WO2018092274A1 - Appareil de commande, procédé de commande et programme de commande - Google Patents

Appareil de commande, procédé de commande et programme de commande Download PDF

Info

Publication number
WO2018092274A1
WO2018092274A1 PCT/JP2016/084296 JP2016084296W WO2018092274A1 WO 2018092274 A1 WO2018092274 A1 WO 2018092274A1 JP 2016084296 W JP2016084296 W JP 2016084296W WO 2018092274 A1 WO2018092274 A1 WO 2018092274A1
Authority
WO
WIPO (PCT)
Prior art keywords
observation
value
control
information
control device
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/JP2016/084296
Other languages
English (en)
Japanese (ja)
Inventor
眞男 相見
松木　譲介
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Hitachi Ltd
Original Assignee
Hitachi Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Hitachi Ltd filed Critical Hitachi Ltd
Priority to JP2018550970A priority Critical patent/JP6778760B2/ja
Priority to PCT/JP2016/084296 priority patent/WO2018092274A1/fr
Publication of WO2018092274A1 publication Critical patent/WO2018092274A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B11/00—Automatic controllers
    • G05B11/01—Automatic controllers electric
    • G05B11/36—Automatic controllers electric with provision for obtaining particular characteristics, e.g. proportional, integral, differential
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04Q—SELECTING
    • H04Q9/00—Arrangements in telecontrol or telemetry systems for selectively calling a substation from a main station, in which substation desired apparatus is selected for applying a control signal thereto or for obtaining measured values therefrom

