SYSTEM, DEVICE AND METHOD FOR MANAGING AND OPTIMIZING CONNECTION BETWEEN FIELD DEVICES AND AUTOMATION DEVICES

Abstract

A system, device, and method for managing connections in an industrial installation are described. The system includes one or more field devices, one or more automation devices, and a self-configurable device. The self-configurable device is adapted to dynamically configure, based on type of the one or more field devices and the one or more automation devices, such that the self-configurable device manages a connection between the one or more field devices and the one or more automation devices. The self-configurable device is adapted to calibrate one or more field devices and manage automation functions in the industrial installation.

Claims

1. An automation system comprising: one or more field devices; one or more automation devices; and a self-configurable device configured to dynamically configure based on type of the one or more field devices and the one or more automation devices such that the self-configurable device manages a connection between the one or more field devices and the one or more automation devices, wherein the self-configurable device comprises a calibration module, wherein the calibration module is configured to: obtain a baseline state-space representation of the automation system, wherein the baseline state-space representation comprises a model of a set of at least one input variable, at least one output variable, and at least one state variable of the automation system corresponding to an optimum functioning of the automation system; determine a real-time state-space representation of the automation system, wherein the real-time state-space representation comprises a model of a set of at least one input variable, at least one output variable, and at least one state variable corresponding to a real-time functioning of the automation system; compare the baseline state-space representation with the real-time state-space representation to identify a deviation; and modify the baseline state-space representation based on the real-time state-space representation when the a deviation is identified.

2. The automation system of claim 1, wherein the self-configurable device comprises: at least one first port configured to connect the one or more field devices; at least one second port configured to connect the one or more automation devices; a processing unit; and a memory coupled to the processing unit.

3. The automation system of claim 2, wherein the memory of the self-configurable device comprises a self-configuration module, wherein the self-configuration module is configured to: identify the one or more field devices installed in an industrial installation; identify the one or more automation devices installed in the industrial installation; and establish a connection between the one or more field devices and the one or more automation devices in the industrial installation.

4. The automation system of claim 3, wherein the self-configuration module is configured to: determine a network configuration associated with the industrial installation; identify at least one attribute associable with the one or more field devices; identify at least one attribute associable with the one or more automation devices; and determine an association between the one or more field devices and the one or more automation devices based on the at least one attribute associable with the one or more field devices, the at least one attribute associable with the one or more automation devices, and the network configuration associated with the industrial installation.

5. The automation system of claim 4, wherein the self-configuration module is further configured to: receive a set of configuration settings based on the identified one or more field devices and the one or more automation devices from a server, wherein the set of configuration settings comprises one or more parameters for configuring the self-configurable device; and configure the self-configurable device using the set of configuration settings such that the self-configurable device dynamically establishes an active communication channel between the one or more field devices with the one or more automation devices.

6. The automation system of claim 5, wherein the memory of the self-configurable device further comprises a calibration module configured to automatically calibrate the automation system.

7. A method of managing a connection between one or more field devices and one or more automation devices in an industrial automation, the method comprising: identifying the one or more field devices; identifying the one or more automation devices; and establishing a connection between the one or more field devices and the one or more automation devices in the industrial installation.

8. The method of claim 7, wherein establishing the connection between the one or more field devices and the one or more automation devices comprises: determining a network configuration associated with the industrial installation; identifying at least one attribute associable with the one or more field devices; identifying at least one attribute associable with the one or more automation devices; and determining an association between the one or more field devices and the one or more automation devices based on the at least one attribute associable with the one or more field devices, the at least one attribute associable with the one or more automation devices, and the network configuration associated with the industrial installation.

9. The method of claim 8, further comprising: receiving a set of configuration settings based on the identified one or more field devices and the one or more automation devices from a server, wherein the set of configuration settings comprises one or more parameters for configuring a self-configurable device; and configuring the self-configurable device using the set of configuration settings such that the self-configurable device dynamically establishes an active communication channel between the one or more field devices with the one or more automation devices.

