A standard track smart home system, comprising: a gateway device (1), a power interface of the gateway device (1) being respectively connected to a power supply live line (L) and a power supply zero line (N), the gateway device (1) remotely connecting to at least one user terminal, and the gateway device (1) being also used for connecting to a plurality of first expansion devices (10); and a standard track (T), the gateway device (1) and the plurality of first expansion devices (10) being arranged side by side on the standard track (T) and connected to one another by means of a plurality of wiring terminals, and outgoing interfaces of each of the first expansion devices (10) being respectively connected to one or more smart home devices.

The present invention provides a control device that executes model predictive control related to a predetermined control target corresponding to an actual target device which is an actual target of servo control in order to cause an output of the actual target device to track a predetermined command. The control device includes: an integrator which receives input of a deviation between the predetermined command and an output of the predetermined control target; and a model predictive control unit which has a prediction model that defines a correlation between a predetermined state variable and an input to the predetermined control target in a form of a predetermined state equation, and which performs model predictive control based on the prediction model according to a predetermined evaluation function in a prediction section having a predetermined time width using the output of the integrator as an input.

The present invention provides a control device that executes model predictive control related to a predetermined control target corresponding to an actual target device which is an actual target of servo control in order to cause an output of the actual target device to track a predetermined command. The control device includes: an integrator which receives input of a deviation between the predetermined command and an output of the predetermined control target; and a model predictive control unit which has a prediction model that defines a correlation between a predetermined state variable and an input to the predetermined control target in a form of a predetermined state equation, and which performs model predictive control based on the prediction model according to a predetermined evaluation function in a prediction section having a predetermined time width using the output of the integrator as an input.

Provided are a program file writing and running processing method, device and system. In an embodiment, the system includes a program file writing processing device, a cloud end processing device and a program file running processing device. The program file writing processing device converts a program file written in a specific format specified by a provider into a program node description model that can be described by a universal description language and is used to represent a reference relationship between nodes in the program file, and then stores same in the cloud end processing device for a program runner to download and run; moreover, during downloading and running by the program runner, the program file running processing device converts same into a program file executable by the program runner based on the reference relationship between nodes in the program node description model for execution by the program runner.

A computer-implemented method for planning an operation of a technical system within its environment. The method includes: obtaining state information comprising: a current domain, a time step and a current state; determining by heuristics costs for reachable states from the current state; selecting a heuristics by a policy out of a set of predefined heuristics depending on the state information and costs; choosing the state with the lowest cost returned by the selected heuristic from the reachable states, and determining an operation of the technical system out of the set of possible operation that has to be carried out by the technical system to reach said state with the lowest costreturned by the selected heuristic.

A dynamic environment (e.g., an automated industrial process) has multiple conditions in response to which corresponding actions are required, and comprises various equipment, control device(s) to control the equipment, and one or more sensors to generate input signal(s) representing a monitored condition of the environment. A control system for the environment comprises a master processor and one or more co-processors, wherein the master processor configures a given co-processor to evaluate only a first subset of conditions expected to occur in the environment within a specified time period (e.g., less than a response time of the master processor), and to provide first control information representing an action to be taken if a particular condition of the first subset is satisfied. The co-processor receives the input signal(s) representing the monitored condition, processes the input signal(s) so as to determine if the particular condition of the first subset is satisfied, and provides the first control information to the control devices so as to control the equipment. Exemplary applications include dynamic environments in which machine vision techniques and/or equipment are employed.

In a control apparatus allowing control programs and information programs to coexist, execution management data that indicates the upper limit of resources that are resources usable by the programs is enabled to be appropriately changed. The control apparatus downloads at least one of one or more object programs (one or more programs among one or more control programs and one or more information programs) from a program distribution apparatus via a network and one or more network ports. At timing different from the timing of the download, the control apparatus changes the execution management data that indicates the upper limit of resources that are resources usable by the object program in relation to a plurality of computing resources of the control apparatus. Each control program is a program that performs a scan operation of outputting control information on the control object apparatuses coupled to I/O ports. Each information program is a program that performs information processing different from the scan operation.

A SCADA Web HMI system includes a drawing generation device (1) and an HMI terminal device (32). A drawing editor (11) generates SVG data (21) and part runtime attribute data (22). The HMI terminal device (32) includes a Web browser (321) that reads SVG data (21) and displays an HMI screen, and an HMI Web runtime (322) that reads the part runtime attribute data (22) as setting parameters and operates on the Web browser (321). When receiving signal data corresponding to unique signal names from a monitoring target device (7), the HMI Web runtime (322) changes display of parts corresponding to the unique signal names on the HMI screen.

A SCADA Web HMI system includes a drawing generation device (1) and an HMI terminal device (32). A drawing editor (11) generates SVG data (21) and part runtime attribute data (22). The HMI terminal device (32) includes a Web browser (321) that reads SVG data (21) and displays an HMI screen, and an HMI Web runtime (322) that reads the part runtime attribute data (22) as setting parameters and operates on the Web browser (321). When receiving signal data corresponding to unique signal names from a monitoring target device (7), the HMI Web runtime (322) changes display of parts corresponding to the unique signal names on the HMI screen.

A cooling system for a datacenter is disclosed. The datacenter cooling system includes a refrigerant cooling loop to extract heat from a secondary cooling loop that is located within the datacenter or to provide supplemental cooling to one or more components of the datacenter that are coupled to the secondary cooling loop.