Definitions

  • the present invention relates to a control device, a control method, and a control program for controlling a controlled object.
  • Patent Document 1 discloses a sensor interface having several sensor inputs and several client inputs. Some client inputs can receive data requests from some clients, and some data requests are returned without identifying the specific physical sensor to be used when capturing a particular type of data. It includes at least one data request specifying a particular type of data to be performed.
  • the sensor interface also includes a processor that i) determines which sensor data can be used to satisfy some data requirements, and ii) extracts sensor data from several physical sensors. Some of the sensor inputs are configured to receive, and iii) if possible, configured to meet some data requirements using the received sensor data.
  • Patent Document 1 discloses a virtual sensor that abstracts an arbitrary type and number of physical sensors, and a client input device that is an interface with the virtual sensor.
  • Patent Document 1 cannot be applied to a device that does not have a physical sensor, and cannot handle non-sensor data. Since the Internet of Things (IoT) business uses relatively inexpensive devices, not all devices are designed to handle data from specific physical sensors.
  • IoT Internet of Things
  • data from non-sensors in the cloud can be combined with data from surrounding physical sensors, or data from surrounding physical sensors can be analyzed to improve accuracy and output as virtual data You may want to Such data output cannot be realized by the technique of Patent Document 1.
  • An object of the present invention is to provide a control parameter to a control object without depending on a device that detects the control parameter.
  • a control device, a control method, and a control program according to an aspect of the invention disclosed in the present application are a control device, a control method, and a control program that give a control parameter for controlling a control target to the control target,
  • a processor that executes a program; a storage device that stores the program; and a correspondence device that associates an adjustment amount of the control parameter with a value of analysis information that is a specific factor of the adjustment amount; and Communication that communicates with one or more physical sensors that observe observation values of observation information that are specific factors from the observation target, and communicates with a server that stores the values of the analysis information and the observation information at the positions of the one or more physical sensors
  • the processor includes a position of the control device among the one or more physical sensors.
  • a specifying process for specifying the adjustment amount of the control parameter corresponding to the value of the value from the correspondence information, and the adjustment amount specified by the specifying process is compensated based on a calculation result of the calculation process. And, and executes a correction process for outputting the correction result to the control target.
  • control parameter control amount can be given to the control object without depending on the device that detects the control parameter.
  • FIG. 1 is an explanatory diagram illustrating an example of control of a control target by a control parameter using a virtual sensor.
  • FIG. 2 is a block diagram illustrating a hardware configuration example of the control device.
  • FIG. 3 is an explanatory diagram of an example of the contents stored in the address character string storage table.
  • FIG. 4 is an explanatory diagram showing an example of the stored contents of the weather information storage table.
  • FIG. 5 is an explanatory diagram showing an example of the stored contents of the adjusted luminance storage table.
  • FIG. 6 is a block diagram of a functional configuration example of the control device according to the first embodiment.
  • FIG. 7 is a flowchart of a control processing procedure example performed by the control device according to the first embodiment.
  • FIG. 8 is a graph showing a change with time of the first observation value.
  • FIG. 9 is an explanatory diagram showing an example of the stored contents of the observation value storage table.
  • FIG. 10 is a block diagram of a functional configuration example of the control device according to the first embodiment.
  • FIG. 11 is a flowchart illustrating an example of a processing procedure for acquiring the first observation value.
  • FIG. 12 is an explanatory diagram of an example of acquiring the first observation value according to the third embodiment.
  • FIG. 13 is an explanatory diagram of an example of stored contents of the weighting table.
  • FIG. 14 is an explanatory diagram of an example of stored contents of the first observation value acquisition table.
  • FIG. 15 is a block diagram of a functional configuration example of the control device according to the first embodiment.
  • FIG. 16 is a flowchart illustrating an example of a processing procedure for acquiring the first observation value.
  • FIG. 1 is an explanatory diagram illustrating an example of control of a control target by a control parameter using a virtual sensor.
  • the control target is the display device 113 connected to the inside or outside of the control apparatus 101
  • the control parameter is the luminance of the display device 113
  • the external physical sensor is the temperature sensor 102.
  • the control apparatus 101 gives the display device 113 control parameters for controlling the display device 113 that is an example of a control target.
  • the control device 101 adjusts the luminance of the display device 113 without mounting a luminance sensor that detects the luminance around the control device 101. Instead, the control device 101 has a virtual sensor 111.
  • the virtual sensor 111 is a virtual sensor that collects the temperature observed by the temperature sensor 102 in the vicinity of the control device 101 to obtain a statistical value of the temperature, and obtains the temperature and the weather at the position of the control device 101 from the weather forecast site 103. Sensor device.
  • the control apparatus 101 adjusts the brightness
  • the luminance of the display device 113 can be adjusted without mounting a luminance sensor.
  • the control system is a system in which a control device 101, a temperature sensor 102, which is an example of a physical sensor, and a weather forecast site 103, which is an example of a server, are connected to be communicable via a network 104.
  • An example of the network 104 is a sensor network.
  • a sensor network is a network that connects sensor nodes that implement physical sensors, and that uses the ad hoc function of a sensor node and utilizes a relay routing function for sending data from another sensor node to a relay node. .
  • the sensor network has a function of ensuring data arrival at the relay node by autonomously reconstructing another relay route when a failure occurs in the relay communication between the sensor nodes.
  • a wireless communication network using a wireless access point may be used instead of the sensor network.
  • the wireless communication network is a network that transmits and receives TCP / IP packets.
  • the control device 101 controls the control target using data obtained from the virtual sensor 111.
  • the control device 101 may be a fixed device or a moving body.
  • the temperature sensor 102 is included in a communication terminal connected to a network. Further, the temperature sensor 102 may be directly connected to the network 104.
  • the temperature sensor 102 may be a fixed device or a moving body.
  • the server periodically acquires and holds the temperature and weather at a plurality of points.
  • the server is, for example, the weather forecast site 103.
  • the control device 101 acquires the position and temperature of the temperature sensor 102 from the temperature sensor 102 in the vicinity of the control device 101 by the virtual sensor 111.