10. The method of claim 7, further comprising automatically calibrating an automation system.

11. The method of claim 10, wherein automatically calibrating the automation system comprises: obtaining a baseline state-space representation of the automation system, wherein the baseline state-space representation comprises a model of a set of at least one input variable, at least one output variable, and at least one state variable of the automation system corresponding to an optimum functioning of the automation system; determining a real-time state-space representation of the automation system, wherein the real-time state-space representation comprises a model of a set of at least one input variable, at least one output variable, and at least one state variable corresponding to a real-time functioning of the automation system; identifying a deviation, identifying the deviation comprising comparing the baseline state-space representation with the real-time state-space representation; and modifying the baseline state-space representation based on the real-time state-space representation when the deviation is identified.

12. In a non-transitory computer-readable storage medium that stores machine readable instructions executable by a processing unit to manage a connection between one or more field devices and one or more automation devices in an industrial installation, the machine readable instructions comprising: identifying the one or more field devices; identifying the one or more automation devices; and establishing a connection between the one or more field devices and the one or more automation devices in the industrial installation.

13. The non-transitory computer-readable storage medium of claim 12, wherein establishing the connection between the one or more field devices and the one or more automation devices comprises: determining a network configuration associated with the industrial installation; identifying at least one attribute associable with the one or more field devices; identifying at least one attribute associable with the one or more automation devices; and determining an association between the one or more field devices and the one or more automation devices based on the at least one attribute associable with the one or more field devices, the at least one attribute associable with the one or more automation devices, and the network configuration associated with the industrial installation.

14. The non-transitory computer-readable storage medium of claim 12, wherein the machine readable instructions further comprise: receiving a set of configuration settings based on the identified one or more field devices and the one or more automation devices from a server, wherein the set of configuration settings comprises one or more parameters for configuring a self-configurable device; and configuring the self-configurable device using the set of configuration settings such that the self-configurable device dynamically establishes an active communication channel between the one or more field devices with the one or more automation devices.

15. The non-transitory computer-readable storage medium of claim 12, wherein the machine readable instructions further comprise automatically calibrating an automation system.

16. The non-transitory computer-readable storage medium of claim 12, wherein automatically calibrating the automation system comprises: obtaining a baseline state-space representation of the automation system, wherein the baseline state-space representation comprises a model of a set of at least one input variable, at least one output variable, and at least one state variable of the automation system corresponding to an optimum functioning of the automation system; determining a real-time state-space representation of the automation system, wherein the real-time state-space representation comprises a model of a set of at least one input variable, at least one output variable, and at least one state variable corresponding to a real-time functioning of the automation system; identifying a deviation, identifying the deviation comprising comparing the baseline state-space representation with the real-time state-space representation; and modifying the baseline state-space representation based on the real-time state-space representation when the deviation is identified.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The present disclosure is further described hereinafter with reference to illustrated embodiments shown in the accompanying drawings, in which:

[0028] FIG. 1A is a schematic representation of an automation system, according to a first embodiment.

[0029] FIG. 1B is a schematic representation of the automation system, according to a second embodiment.

[0030] FIG. 2 illustrates block diagram of a self-configurable device, according to an embodiment.

[0031] FIG. 3 illustrates a flowchart of a method of managing a connection between one or more field devices and one or more automation devices, according to an embodiment.

[0032] FIG. 4 illustrates a flowchart of a method of establishing a connection between one or more field devices and one or more automation devices, according to an embodiment.

[0033] FIG. 5 illustrates a flowchart of a method of configuring the self-configurable device, according to an embodiment.

[0034] FIG. 6 illustrates a schematic representation of a section of industrial installation.

[0035] FIG. 7 illustrates a flowchart of a method of automatically calibrating the automation system, according to an embodiment.

[0036] FIG. 8 is a high-level schematic representation of an automation system in an industrial installation, according to a first embodiment.

