A method for the autonomous construction and/or design of at least one component part of a component includes the step of determining a state (s.sub.i) of the component part by a state module, wherein a state (s.sub.i) is defined by parameters (p.sub.i) such as data and/or measured values of at least one property (e.sub.i) of the component part. The state (s.sub.i) is transmitted to a reinforcement learning agent, which uses a reinforcement learning algorithm. A calculation function (ƒ.sub.i) and/or an action (a.sub.i) is selected on the basis of a policy for a state (s.sub.i) for the modification of at least one parameter (p.sub.i) by the reinforcement learning agent. A modeled value for the property (e.sub.i) is calculated using the modified parameter (p.sub.i). A new state (s.sub.i+1) is calculated by an environment module on the basis of the modeled value for the property (e.sub.i).

The present embodiments provide systems, processes and/or methods of controlling irrigation. In some embodiments, methods are provided that receive (4112) water usage information corresponding to a first volumetric water usage at a site location having an irrigation controller (130), wherein the first volumetric water usage corresponds to volumetric water usage from a beginning of a budget period of time to a first time within the budget period of time; determine (4114) automatically whether a volumetric water budget at the site location will be met for the budget period of time based on at least the first volumetric water usage, the volumetric water budget corresponding to a specified volume of water for use during the budget period of time; determine (4116) automatically, in the event the volumetric water budget will not be met, an adjustment to the irrigation by the irrigation controller; and output (4118) signaling to effect the adjustment.

Example implementations relate to a display and strap with sensors. In some examples, an apparatus may comprise a strap, a pressure sensor coupled to the strap, and a display coupled to the strap. In some examples, the apparatus may include a tensioner mechanism coupled to the strap and a motor coupled to the tensioner mechanism. The motor may actuate the tensioner mechanism to adjust the strap to a particular amount of tension, and the particular amount of tension may be based on an amount of pressure detected by the pressure sensor.

An atherectomy system includes a drive mechanism that is adapted to rotatably actuate an atherectomy burr and a controller that is adapted to regulate operation of the drive mechanism. In some cases, the drive mechanism includes a drive cable that is coupled with the atherectomy burr and a drive motor that is adapted to rotate the drive cable. The controller is adapted to receive an indication of an increase in torque experienced at the atherectomy burr and is further adapted to, in response, regulate operation of the drive mechanism such that the increase in torque results in a noticeable reduction in speed of the drive mechanism such that a user of the atherectomy system notices the reduction in speed and is alerted to the increase in torque.

An acquisition unit (11) acquires an explanatory variable that is to be input to a model (37) configured to output an objective variable for the explanatory variable, a specification unit (12) associates a frequency at which an explanatory variable included in each of a plurality of areas, which are obtained by dividing an explanatory variable space, is acquired by the acquisition unit (11) with each of the plurality of areas, and specifies an area to which an explanatory variable included in learning data used to learn the model (37) belongs and in which a frequency of an explanatory variable acquired by the acquisition unit (11) is a predetermined value or less, and an update unit (14) updates the model (37) in such a manner that learning data including an explanatory variable belonging to an area specified by the specification unit (12) is forgotten.

A system that maintains power consumption of a network to a predefined limit. A plurality of elements such as components, nodes and modules may be connected in a daisy chain configuration. Power may be inserted to one or more of the elements which may proceed down the chain to be consumed by the one or more elements. However, there a limit as to the total amount of energy that may be consumed at the same time. Thus, power to the elements may be scheduled so that the limit is not exceeded by at any one time. At the same time, communications may proceed through that chain from element to element. An example of the present system may be a power over a network (PoE).

This motor control device receives a speed command from an upper layer system control device having a position controller, the motor control device having: a position command estimator that calculates an estimate of a position command on the basis of the speed command and a motor axis position response; and a speed command generator that generates an actual speed command on the basis of the estimate so that an end section of a machine connected to the motor does not oscillate, wherein the actual speed command is output from the speed command generator to a speed controller.

Disclosed are a roll-to-roll machining control decision generation method and apparatus for a flexible material. The method comprises: acquiring first vibration data of a first unwinding module, second vibration data of a second unwinding module, third vibration data of a pressing module, fourth vibration data of a winding module, and rotating speed data and winding tension data of the winding module; calculating to obtain a plurality of health state level combinations according to preset health state levels, the first vibration data, the second vibration data, the third vibration data and the fourth vibration data; generating a winding module rotating speed interval and a winding tension value interval of each health state level combination based on the rotating speed data and the winding tension data; and generating an adjustment decision by using the plurality of health state level combinations, the winding module rotating speed interval and the winding tension value interval.

An optimization device includes: a plurality of search parts; and a controller that controls the plurality of search parts, wherein, each of the plurality of search parts includes a state holding part configured to hold each of values of a plurality of state variables included in an evaluation function representing an energy value, an energy calculation part configured to calculate a change value of the energy value generated in a case where any one of the values of the plurality of state variables is changed, and a transition controller configured to stochastically determine whether or not to accept a state transition by a relative relation between the change value of the energy value and thermal excitation energy, based on a set temperature value, the change value, and a random number value.

A multi-layer architecture for control of distributed energy resources (DER) includes a forecasting and optimization system and one or more site-level controllers. The forecasting and optimization system generates predictions of optimal set points and communicate the optimal set points to a site-level controller. The site-level controller includes stored instructions that, when executed, direct the site-level controller to perform a boundary check and a real-time static economic dispatch, which can include steps of receiving optimal set points from the forecasting and optimization system; comparing received optimal set points with local conditions; outputting dispatch commands for DER control according to the optimal set points when the optimal set points are within appropriate limits with respect to the local conditions; and when the optimal set points exceed the appropriate limits, generating adjusted dispatch commands and outputting the adjusted dispatch commands for the DER control.