  • the neighboring temperature sensor 102 is a physical sensor that exists statically or dynamically within an allowable range including the position of the control device 101.
  • the allowable range may be, for example, a range that does not change the temperature and the weather.
  • a physical sensor connected in a communication area of a wireless base station for example, a wifi spot
  • the control device 101 registers an entry 121 including the acquired position and temperature in the internal table 120.
  • the position field value may be the position a of any neighboring physical sensor as long as it is included in the area A.
  • the value of the date / time field may be the control processing time b.
  • the value of the temperature field may be a statistical value of temperature from a plurality of neighboring physical sensors (for example, an average value, a median value, a maximum value, or a minimum value).
  • the control device 101 transmits a request to the weather forecast site 103 by the virtual sensor 111.
  • the request includes the control processing time (for example, the latest acquisition date and time) and the position (latitude and longitude) of the control device 101.
  • the weather forecast site 103 accepts the request, the weather forecast site 103 returns to the virtual sensor 111 the temperature and weather within the allowable range including the position of the control device 101 in the time zone including the control processing time as a response.
  • the virtual sensor 111 registers the entry 122 including the position, time, acquired weather, and acquired temperature of the control device 101 in the internal table 120.
  • the control device 101 uses the virtual sensor 111 to average the temperature of the entry 122 (26.0 degrees in the example) and the temperature of the entry 121 (in the example, 28.0 degrees, 28.0 degrees, and 28.6 degrees).
  • control device 101 uses the virtual sensor 111 to specify the brightness adjustment amount corresponding to the weather “cloudy” in the entry 122 and correct the specified adjustment amount according to the difference D.
  • the control device 101 outputs a correction amount, which is an adjustment amount after correction, to the driver 112 to be controlled by the virtual sensor 111.
  • the driver 112 is software that controls a control target.
  • the control device 101 adjusts the brightness of the control target according to the adjustment amount from the driver 112.
  • the control parameter adjustment amount is given to the control object without depending on the sensor device (luminance sensor) that detects the control parameter.
  • the configuration in which the control device 101 includes the driver 112 and the control target has been described, but the driver 112 and the control target may be provided outside the control device 101.
  • the control apparatus 101 has been described with respect to a configuration that does not include a sensor device (luminance sensor).
  • the control device 101 is configured to use the sensor device and the virtual sensor 111 together, and the virtual sensor 111 is used when the sensor device is not used. It is good also as a structure to use.
  • FIG. 2 is a block diagram illustrating a hardware configuration example of the control device 101.
  • the control apparatus 101 includes a processor 201, a storage device 202, an input device 203, an output device 204, and a communication interface (communication IF 205).
  • the processor 201, the storage device 202, the input device 203, the output device 204, and the communication IF 205 are connected by a bus.
  • the processor 201 controls the control device 101.
  • the storage device 202 serves as a work area for the processor 201.
  • the storage device 202 is a non-temporary or temporary recording medium that stores various programs and data.
  • Examples of the storage device 202 include a ROM (Read Only Memory), a RAM (Random Access Memory), a HDD (Hard Disk Drive), and a flash memory.
  • the input device 203 inputs data. Examples of the input device 203 include a keyboard, a mouse, a touch panel, a numeric keypad, a scanner, a GPS receiver, and various sensors.
  • the output device 204 outputs data. Examples of the output device 204 include a display (a display device 113 to be controlled) and a printer.
  • the communication IF 205 is connected to the network 104 and transmits / receives data.
  • the data structure is described in a table format.
  • the data structure is not necessarily represented by a table, and may be represented by a data structure such as a list, a DB, a queue, or the like.
  • FIG. 3 is an explanatory diagram showing an example of the contents stored in the address character string storage table.
  • the address character string storage table 300 includes a website name 301 and an address character string 302 as fields.
  • the website name 301 is a field for storing a character string indicating the name of the website as a value.
  • the website name 301 is a primary key of the address character string storage table 300.
  • the address character string 302 is a field for storing a character string indicating a website address (for example, URL (Uniform Resource Locator)) as a value.
  • the address character string storage table 300 is stored, for example, in the storage device 202 shown in FIG.
  • FIG. 4 is an explanatory diagram showing an example of stored contents of a weather information storage table.
  • the weather information storage table 400 includes a position 401, a time 402, a weather 403, and a temperature 404 as fields. Each field corresponds to each field of the internal table 120 shown in FIG.
  • the position 401 is a field that stores, for example, the latitude and longitude of the observation point as values.
  • the time 402 is a field for storing the observation time as a value.
  • the interval between the values at time 402 is an observation interval. In this example, the observation interval is 1 hour. For example, when the value of the time 402 is “13:00”, the observation interval is 1 hour, so the time zone of the time 402 is “13:00 to 13:59”.
  • the weather 403 is a field that stores weather information indicating an atmospheric condition that affects the surface of the position 401 at time 402 as an analysis value of analysis information that is a specific factor of the control parameter adjustment amount, for example. For example, 15 types of weather information for general citizens determined by the Japan Meteorological Agency such as “clear” and “clear” are stored in the weather 403 as values.
  • the temperature 404 is a field that stores, for example, meteorological information indicating the temperature of the atmosphere at a position 401 at time 402 as an observation value of observation information observed by a physical sensor.
  • the weather information storage table 400 is stored in, for example, the storage device 202 shown in FIG.
  • FIG. 5 is an explanatory diagram showing an example of stored contents of the adjusted luminance storage table.
  • the adjustment luminance storage table 500 is correspondence information in which the adjustment amount of the control parameter is associated with the analysis value of the analysis information that is a specific factor of the adjustment amount.
  • the adjusted brightness storage table 500 includes weather 501 and adjusted brightness 502 as fields.
  • the weather 501 is a field for storing weather information as an analysis value of the analysis information.
  • the adjustment brightness 502 is a field that stores a brightness adjustment amount for the display device 113 that is an example of a control target as a value.
  • the adjusted luminance storage table 500 is stored in, for example, the storage device 202 shown in FIG.
  • FIG. 6 is a block diagram of a functional configuration example of the control device 101 according to the first embodiment.
  • the control device 101 includes an address character string storage table 300, a weather information storage table 400, an adjusted luminance storage table 500, a first acquisition unit 601, a second acquisition unit 602, a calculation unit 603, and a specification unit 604.