DETAILED DESCRIPTION

[0037] Hereinafter, embodiments for carrying out the present disclosure are described in detail. The various embodiments are described with reference to the drawings, where like reference numerals are used to refer to like elements throughout. In the following description, for purpose of explanation, numerous specific details are set forth in order to provide a thorough understanding of one or more embodiments. It may be evident that such embodiments may be practiced without these specific details.

[0038] FIG. 1A is a schematic representation of an industrial installation 100, according to a first embodiment. The industrial installation 100 may be an industrial setup such as manufacturing facility, power plant, etc. The industrial installation 100 includes an automation system 107. The automation system 107 includes a self-configurable device 101. The self-configurable device 101 is connected to one or more field devices 102A-N (e.g., equipment, machines, sensors, actuators, etc.) and one or more automation devices 103. Such connection may be wired or wireless. The self-configurable device 101 includes a self-configuration module 110, a calibration module 112, and a network interface 114. The self-configurable device 101 is capable of communicating with the one or more field devices 102A-N and the one or more automation devices 103 through the Internet or a network. The automation system 107 further includes a human machine interface (HMI) device 104 connected to the one or more automation device 103. The component 104 may also be, for example, an engineering server, operator station, connectivity server, OPC server, etc. The self-configurable device 101 is capable of communicating with the one or more automation devices 103 using the network interface 114 and a communication link 116A via the Internet or a network. The HMI device 104 is capable of communicating with the self-configurable device 101 using a communication link 116C. FIG. 1B is a schematic representation of an industrial installation 100, according to a second embodiment. In the second embodiment, the self-configurable device 101 may be connected to a cloud platform 105. The self-configurable device 101 is capable of communicating with the cloud platform 105 using the network interface 114 via communication link 116B. The communication links 116A to 116B may be wired or wireless links.

[0039] The self-configurable device 101 and the automation device 103 may have an operating system and at least one software program for performing desired operations in the industrial installation 100. Also, the field devices 102A-N may run software applications for collecting, and pre-processing plant data (process data) and transmitting the pre-processed data to the self-configurable device 101 and/or to the cloud platform 105.

[0040] The cloud platform 105 may be a cloud infrastructure capable of providing cloud-based services such as data storage services, data analytics services, data visualization services, etc. based on the plant data. The cloud platform 105 may be part of public cloud or a private cloud. The cloud platform 105 may enable data scientists/software vendors to provide software applications/firmware as a service, thereby eliminating a need for software maintenance, upgrading, and backup by the users. The software application may be a full application or a software patch.

[0041] The self-configurable device 101 is further illustrated in greater detail in FIG. 2. Referring to FIG. 2, the self-configurable device 101 includes a processing unit 201, a memory 202, a storage unit 203, a network interface 114, a standard interface, or bus 207. The self-configurable device 101 may be an exemplary embodiment of a system. The system 101 may be a computer (e.g., personal computer), a workstation, a virtual machine running on host hardware, a microcontroller, or an integrated circuit. As an alternative, the system 101 may be a real or a virtual group of computers (the technical term for a real group of computers is “cluster”, the technical term for a virtual group of computers is “cloud”).

[0042] The processing unit 201, as used herein, may be any type of computational circuit, such as, but not limited to, a microprocessor, microcontroller, complex instruction set computing microprocessor, reduced instruction set computing microprocessor, very long instruction word microprocessor, explicitly parallel instruction computing microprocessor, digital signal processor, or any other type of processing circuit. The processing unit 201 may also include embedded controllers, such as generic or programmable logic devices or arrays, application specific integrated circuits, single-chip computers, and the like. In general, a processing unit 201 may include hardware elements and software elements. The processing unit 201 may be configured for multithreading (e.g., the processing unit 201 may host different calculation processes at the same time), executing either in parallel, or switching between active and passive calculation processes.

