADA) information including a power network topology; generating a SCADA state estimation using the set of SCADA information; receiving, with a cloud-computing architecture, a set of PMU phasors; aligning, with the cloud-computing architecture, a timestamp of the SCADA estimation and a timestamp of the set of PMU phasors; updating, with the cloud-computing architecture, the power network topology using the set of PMU phasors; generating, with the cloud-computing architecture, a hybrid state estimation using the updated power network topology, the set of PMU phasors, and the SCADA state estimation; and transmitting the hybrid state estimation to a local control system.

A method for adjusting a multi-dimensional operating space of a wind turbine includes receiving, via a central multi-dimensional operating space controller, a plurality of signals from a plurality of requestors of modified operating space. Each of the plurality of signals includes a data structure having requested set points for a plurality of dimensions in the operating space. The method also includes tracking, via the central multi-dimensional operating space controller, current set points for the plurality of dimensions in the operating space. Further, the method includes dynamically determining, via the central multi-dimensional operating space controller, an output signal based on the requested set points, the output signal comprising one or more changes for the current set points for the plurality of dimensions in the operating space. Moreover, the method includes controlling the wind turbine based on the output signal so as to provide a modified multi-dimensional operating space.

A method and an apparatus for dynamically determining a yaw control precision. The method comprises: during a predetermined time period, collecting a plurality of wind speed data and a plurality of wind direction data, and processing the collected plurality of wind speed data and plurality of wind direction data; on the basis of the processed wind speed data and wind direction data, establishing a model of the corresponding relationship between wind speed, wind direction angle change, yaw control precision, yaw fatigue, and power loss; and, on the basis of the current wind speed data, wind direction data, predetermined yaw fatigue range, and predetermined power loss range, by means of the corresponding relationship model, determining the yaw control precision corresponding to the current wind speed and current wind direction angle change.

A system and a method for executing a work process on an object. The system includes at least one work station, an acquisition device, a control device and an auditor device.

A method of priming a minimum quantity lubrication (MQL) tool includes determining a category of the tool, supplying a short-prime MQL dosage if the tool is a first category or if both a second category and lubricated within a first predetermined timeframe, and supplying a long-prime MQL dosage if the tool is the second category and has not been lubricated within the predetermined timeframe. The category is based on internal passage complexity of the tool.

A machining system (10) comprising a machine comprising: real tool (12); actuators (14) for moving the real tool (12); sensors (15) for generating positioning data (16) for the real tool (12); a memory (17) for storing shape correction data (20) for the real tool (12); and a physical controller (18) for executing a machining program (19) and for controlling the actuators (14) as a function of the shape correction data (20), so as to move the real tool (12) relative to the real blank (13). On the basis of said data (22) representative of the positions of the real tool (12) and of the real blank (13), image display means (24) generate a reconstituted image (25) representative: of the shape of the real blank (13); and of the position of the real tool (12) at a given instant.

In a control method of a washing machine, a washing operation is performed through a heating washing process for a first set time and is performed through a non-heating washing process for a residual time, and, if the heating washing process is started, the rotation of a driving motor is weakly controlled until a washing water temperature reaches a primary target temperature, and is strongly controlled until the washing water temperature reaches a secondary target temperature after the washing water temperature reaches the primary target temperature, so that the washing water temperature is relatively gradually increased.

In an embodiment, an agricultural intelligence computing system stores a digital model of crop growth, the digital model of crop growth being configured to compute nutrient requirements in soil to produce particular yield values based, at least in part, on data unique to an agricultural field. The system receives agronomic field data for a particular agronomic field, the agronomic field data comprising one or more input parameters for each of a plurality of locations on the agronomic field, nutrient application values for each of the plurality of locations, and measured yield values for each of the plurality of locations. The system computes, for each location of the plurality of locations, a required nutrient value indicating a required amount of nutrient to produce the measured yield values. The system identifies a subset of the plurality of locations where the computed required nutrient value is greater than the nutrient application value. The system computes, for each of the subset of the plurality of locations, a residual value comprising a difference between the required nutrient value and the nutrient application value. The system generates a residual map comprising the residual values at the subset of the plurality of locations. Using the residual map and the one or more input parameters for each of the plurality of locations, the system generates and stores particular model correction data for the particular agronomic field.