  • the first acquisition unit 601 to the control unit 606 are functions realized by causing the processor 201 to execute a program stored in the storage device illustrated in FIG.
  • the first acquisition unit 601 to the correction unit 605 are functions corresponding to the virtual sensor 111 illustrated in FIG. 1, and the control unit 606 is a function corresponding to the driver 112 illustrated in FIG.
  • the first acquisition unit 601 is a function realized by causing the processor 201 to execute the first acquisition process.
  • the first acquisition process includes observation information observed from a specific physical sensor located within an allowable range from the position of the control device 101 among one or more physical sensors at a control processing time when the specific physical sensor controls a control target. This is a process for acquiring the first observation value.
  • the physical sensor is, for example, the temperature sensor 102 outside the control device 101 shown in FIG.
  • the specific physical sensor is, for example, the temperature sensor 102 of the neighboring user shown in FIG.
  • the control processing time is, for example, the current time.
  • the control processing time may be a past time. In this case, the control processing time may be a preset time or a time given from the input device 203.
  • the first observation value of the observation information is an observation value from a specific physical sensor, for example, an observation value of the temperature sensor 102 of a neighboring user, and becomes a calculation source of the temperature of the entry 121 of the internal table 120 in FIG.
  • the processor 201 may calculate a statistical value for a plurality of observation values of the observation information observed by the plurality of specific physical sensors.
  • the statistical value may be, for example, a statistical value of air temperature (for example, an average value, a median value, a maximum value, or a minimum value) from a plurality of neighboring temperature sensors 102.
  • the second acquisition unit 602 is a function realized by causing the processor 201 to execute the second acquisition process.
  • the second acquisition process is a process of acquiring the second observation value of the observation information and the analysis value of the analysis information from the server at a position within the allowable range from the position of the control device 101 and including the control processing time. is there.
  • the server is, for example, the weather forecast site 103.
  • the period including the control processing time is a time zone including the control processing time. For example, when the observation interval is 1 hour and observation is performed at the timing of 0 minute, if the control processing time is 13:27, the period including the control processing time is a time zone of 13:00 to 13:59.
  • the second observation value of the observation information is an observation value from a specific physical sensor, for example, an observation value of the temperature sensor 102 of a neighboring user, and the entry 121 of the internal table 120 in FIG. It becomes the calculation source of temperature.
  • the first observation value and the second observation value are observation values that are different from each other by the neighboring temperature sensor 102 serving as an observation source.
  • the analysis information is the weather in the time zone including the control processing time stored in the weather forecast site 103, and the analysis value is a specifically specified value such as “sunny” or “cloudy”, for example.
  • the calculation unit 603 is a function realized by causing the processor 201 to execute calculation processing.
  • the calculation process calculates a difference D between the first observation value acquired by the first acquisition process and the second observation value acquired by the second acquisition process. Specifically, for example, in the calculation process, the processor 201 subtracts the second observation value from the first observation value.
  • the difference D is positive, it indicates that the temperature is higher than the observation of the weather forecast site 103, and when the difference D is negative, it indicates that the temperature is lower than the observation of the weather forecast site 103.
  • the processor 201 may calculate the difference between the above-described statistical value and the second observation value. Specifically, for example, as shown in FIG. 1, when 28.0 degrees, 28.0 degrees, and 28.6 degrees are observed by the three temperature sensors 102 of the neighboring users, respectively, 28.2 degrees is calculated.
  • the specifying unit 604 is a function realized by causing the processor 201 to execute a specific process.
  • the specifying process is a process of specifying the adjustment amount of the control parameter corresponding to the analysis value acquired by the second acquiring process from the correspondence information.
  • the processor 201 specifies the adjusted brightness value corresponding to the weather value acquired by the second acquiring process from the adjusted brightness storage table 500 that is the correspondence information. For example, if the value of the weather 501 is “cloudy”, the value “ ⁇ %” of the adjustment brightness 502 is specified.
  • the correction unit 605 is a function realized by causing the processor 201 to execute specific processing.
  • the correction process is a process of correcting the adjustment amount specified by the specifying process based on the calculation result of the calculation process and outputting the correction result to the control target.
  • the processor 201 multiplies the identified adjustment amount by the difference D that is the calculation result.
  • a preset correction coefficient may be multiplied. This multiplication result becomes the correction result.
  • the processor 201 outputs the correction result to the control target via the control unit 606.
  • the control unit 606 is a function realized by causing the processor 201 to execute control processing.
  • the control process is a process for controlling the control target using the correction result.
  • the processor 201 controls the control target according to the correction result.
  • the processor 201 performs control so that the luminance is increased if the correction result is a positive value. If the correction result is negative, the luminance may be controlled to be low. Further, the processor 201 may perform control so as not to adjust the luminance if the correction result is negative. Further, the processor 201 may perform control so as not to adjust the brightness if the weather information is “sunny” or more such as “sunny” or “sunny” regardless of whether the correction result is positive or negative.
  • the processor 201 is not limited to the luminance adjustment of the display device 113, and may make other specific adjustments of other devices. For example, in the case of brightness adjustment such as camera exposure and lens F-number, the processor 201 may perform control so that the smaller the correction result value, the brighter the brightness.
  • FIG. 7 is a flowchart of an example of a control processing procedure performed by the control device 101 according to the first embodiment.
  • the control device 101 waits for a control instruction (step S701: No). Specifically, for example, when the user of the control apparatus 101 inputs a control instruction, or when a preset time is reached, for example, when an observation value is acquired from the temperature sensor 102, the control instruction Is issued.
  • the control instruction includes the control processing time described above. In the subsequent processing, the control processing time is set to “current time”, which is the timing at which the control instruction is received.
  • the control device 101 acquires the position of the control device 101 at the control processing time by the GPS receiver (step S702).