[0043] The memory 202 may be volatile memory and non-volatile memory. The memory 202 may be coupled for communication with the processing unit 201. The processing unit 201 may execute instructions and/or code stored in the memory 202. A variety of computer-readable storage media may be stored in and accessed from the memory 202. The memory 202 may include any suitable elements for storing data and machine-readable instructions, such as read only memory, random access memory, erasable programmable read only memory, electrically erasable programmable read only memory, a hard drive, a removable media drive for handling compact disks, digital video disks, diskettes, magnetic tape cartridges, memory cards, and the like. In the present embodiment, the memory 202 includes a self-configuration module 110 stored in the form of machine-readable instructions on any of the above-mentioned storage media and may be in communication to and executed by processing unit 201. When executed by the processing unit 201, the self-configuration module 110 causes the processing unit 201 to dynamically manage connections between one or more field devices 102A-N and one or more automation devices 103. The memory 202 also includes a calibration module 112 that, when executed by the processing unit 201, causes the processing unit 201 to calibrate one or more field devices. Method acts executed by the processing unit 201 to achieve the abovementioned functionality are elaborated upon in detail in FIGS. 3, 4, 5, 6, and 7.

[0044] The storage unit 203 may be a non-transitory storage medium that stores a technical database 204. The technical database 204 may store an event history of the one or more field devices 102A-N and the one or more automation devices 103 in the industrial installation 100. The storage unit 203 also includes signal tables and control schemas based on distributed automation function. Additionally, the technical database 204 may also include baseline and real-time state-space representations of the automation system 107. The input device is capable of receiving input signal from one or more field devices. The bus 207 acts as interconnect between the processing unit 201, the memory 202, the storage unit 203, the input unit 205, the output unit 206, and the network interface 114.

[0045] Those of ordinary skill in the art will appreciate that the hardware depicted in FIG. 2 may vary for particular implementations. For example, other peripheral devices such as an optical disk drive and the like, Local Area Network (LAN)/Wide Area Network (WAN)/Wireless (e.g., Wi-Fi) adapter, graphics adapter, disk controller, input/output (I/O) adapter also may be used in addition or in place of the hardware depicted. The depicted example is provided for the purpose of explanation only and is not meant to imply architectural limitations with respect to the present disclosure.

[0046] A system in accordance with an embodiment of the present disclosure includes an operating system employing a graphical user interface. The operating system permits multiple display windows to be presented in the graphical user interface simultaneously with each display window providing an interface to a different application or to a different instance of the same application. A cursor in the graphical user interface may be manipulated by a user through the pointing device. The position of the cursor may be changed, and/or an event such as clicking a mouse button may be generated to actuate a desired response.

[0047] One of various commercial operating systems, such as a version of Microsoft Windows™, a product of Microsoft Corporation located in Redmond, Wash., may be employed if suitably modified. The operating system is modified or created in accordance with the present disclosure as described.

[0048] The present disclosure is not limited to a particular computer system platform, processing unit, operating system, or network. One or more aspects of the present disclosure may be distributed among one or more computer systems (e.g., servers configured to provide one or more services to one or more client computers, or to perform a complete task in a distributed system). For example, one or more aspects of the present disclosure may be performed on a client-server system that includes components distributed among one or more server systems that perform multiple functions according to various embodiments. These components include, for example, executable, intermediate, or interpreted code, which communicate over a network using a communication protocol. The present disclosure is not limited to be executable on any particular system or group of systems, and is not limited to any particular distributed architecture, network, or communication protocol.

[0049] Disclosed embodiments provide systems, devices, and methods for dynamically managing a connection between one or more field devices and one or more automation devices in an automation system.

[0050] FIG. 3 illustrates a flowchart of a method 300 of managing a connection between one or more field devices 102A-N and one or more automation devices 103, in the industrial installation 100. The method includes act 301 of identifying one or more field devices 102A-N in the industrial installation 100. One or more field devices 102A-N may be deployed in the industrial installation 100 and are configured to capture one or more parameters associated with the functioning of the industrial installation 100. The field devices 102A-N may include, for example, actuators, sensors, pneumatic devices, transmitters, switches, etc. At act 302, the method 300 includes identifying one or more automation devices 103 in the industrial installation 100. The one or more automation devices 103 may include, for example, programmable logic controllers, HMI devices, etc. Such identification of one or more field devices 102A-N and one or more automation devices 103 may be performed based on one or more signals from the one or more field devices 102A-N and the one or more automation devices 103. At act 303, the method includes establishing a connection between the one or more field devices 102A-N and the one or more automation devices 103. The method acts describing the establishment of connection between the one or more field devices 102A-N and the one or more automation devices 103 are explained in detail under FIG. 4.

