Abstract: A system for proactively controlling rimpull limit of a machine includes a hydraulic system having a lift cylinder to move an implement; a lift cylinder pressure sensor that senses a hydraulic pressure of the lift cylinder and responsively produces a lift cylinder pressure signal; and a controller in operable communication with the power train and the lift cylinder pressure sensor. The controller is configured to receive the lift cylinder pressure signal; determine the rimpull limit based at least in part upon the lift cylinder pressure signal; and adjust the torque of the power train to the rimpull limit.

Abstract: A system for proactively controlling rimpull limit of a machine includes a hydraulic system having a lift cylinder to move an implement; a lift cylinder pressure sensor that senses a hydraulic pressure of the lift cylinder and responsively produces a lift cylinder pressure signal; and a controller in operable communication with the power train and the lift cylinder pressure sensor. The controller is configured to receive the lift cylinder pressure signal; determine the rimpull limit based at least in part upon the lift cylinder pressure signal; and adjust the torque of the power train to the rimpull limit.

Abstract: Operating a machine including a continuously variable transmission (CVT) includes operating an engine of the machine at a lower engine speed, receiving data indicative of an expected increase in load on the engine, and commanding increasing the engine speed responsive to the data. The engine is operated at a higher engine speed responsive to the commanded increase, with the operation at the higher engine speed being initiated proactively so as to limit retarding a ground speed of the machine. Related control logic and machine structure is also disclosed.

Abstract: Operating a machine including a continuously variable transmission (CVT) includes operating an engine of the machine at a lower engine speed, receiving data indicative of an expected increase in load on the engine, and commanding increasing the engine speed responsive to the data. The engine is operated at a higher engine speed responsive to the commanded increase, with the operation at the higher engine speed being initiated proactively so as to limit retarding a ground speed of the machine. Related control logic and machine structure is also disclosed.

Abstract: Using machine learning to predict behavior based on local conditions. In one example embodiment, a method for using machine learning to predict behavior based on local conditions may include identifying a lead, identifying a target behavior for the lead, identifying a locality associated with the lead, identifying a current local condition of the locality, and employing a machine learning classifier to generate a prediction of a likelihood of the lead exhibiting the target behavior. In this example embodiment, the machine learning classifier may base the prediction on the target behavior, the locality, and the current local condition.

Abstract: Using machine learning to predict performance of an individual in a role based on characteristics of the individual. In one example embodiment, a method for using machine learning to predict performance of an individual in a role based on characteristics of the individual may include identifying the role, identifying the individual, identifying a target performance metric for the role, identifying the characteristics of the individual, and applying a machine learning classifier to generate a prediction of the individual achieving the target performance metric in the role. In this example embodiment, the machine learning classifier may base the prediction on the characteristics of the individual.

Abstract: Using machine learning to predict behavior based on local conditions. In one example embodiment, a method for using machine learning to predict behavior based on local conditions may include identifying a lead, identifying a target behavior for the lead, identifying a locality associated with the lead, identifying a current local condition of the locality, and employing a machine learning classifier to generate a prediction of a likelihood of the lead exhibiting the target behavior. In this example embodiment, the machine learning classifier may base the prediction on the target behavior, the locality, and the current local condition.

Abstract: An automated bucket loading control method includes determining a bucket tilt parameter for a bucket of the machine which corresponds with a partial bucket load, and capturing a partial bucket load by controllably tilting the bucket in a pile of material according to the determined bucket tilt parameter. A control system includes a sensor configured to monitor a bucket tilt parameter and output a bucket tilt signal, and further includes an electronic payload controller coupled with the sensor which is configured to output bucket tilting control commands. The electronic payload controller is further configured to determine a value for the bucket tilt parameter that corresponds with a target partial bucket load and output corresponding bucket tilting control commands during moving a bucket of the machine in a material pile to capture a partial bucket load.

Abstract: A method of loading a truck with material using a loader includes a step of determining a target load for a final pass. Material is loaded into a bucket of the loader in excess of the target load. Excess material is dumped from the bucket back to the pile in a controlled manner to arrive at a target load of reposed material in the bucket. The target load amount of the material in the bucket, which is less than a total amount of material originally loaded in the bucket is dumped into the truck by pitching the bucket. The bucket may be pitched to a determined pitch angle that is based upon the target load using an appropriate material curve stored on the loader. The pitch control algorithm can be calibrated by sensing the reposed weight of material in the bucket, and comparing that to an expected reposed weight, and then updating one of the material curves if there is a deviation.

Abstract: An automatic loading control system for loading a work implement of a work machine with material from a pile may include a lift sensor configured to monitor a lift actuator and communicate a lift signal. The system may also include a tilt sensor configured to monitor a tilt actuator and communicate a tilt signal. A speed sensor may be configured to communicate a speed signal indicative of a speed of the work machine. A control module may be configured to receive the lift signal, the tilt signal, and the speed signal and generate a signal to control a rim-pull based on at least one of a lift velocity of the lift actuator, a tilt velocity of the tilt actuator, and a work machine velocity to facilitate movement of the work implement through the pile.

Abstract: The present invention provides an assembly that includes a print head and a power conditioning circuit in a common frame. The co-location of the print head and power conditioning circuit in the frame alleviates added signal noise and power dissipation. Further, it allows for efficient temperature regulation of the two print head and power conditioning circuit.

Abstract: A thermal printer apparatus has a plurality of print stations for recording image information onto a receiver moving past the print stations. An adjustable-speed receiver drive mechanism is adapted to advance the receiver along the path. A plurality of sensors adapted to detect the temperature of the receiver and other surfaces along the path. A controller adjusts the speed of the drive mechanism as a function of the detected temperatures so as to effect a shim of the average raster line pitch of the printer to compensate for changes in the temperature of the receiver. An empirical model of receiver speed as a function of measured receiver temperature is used in software to predict receiver speed during printing.