  • control device 101 acquires the first observation value from the temperature sensor 102 of the neighboring user (step S703). If a plurality of first observation values are acquired, the processor 201 calculates a statistical value of the first observation value. The control device 101 transmits a request including the acquisition position of step S702 to the weather forecast site 103, and as a result, acquires an analysis result from the weather forecast site 103 and stores it in the weather information storage table 400 (step S704).
  • the control apparatus 101 specifies an entry including the acquisition position and the control processing time in step S702 from the weather information storage table 400 (step S705). In this case, the latest entry is specified. Then, the processor 201 calculates a difference D between the latest first observation value acquired in step S703 and the second observation value in the entry specified in step S705 (step S706). In addition, the processor 201 specifies an adjusted luminance value corresponding to the weather value of the specified entry from the adjusted luminance storage table 500 (step S707).
  • the processor 201 corrects the specified adjustment brightness with the difference D, and outputs the correction result to the control unit 606 (step S708). Finally, the processor 201 performs brightness adjustment of the display device 113 with the correction result (step S709). As a result, the control process ends.
  • the control parameter control amount (luminance adjustment amount in this example) can be given to the control object without depending on the device that detects the control parameter. Further, when there are a plurality of first observation values, the accuracy of the actual observation value at the position of the control device 101 is increased by calculating the statistical value. Therefore, the control amount of the control parameter can be optimized.
  • Example 2 is an example in which the accuracy of the first observation value is improved in Example 1.
  • the observation period for acquiring the first observation value may vary depending on the vendor and price even for the same type of sensor. If the observation period is short, there is not much problem, but if the observation period is large, there is a large difference between the time when the first observation value is acquired and the current time, and a correct observation value at the current time cannot be acquired. Therefore, in the second embodiment, the first observation value is stored in time series, and the first observation value at the current time is calculated based on the correlation of the past first time observation values.
  • control device 101 generates a regression line from the first time-series observed values so far, and predicts the first observed value at the timing of the control instruction using the regression line.
  • the first observation value is highly accurate, and more appropriate control can be performed on the control target.
  • FIG. 8 is a graph showing a change with time of the first observed value.
  • a black circle is an actual measurement value of the first observation value.
  • symbol 801 is the newest measured value of a 1st observed value.
  • a white circle is a predicted value 802 of the first observed value predicted from the regression line 800 by correlation from the first observed value in time series.
  • the observation interval of the actually measured values is 50 [ms].
  • FIG. 9 is an explanatory diagram showing an example of the stored contents of the observation value storage table.
  • the observation value storage table 900 is a table for storing time-series first observation values for each temperature sensor 102 of the neighboring user.
  • the observation value storage table 900 has time and observation values as fields.
  • the time is a field for storing the observation time of the first observation value that arrives at each observation interval as a value.
  • the observed value is a field for storing the first observed value observed at the time as a value.
  • FIG. 10 is a block diagram of a functional configuration example of the control device 101 according to the second embodiment.
  • the difference from FIG. 6 is that the observation value storage table 900 is provided, and the first acquisition unit 601 refers to the observation value storage table 900.
  • the processor 201 performs time series based on the correlation of the first series of observed values observed by a specific physical sensor (for example, the temperature sensor 102 of the neighboring user) before the control processing time. The first observation value next to the latest first observation value among the first observation values is calculated.
  • the processor 201 determines, for each specific physical sensor, the first time-series observation value that the specific physical sensor observes before the control processing time. Based on this correlation, the statistical value of the next first observation value may be calculated.
  • FIG. 11 is a flowchart illustrating an example of a processing procedure for acquiring the first observation value.
  • the process of FIG. 11 is a process corresponding to step S703 of FIG.
  • the predicted value of the first observed value is referred to as “interpolated observed value”.
  • the observation interval is called “sleep time”.
  • the control device 101 determines whether or not to end the first observation value acquisition process (step S1101). If not finished (step S1101: No), the control device 101 determines whether or not there is a request for acquiring an interpolation observation value (step S1102).
  • the acquisition request is, for example, a control instruction in step S701.
  • the control apparatus 101 determines whether the sleep time has elapsed (step S1103).
  • step S1103: NO If the sleep time has not elapsed (step S1103: NO), the process returns to step S1101.
  • step S1103: Yes the control device 101 acquires the first observation value from the temperature sensor 102 of the neighboring user and stores it in the observation value storage table 900 together with the current time (step S1104). Then, the control device 101 resets the sleep time and starts time counting again (step S1105), and returns to step S1101.
  • Step S1102 when there is an acquisition request (Step S1102: Yes), the control device 101 acquires the past first observation value in the observation value storage table 900 (Step S1106).
  • the control apparatus 101 calculates a correlation coefficient from the acquired past first observation value, and generates a regression line (step S1107).
  • the control device 101 specifies the interpolation observation value at the current time from the regression line 800 (step S1108), outputs the specified interpolation observation value to the calculation unit 603 (step S1109), and specifies the specified interpolation observation value and the current time.
  • the past interpolation observation values are updated according to the regression line 800 (step S1111), and the process returns to step S1101.
  • step S1101 when the acquisition process of the first observation value is terminated (step S1101: Yes), the process of this flowchart is terminated.
  • the control target can be appropriately adjusted by predicting the first observation value.
  • Example 3 is an example in which the accuracy of the first observation value is improved in Example 1 or Example 2. If there is a temperature sensor 102 with a long observation period among the temperature sensors 102 of neighboring users, a so-called outlier that is significantly different from the observation values of other temperature sensors 102 may be observed.
  • FIG. 12 is an explanatory diagram of an example of obtaining the first observation value according to the third embodiment.
  • the observation period of the temperature sensor 102 with sensor ID S1 is 30 [ms]
  • the observation period of the temperature sensor 102 with sensor ID S2 is 100 [ms]
  • the observation period of the temperature sensor 102 with sensor ID S3 is 10 [Ms].
  • the temperature sensor 102 with the sensor ID: S2 observes the first observation value that is an outlier.
  • the control apparatus 101 of Example 3 calculates