[0051] Referring to FIG. 4, the method 400 includes act 401 of determining a network configuration associated with the industrial installation 100. The network configuration of the industrial installation 100 may include, for example, PROFINET parameters for the operating conditions of the industrial installation. The network configuration enables identification of sources of origin of signal(s) in the industrial installation 100. The signal sources may be, for example, the one or more field devices 102A-N. The network configuration also enables identification of destination/target devices for the generated signals. Each signal originating from a field device 102A-N may be transmitted to a target device in the industrial installation 100. Such target device may be, for example, one or more automation devices 103. The network configuration further enables identification of functional data associated with the industrial installation. The method 400 further includes act 402 of identifying at least one attribute associable with the one or more field devices 102A-N. Such attribute may be, for example, data associated with device configuration such as, but not limited to, device type, device description, field device technology (FDT) configuration, etc. At act 403, at least one attribute associable with the one or more automation devices 103 is identified. Such attribute may be, for example, device description of the automation devices 103, network parameters associated with the automation devices 103, etc. At act 404, an association between the one or more field devices 102A-N and the one or more automation devices 103 is determined based on the identified one or more attributes associable with the one or more field devices 102A-N and the one or more automation devices 103. In an embodiment, a mapping of the signal source, signal destination(s), and device specific information may be performed to determine the association between the one or more field devices 102A-N and the one or more automation devices 103. Such device specific information may be obtained from engineering configuration of the automation system 107. Additionally, the mapping may also include communication signals, archiving data, etc. In a further embodiment, on determination of the association, the one or more field devices 102A-N and the one or more automation devices 103 may be connected. Such establishment of connection between the one or more field devices 102A-N and the one or more automation devices 103 is achieved through the self-configurable device 101. In yet another embodiment, logical source and destination signal tables may be generated. Based on such table, one or more signals may be routed to a target automation device 103 when a corresponding event may be triggered or when a dead-band is exceeded.

[0052] FIG. 5 provides an illustration of a flowchart of a method 500 of configuring a self-configurable device 101, according to an embodiment. At act 501, a set of configuration settings are received from a server (e.g., the cloud platform 105). The configuration settings may be determined based on the one or more field devices 102A-N and the one or more automation devices 103 connected to the self-configurable device 101. Such configuration settings include one or more parameters for configuring the self-configurable device 101. Therefore, the self-configurable device 101 may be a ‘plug-and-play’ device that may dynamically establish a connection or a communication channel between the one or more field devices 102A-N and the one or more automation devices 103. At act 502, the self-configurable device 101 is configured using the configuration settings such that an active communication channel is established dynamically between the one or more field devices 102A-N and the one or more automation devices 103.

[0053] In an embodiment, the self-configurable device 101 is configured to generate an alarm if an error in communication between the one or more field devices 102A-N and the one or more automation devices 103 or between self-configurable device 101 and one or more field devices 102A-N or one or more automation devices 103 is identified. Such communication error may occur, for example, if the self-configurable device 101 is disconnected from the one or more field devices 102A-N or the one or more automation devices 103. Alternatively, communication error may also occur if signal levels from the one or more field devices 102A-N are below NAMUR signal levels.