  • FIG. 13 is an explanatory diagram showing an example of the contents stored in the weighting table.
  • the weighting table 1300 has sensor IDs 1301 and weights 1302 as fields.
  • the sensor ID 1301 is a field that stores identification information (sensor ID) that uniquely identifies the temperature sensor 102 as a value.
  • the weight 1302 is a field for storing a weight value corresponding to the observation period of the temperature sensor 102 as a value.
  • the weight value decreases as the observation period increases.
  • the weight value w2 is smaller than other weight values. Thereby, the influence of the 1st observation value of the temperature sensor 102 with a long observation period can be reduced.
  • FIG. 14 is an explanatory diagram showing an example of the stored contents of the first observation value acquisition table.
  • the acquisition table 1400 includes a time 1401, an observed value 1402, and a sensor ID 1403 as fields.
  • the time 1401 is a field for storing the observation time of each temperature sensor 102 as a value.
  • the observed value 1402 is a field for storing the first observed value observed at time 1401 as a value.
  • the sensor ID 1403 is a field that stores identification information (sensor ID) that uniquely identifies the temperature sensor 102 as a value.
  • the first observation values are sequentially acquired from the acquisition table 1400 in units of the oldest four data.
  • the buffering including the first observation value of the sensor ID S2 is BF1 and BF5.
  • the processor 201 refers to the weighting table 1300 and calculates a statistical value.
  • BF1 V0A ⁇ w1 + V0B ⁇ w2 + V0C ⁇ w3 + V1C ⁇ w3
  • BF2 V2C ⁇ w3 + V3C ⁇ w3 + V3A ⁇ w1 + V4C ⁇ w3
  • BF3 V5C ⁇ w3 + V6C ⁇ w3 + V6A ⁇ w1 + V7C ⁇ w3
  • BF4 V8C ⁇ w3 + V9C ⁇ w3 + V9A ⁇ w1 + V10C ⁇ w3
  • BF5 V10B ⁇ w2 + V11C ⁇ w3 + V12C ⁇ w3 + V12A ⁇ w1
  • FIG. 15 is a block diagram of a functional configuration example of the control apparatus 101 according to the first embodiment. 10 differs from FIG. 10 in that it has a weighting table 1300, an observation value storage table 900, the first acquisition unit 601 refers to the observation value storage table 900, has an acquisition table 1400, and has a first acquisition. The unit 601 writes to and reads from the acquisition table 1400.
  • the processor 201 calculates a statistical value of the first observation value of each specific physical sensor based on the length of the observation interval of each specific physical sensor (for example, the temperature sensor 102 of the neighboring user). To do. Specifically, for example, the processor 201 calculates a weighted average value as a statistical value using a smaller weight value as the observation interval is longer.
  • the processor 201 when applied to the second embodiment, in the first acquisition process, performs a specific process based on the correlation of the first time-series observation values observed by a specific physical sensor before the control process time.
  • the next first observation value is calculated for each physical sensor, and the statistical value of the next first observation value calculated for each specific physical sensor is calculated based on the length of the observation interval of each specific physical sensor. .
  • the processor 201 determines from the past series of first observation values. A correlation coefficient is calculated, a regression line 800 is generated, and a predicted value (interpolated observed value) of the first observed value at time tc is obtained. In the first acquisition process, the processor 201 similarly refers to the weighting table 1300 to calculate the weighted average value even when the predicted value is calculated instead of the buffered observation value (actual measurement value). To do.
  • the actual measurement values are buffered as shown in FIG. 14 and used for the weighted average.
  • FIG. 16 is a flowchart illustrating an example of a processing procedure for acquiring the first observation value.
  • the process of FIG. 16 is a process corresponding to step S703 of FIG.
  • the control device 101 sets the current time as the starting time (step S1601).
  • step S1603 No
  • the control apparatus 101 determines whether there is data in the sensor queue (step S1604).
  • the sensor queue is a memory that temporarily holds data from the temperature sensor 102 (observation value, observation time, sensor ID).
  • step S1604 If there is no data in the sensor queue (step S1604: No), the process returns to step S1603. If there is data in the sensor queue (step S1604: Yes), the control apparatus 101 acquires data held in the sensor queue (step S1605), and assigns a weight value corresponding to the sensor ID in the acquired data to the weighting table 1300. (Step S1606). The identified data is written into the acquisition table 1400. Then, the process returns to step S1603. In step S1604, when the time obtained by subtracting the starting time from the current time is larger than the predetermined acquisition interval (step S1603: Yes), the control device 101 resets the weighted average value (step S1607), and the observed value group from the buffering area. Is read out (step S1608).
  • the buffering area is an area where the oldest data group (four in FIG. 14) in the acquisition table 1400 is buffered.
  • step S1609 the control apparatus 101 calculates a weighted average value about the read 1st observation value (step S1609). And the control apparatus 101 acquires the time zone information of the observation value group which calculated the weighted average value (step S1610).
  • the time zone information is the time of the acquisition table 1400 regarding the observation value group. The time to be adopted is determined in advance.
  • the control device 101 outputs the weighted average value and the time zone information as observation value information to the calculation unit 603 (step S1611), and clears the buffering area from which the observation value group has been acquired (step S1612). Then, the process returns to step S1602.
  • step S1602 when the acquisition process of the first observation value is finished (step S1602: Yes), the process of this flowchart is finished.
  • control object can be controlled more appropriately.
  • step S1610 the processor 201 calculates an interpolated observation value and calculates a weighted average value for a sensor that does not have an observation value at the current time. . Thereby, even when the observation value at the current time does not exist, the control target can be appropriately adjusted by predicting the observation value.
  • the present invention is not limited to the above-described embodiments, and includes various modifications and equivalent configurations within the scope of the appended claims.
  • the above-described embodiments have been described in detail for easy understanding of the present invention, and the present invention is not necessarily limited to those having all the configurations described.
  • a part of the configuration of one embodiment may be replaced with the configuration of another embodiment.
  • each of the above-described configurations, functions, processing units, processing means, and the like may be realized in hardware by designing a part or all of them with, for example, an integrated circuit, and the processor 201 performs each function. It may be realized by software by interpreting and executing the program to be realized.
  • Information such as programs, tables, and files for realizing each function is recorded on a memory, a hard disk, a storage device such as SSD (Solid State Drive), or an IC (Integrated Circuit) card, SD card, DVD (Digital Versatile Disc). It can be stored on a medium.
  • SSD Solid State Drive
  • IC Integrated Circuit
  • SD card Digital Card
  • DVD Digital Versatile Disc
  • control lines and information lines indicate what is considered necessary for the explanation, and do not necessarily indicate all control lines and information lines necessary for mounting. In practice, it can be considered that almost all the components are connected to each other.

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Selective Calling Equipment (AREA)
  • Feedback Control In General (AREA)
  • Telephonic Communication Services (AREA)

Abstract

L'invention concerne un appareil de commande, comprenant : un dispositif de stockage qui stocke des informations de correspondance associant une quantité de réglage d'un paramètre de commande à des fins de commande d'un objet à commander avec une valeur d'informations d'analyse qui devient un facteur de spécification pour la quantité de réglage ; et une interface de communication qui communique avec un capteur physique pour observer, à partir de l'objet à observer, une valeur d'observation d'informations d'observation qui devient un facteur de spécification pour les informations d'analyse, et qui communique également avec un serveur qui stocke les valeurs des informations d'analyse et des informations d'observation au niveau de la position du capteur physique. L'appareil de commande acquiert une première valeur d'observation des informations d'observation observées au moment d'un processus de commande lorsqu'un capteur physique spécifique commande l'objet à commander, à partir du capteur physique spécifique qui est situé dans une plage admissible à partir de la position de l'appareil de commande, acquiert, à partir du serveur, une valeur des informations d'analyse et une seconde valeur d'observation des informations d'observation à une position dans la plage admissible à partir de la position de l'appareil de commande pendant une période comprenant le temps de traitement de commande, calcule la différence entre la première valeur d'observation et la seconde valeur d'observation, spécifie, à partir des informations de correspondance, la valeur de réglage du paramètre de commande correspondant à la valeur des informations d'analyse, corrige la valeur de réglage spécifiée sur la base du résultat de calcul, et délivre le résultat de correction à l'objet à commander.
PCT/JP2016/084296 2016-11-18 2016-11-18 Appareil de commande, procédé de commande et programme de commande Ceased WO2018092274A1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
JP2018550970A JP6778760B2 (ja) 2016-11-18 2016-11-18 制御装置、制御方法、および制御プログラム
PCT/JP2016/084296 WO2018092274A1 (fr) 2016-11-18 2016-11-18 Appareil de commande, procédé de commande et programme de commande