[0054] FIG. 7 illustrates a flowchart of a method 700 of automatically calibrating the field devices 102A-N. The one or more field devices 102A-N are monitored at regular intervals to determine efficient functioning and the effect of related field parameters on such one or more field devices 102A-N. The one or more field devices 102A-N may need calibration/recalibration at regular intervals so as to provide efficient functioning of the automation system 107. The determination of need for a calibration may be determined by framing a state-space representation of the automation system 107 and/or a section of the industrial installation 100. State-space representation provides an overview of the state of the system 107 at any given point in time. At act 701, a baseline state-space representation of the automation system 107 is obtained. The baseline state-space representation includes a model of a set of at least one input variable, at least one output variable, and at least one state variable of the automation system corresponding to an optimum functioning of the automation system. The baseline state-space representation may be automatically determined, for example, based on one or more optimum working conditions of at least one section of the industrial installation 100 and control schemes in the engineering configuration of the industrial installation 100. The state-space representation of a system may be represented as follows:

[00001]$\begin{array}{cc}X=Ax+\mathrm{Bu}& \left(1\right)\\ Y=Cx+\mathrm{Du}& \left(2\right)\end{array}$

where X is the state vector, Y is the output vector, u is the input vector or variables associated with the at least one section of the industrial installation 100, A is the system matrix or constants describing the at least one section of the industrial installation 100, B is the input matrix or constants describing the at least one section of the industrial installation 100, C is the output matrix or constants that weigh the state variables, D is the feedthrough matrix or constants that weigh the variables associated with the at least one section of the industrial installation 100.

[0055] The method of derivation of a state-space representation is well-known in the state of the art and has not been described for the purposes of brevity. In an embodiment, the baseline state-space representation may be automatically determined based on optimum operating conditions of at least one section of the industrial installation 100. The derivation of the baseline state-space representation may be performed during plant commissioning or maintenance process of the industrial installation 100. The process of determining the baseline state-space representation is described with an illustrative example of a section 600 of an industrial installation 100, in FIG. 6. Referring to FIG. 6, the section 600 of the industrial installation 100 includes a container 601. The container 601 may include a substance that may be required to be maintained at a pre-defined level. The container 601 may include one or more input and output valves, and the level of substance may be maintained by controlling inlet and outlet flow rate of the substance in the container 601. The container 601 may be further associated with a flow indicator and controller 602 for inlet flow to the container 601, a level indicator and controller 603, a flow indicator and controller 604 for outlet flow from the container 601. Control scheme of the section 600 of the industrial installation 100 may be configured and controlled during run-time of the section 600. A desired pre-defined level of the substance in the container 601 is set as a set-point LIC101.SP at the level indicator and controller 603. An actual level of the substance in the container 601 is determined using a level transmitter 609 in the container 601. Such input of the actual level of the substance is transmitted to the level indicator and controller 603. The level indicator and controller 603 determines if the actual level deviates from the desired pre-defined level. Based on the deviation, the level indicator and controller 603 computes an output CV1/CV2 that is analyzed by a standard control algorithm. Such standard control algorithm may monitor and control the flow parameters of the substance in the container 601. The standard control algorithm, based on the analysis, may compute an output FIC101.SP/FIC102.SP to the flow indicator and controller 602 for inlet flow to the container 601 and/or to the flow indicator and controller 604 for outlet flow from the container 601. The inlet flow FIC101.PV is measured by an inlet flow transmitter 605 and provided to the inlet flow indicator and controller 602. The outlet flow FIC102.PV is measured by an outlet flow transmitter 607 and provided to outlet flow indicator and controller 604. The flow indicator and controller unit 602 for the inlet flow and the flow indicator and controller unit for the outlet flow 604 derive an output signal FIC101.CV/FIC102.CV for operation of valves 606 and 608 to desired set-point calculated by the level indicator and controller unit 603.

[0056] The section 600 of the industrial installation 100 may be considered for determination of the state-space representation to identify a need for calibration of one or more components of the section 600. The state-space representation may be determined based on the following acts:

[0057] Act 1: The state variables are identified automatically based on the control scheme:

[00002]$\left[\begin{array}{c}x1\\ x2\\ x3\\ x4\end{array}\right]=\left[\begin{array}{c}603\\ 604\\ 606.\%\mathrm{open}\mathrm{feedback}\\ 608.\%\mathrm{open}\mathrm{feedback}\end{array}\right]$

[0058] Act 2: The system input variables are identified automatically based on the control scheme:

[00003]$\left[\begin{array}{c}u1\\ u2\\ u3\\ u4\\ u5\end{array}\right]=\left[\begin{array}{c}\mathrm{LIC}101.\mathrm{SP}\\ \mathrm{FIC}101.\mathrm{SP}\\ \mathrm{FIC}102.\mathrm{SP}\\ \mathrm{FIC}101.\mathrm{CV}\\ \mathrm{FIC}102.\mathrm{CV}\end{array}\right]$

[0059] Act 3: First order differential equations are derived based on the state variables and system input variables:

[00004]$\frac{dx1}{dt}=a11.x1+a12.x2+a13.x3+a14.x4+b11.u1+b12.u2+b13.u3+b14.u4+b15.u5$$\frac{dx2}{dt}=a21.x1+a22.x2+a23.x3+a24.x4+b21.u1+b22.u2+b23.u3+b24.u4+b25.u5$$\frac{dx3}{dt}=a31.x1+a32.x2+a33.x3+a34.x4+b31.u1+b32.u2+b33.u3+b34.u4+b35.u5$$\frac{dx4}{dt}=a41.x1+a42.x2+a43.x3+a44.x4+b41.u1+b42.u2+b43.u3+b44.u4+b45.u5$

[0060] Act 4: Matrix A & B of state equation (1) are determined, and the state equation is computed. For various values of Ui during the industrial installation process, the state equations are framed and resolved to find the constants describing the system 600 under consideration.

[00005]$A=\left[\begin{array}{cccc}a11& a12& a13& a14\\ a21& a22& a23& a24\\ a31& a32& a33& a34\\ a41& a42& a43& a44\end{array}\right]$$B=\left[\begin{array}{ccccc}b11& b12& b13& b14& b15\\ b21& b22& b23& b24& b25\\ b31& b32& b33& b34& b35\\ b41& b42& b43& b44& b45\end{array}\right]$

[0061] Hence, the state equation X=Ax+Bu is derived.

[0062] Act 5: The output variables are automatically determined from the control scheme, and the output equations are framed for n(4) state variables and r(5) system inputs. The system outputs are directly connected to the level set-point LIC101.SP, and hence, the output variable is the level of the container LIC101.PV. During stable operation of the industrial installation 100, various container levels are observed for different combinations of state variables and system input parameters. The number of iterations depends on the number of state variables added to number of system input variables. If m such iterations are to be provided, the first order differential equation is derived as follows:

[00006]$y1=c11.x1+c12.x2+c13.x3+c14.x4+d11.u1+d12.u2+d13.u3+d14.u4+d15.u5$$y2=c21.x1+c22.x2+c23.x3+c24.x4+d21.u1+d22.u2+d23.u3+d24.u4+d25.u5$$\mathrm{.Math.}$$\mathrm{ym}=\mathrm{cm}1.x1+\mathrm{cm}2.x2+cm3.x3+\mathrm{cm}4.x4+dm1.u1+dm2.u2+dm3.u3+dm4.u4+\mathrm{dm}5.u5$

[0063] Act 6: Matrix C & D of output equation (2) are determined, and the output equation is computed. For various values of Ui during the industrial installation process, the state equations are framed and resolved to find the constants describing the system under consideration.

[00007]$C=\left[\begin{array}{cccc}c11& c12& c13& c14\\ c21& c22& c23& c24\\ \mathrm{.Math.}& \mathrm{.Math.}& \mathrm{.Math.}& \mathrm{.Math.}\\ cm1& cm2& cm3& cm4\end{array}\right]$$D=\left[\begin{array}{ccccc}d11& d12& d13& d14& d15\\ d21& d22& d23& d24& d25\\ \mathrm{.Math.}& \mathrm{.Math.}& \mathrm{.Math.}& \mathrm{.Math.}& \mathrm{.Math.}\\ dm1& dm2& dm3& dm4& dm5\end{array}\right]$

[0064] Hence, the output equation Y=Cx+Du is derived.