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/JP2016/084296 WO2018092274A1 (fr) 2016-11-18 2016-11-18 Appareil de commande, procédé de commande et programme de commande

Publications (1)

Publication Number Publication Date
WO2018092274A1 true WO2018092274A1 (fr) 2018-05-24

Family

ID=62145396

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/JP2016/084296 Ceased WO2018092274A1 (fr) 2016-11-18 2016-11-18 Appareil de commande, procédé de commande et programme de commande

Country Status (2)

Country Link
JP (1) JP6778760B2 (fr)
WO (1) WO2018092274A1 (fr)

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2009533906A (ja) * 2006-04-07 2009-09-17 クゥアルコム・インコーポレイテッド センサーインタフェース並びにセンサーインタフェースに関連する方法および装置
JP2015103006A (ja) * 2013-11-25 2015-06-04 三菱日立パワーシステムズ株式会社 管理装置、管理システム、管理方法、及びプログラム

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2009533906A (ja) * 2006-04-07 2009-09-17 クゥアルコム・インコーポレイテッド センサーインタフェース並びにセンサーインタフェースに関連する方法および装置
JP2015103006A (ja) * 2013-11-25 2015-06-04 三菱日立パワーシステムズ株式会社 管理装置、管理システム、管理方法、及びプログラム

Also Published As

Publication number Publication date
JPWO2018092274A1 (ja) 2019-07-04
JP6778760B2 (ja) 2020-11-04

Similar Documents

Publication Publication Date Title
JP7577123B2 (ja) 測位方法、端末及びネットワーク機器
JP5508610B1 (ja) 情報処理装置、情報処理方法及び情報処理プログラム
JP4926752B2 (ja) 分散計測システムおよびその方法
JP2017096522A (ja) 断熱性能推定装置、及び、断熱性能推定方法
JP2022133391A (ja) 通信装置、サーバおよびプログラム
JP2017138262A (ja) 位置推定システム
JP2022081620A (ja) 電子装置、方法及びプログラム
JP2015222882A (ja) 通信スループット予測装置、通信スループット予測方法、及び、プログラム
US20150237122A1 (en) Peer-to-peer connection system with capability of peer-to-peer connection path routing, path routing method of peer-to-peer connection and computer application program thereof
JP6778760B2 (ja) 制御装置、制御方法、および制御プログラム
CN109194706B (zh) 网络资源拨测方法及终端
WO2018131311A1 (fr) Système de détection, dispositif de nœud de capteur, procédé de traitement de valeurs de mesure de capteur et programme
CN109561482B (zh) 一种数据获取方法、数据获取装置及智能终端
JP7516580B2 (ja) ビデオ分析システムおよびデータ配信方法
JP2017188756A (ja) 通信装置、遠隔制御システム、通信方法及びコンピュータプログラム
JP6326646B2 (ja) 減衰特性関数推定装置、減衰特性関数推定方法、及びプログラム
JP6382752B2 (ja) 遠隔制御システム、遠隔制御方法、分配装置、分配方法、制御装置、制御方法、分析装置、分析方法及びコンピュータプログラム
JP6378562B2 (ja) 情報処理装置及び情報処理方法
JP2019159635A (ja) 情報収集装置及びプログラム
JP7112885B2 (ja) 情報処理装置
US20200084570A1 (en) Method and device for synchronizing a parameter of a movable device
JP2022061071A (ja) 発電量予測装置、発電量予測システム、及び発電量予測方法
CN106445935B (zh) 点击数据的误判处理方法和装置
JP6572136B2 (ja) 通信システム、通信装置、第二装置、通信方法及びコンピュータプログラム
JP7740520B2 (ja) 情報処理装置、情報処理装置の方法、及びプログラム

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 16921718

Country of ref document: EP

Kind code of ref document: A1

ENP Entry into the national phase

Ref document number: 2018550970

Country of ref document: JP

Kind code of ref document: A

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 16921718

Country of ref document: EP

Kind code of ref document: A1