[0065] At act 702 of the method 700, a real-time state-space representation of the automation system 107 is determined. The real-time state-space representation includes a model of a set of at least one input variable, at least one output variable, and at least one state variable corresponding to a real-time functioning of the automation system 107. At act 703, the real-time state-space representation is compared with the baseline state-space representation to identify a deviation. If a deviation is identified at act 704, a notification or alarm is generated at act 705, for example, in the HMI device 104. Such notification may be presented to the user of the industrial installation 100 to determine if a calibration of the field devices 102A-N is to be performed. At act 706, a determination is made if calibration of the automation system 107 is to be performed. If the calibration is to be performed, at act 708, the real-time state-space representation of the automation system 107 is calibrated based on the baseline state-space representation. Alternatively, an alarm is generated for maintenance and calibration of the automation system 107. If the calibration is not to be performed, at act 707, the baseline state-space representation is modified according to the real-time state-space representation of the automation system 107.

[0066] In an embodiment, the self-configurable device 101 is configured to perform one or more functions of a controller unit in an industrial installation 100. The controller unit may be configured to monitor and control a plurality of processes in the industrial installation 100 so as to enable efficient functioning of the industrial installation 100. An average industrial installation 100 includes a number of signals originating from one or more field devices 102A-N. A portion of such signals may form a part of process control schemes. However, the rest of the signals may be associated only with monitoring and closed loop control of the industrial installation 100. In an embodiment, signal processing functions, simple monitoring loops, and simple control loops may be transferred from the controller unit to the self-configurable device 101 associated with the target automation device 103. Such transfer of functions from the controller unit may be performed based on a bandwidth capacity of the self-configurable device 101. Transfer of such functions to the self-configurable device 101 enables efficient management and processing of signals in the industrial installation 100. Additionally, transfer of such functions from the controller unit to the self-configurable device 101 enables the controller unit to be efficiently used for complex process controls that may require greater processing capacity.

[0067] FIG. 8 is a high-level schematic representation 800 of the industrial installation 100, according to an embodiment. The self-configurable device 101 is connected to the one or more field devices 102A-N and one or more automation devices 103A-N. The self-configuration device 101 may be connected to one or more servers 105A-N. The servers may be, for example, an engineering server, an archiving server, a calculation server, a communication server, etc. The servers 105A-N may include data associated with the industrial installation 100 such as, but not limited to, events and alarms of the industrial installation 100. The servers 105A-N may also include data associated with the operation of the industrial installation 100. At least one of the servers 105A-N may be an OPC-UA server. The self-configurable device 101 may be directly connected to a plant network 810 or a control network 812. A Thin client 801, a web client 802, and SAP systems 803 may be connected to the industrial installation 100 via the plant network 810 and a firewall 820 for secured access.

[0068] The foregoing examples have been provided merely for the purpose of explanation and are in no way to be construed as limiting of the present disclosure disclosed herein. While the present disclosure has been described with reference to various embodiments, it is understood that the words, which have been used herein, are words of description and illustration, rather than words of limitation. Further, although the present disclosure has been described herein with reference to particular means, materials, and embodiments, the present disclosure is not intended to be limited to the particulars disclosed herein; rather, the present disclosure extends to all functionally equivalent structures, methods, and uses, such as are within the scope of the appended claims. Those skilled in the art, having the benefit of the teachings of this specification, may affect numerous modifications thereto, and changes may be made without departing from the scope and spirit of the present disclosure in its aspects.

[0069] The elements and features recited in the appended claims may be combined in different ways to produce new claims that likewise fall within the scope of the present invention. Thus, whereas the dependent claims appended below depend from only a single independent or dependent claim, it is to be understood that these dependent claims may, alternatively, be made to depend in the alternative from any preceding or following claim, whether independent or dependent. Such new combinations are to be understood as forming a part of the present specification.

[0070] While the present invention has been described above by reference to various embodiments, it should be understood that many changes and modifications can be made to the described embodiments. It is therefore intended that the foregoing description be regarded as illustrative rather than limiting, and that it be understood that all equivalents and/or combinations of embodiments are intended to be included in this description.