KR101742119B1 - Apparatus and Method for Hybrid System Modeling and Simulation assembling a Discrete Event System Model and Continuous Time System Model - Google Patents

Abstract

The present invention relates to a weapon system simulation technique, and more particularly, to a method and an apparatus for modelling and simulation of a hybrid system by using an assembly between a discrete event system model and a continuous time system model. The method for modelling and simulation of a hybrid system by using an assembly between a discrete event system model and a continuous time system model comprises: an initialization step; a next time calculation step; a model distinction step; a continuous time system model execution step; and a discrete event system model execution step.

Description

Technical Field [0001] The present invention relates to a method and apparatus for modeling and simulating a hybrid system using assembly between a discrete event system model and a continuous time system model,

The present invention relates to a weapon system simulation technique, and more particularly, to a method and apparatus for modeling and simulating a hybrid system composed of a discrete event system and a continuous time system, such as a weapon system.

Discrete Event System Specification (DEVS) formalism is a proposed modeling theory based on set theory and system theory. It is a kind of standardization tool that plays a role of UML (Unified Modeling Language) and design pattern in simulation program development.

The specification of the DEVS model represented by the DEVS diagram is very similar to UML because both DEVS and UML are based on object-oriented thinking. However, DEVS reflects the simulation management functions that UML can not express in the model specification, and it provides hierarchical model structure and independent simulation control algorithm with design pattern specific to simulation.

The DEVS framework provides a variety of application programming interfaces (APIs) for executing and analyzing model configurations and simulations according to the DEVS formalism as an underlying software that supports such DEVS formulations to be applied to real simulation program development. An example of API is DEVSim ++ developed in C ++ and DEVSJAVA developed in JAVA.

Due to these developments, there is a growing need for a modeling and simulation technique for a hybrid system using assembly between a discrete event system model and a continuous time system model. In particular, a technique for simulating a hybrid system that is simpler and more effective is required.

1. Korean Patent No. 10-12695280000 2. Korean Patent No. 10-12751720000 3. Korean Patent Publication No. 10-2013-0091096

1. Lee, JY, "DEVS Integrated Development Environment for Simulation-based Combat Experiments", Journal of the Korea Society for Simulation, Vol. 22, No. 4, pp. 39-47 (2013.12) 2. Yong Heon Lee et al., "Development of framework and tools for rapid development and reuse of M & S components" Journal of the Korea Society for Simulation, Vol. 22, No.4, pp.29-38 (2013.12)

Disclosure of the Invention Problems to be Solved by the Invention The present invention has been proposed in order to solve the problems according to the above background art, and is an extension of the Discrete Event System Specification (DEVS) methodology widely used as a discrete event simulation methodology. And to provide a method and apparatus for modeling and simulating a hybrid system implementing the modeling methodology.

It is another object of the present invention to provide an apparatus and method for modeling and simulating a hybrid system that can simulate a hybrid system more simply and effectively through the modeling methodology of the continuous-time system.

Disclosure of the Invention In order to achieve the above-described object, the present invention is an extension of the Discrete Event System Specification (DEVS) methodology widely used as a discrete event simulation methodology. It is a hybrid method that implements a continuous time system modeling methodology in a form similar to a general DEVS methodology And provides a method for modeling and simulating the system.

A method for modeling and simulating a hybrid system,

A method for modeling and simulating a hybrid system using assembly between a discrete event system model and a continuous time system model,

An initialization step of setting an initial condition for initialization;

A next time calculation step of calculating the next time as the initial condition is set;

Determining whether the event block type corresponds to the continuous time system model or the discrete event system model according to the initial condition being set;

Determining whether the next time calculation step or the zero crossing is detected according to whether the zero crossing is detected in the continuous time system model; And

And a discrete event system model execution step of performing an internal state transition and performing a time advance call (FTC) call according to the discrete event system model to perform the next time calculation step do.

In this case, the hybrid system may be a combined system model of the discrete event system model and the continuous time system model.

Also, the continuous-time system model may include a state condition function that identifies a change in the continuous-time state variable such that a change in the continuous state variable causes a discrete event, and a generated discrete event state variable.

Also, the discrete event system model may include an internal state transition function for expressing the state change at the discrete time and a time progress function for determining the execution time of the internal state transition function.

Also, the continuous time system model may be expressed by the following mathematical specification DESS Model = <Ucont, Ycont, Xcont, f, g, c, Xmode> (where Ucont is a set of consecutive input variables; Ycont is a set of consecutive output variables; Xcont : Xcont × Ucont → Xcont × Continuous state transition function, g: Xcont × Ucont → Ycont: Continuous output function, c: Xcont × Xmode → bool: state event condition function).

Also, the discrete event system model includes DEVS Model = Udisc, Ydisc, Xdisc, Δext, Δint, λ, ta (where Udisc is a set of input events, Ydisc is a set of output events, Xdisc is a set of discrete states (S), s: current state, e: time remaining in the current state, δext: Q × Udisc → Xdisc: external state transition function Q = Xdisc → Xdisc: internal state transition function, ta: Xdisc → R0, ∞: time progression function), where Q is the total state of the atomic model, λ is the Xdisc → Ydisc output function, .

Also, the hybrid system may be configured to use the following mathematical specification Hybrid Model = (U = Ucont∪Udisc: discrete event, set of continuous inputs; Y = Ycont∪Ydisc: EOC: External output event connection relation, IC: Internal event connection relation, SELECT: External input event handling, EOC: External output event connection relation, IC: Internal event connection relation, MISDES∪DEVS∪Hybrid: A priority selection function between the internal models of the first and second embodiments.

In this case, the next time calculation may be a continuous update time interval and a discrete update time interval, and may have several consecutive update time intervals for each discrete update time interval.

Also, the discrete event system model and the graphical notation system of the continuous time system can be used.

In addition, when the internal state transition occurs, the state transition is updated continuously, discrete, or at a predetermined time.

According to another aspect of the present invention, there is provided an apparatus for modeling and simulating a hybrid system using an assembly between a discrete event system model and a continuous time system model, the apparatus comprising: initial conditions for initialization; And determines whether the event block type corresponds to the continuous time system model or the discrete event system model as the initial condition is set. If it is determined that the event block type corresponds to the continuous time system model, The system model re-checks whether the next time calculation step or the zero crossing is detected according to whether the system model is detected as zero crossing. If it is determined that the discrete event system model corresponds to the discrete event system model, By performing a Time Advance Fcn Call It provides an apparatus for the modeling and simulation of hybrid systems, characterized in that for performing the following time period calculated.

The present invention proposes a methodology for modeling and simulating a complex hybrid simulation structure in a more simplified manner.

Another advantage of the present invention is that it enables efficient simulation of complex simulation such as weapon system simulation.

1 is a conceptual diagram showing a basic interface and a combining method of a model class for combining a discrete event system model (DEVS) and a continuous time system model (Continuous Time) according to an embodiment of the present invention.
2 is a conceptual diagram of the coupled system model shown in FIG.
3A is a flowchart illustrating an integrated simulation process between a discrete event system model and a continuous time system model according to an embodiment of the present invention.
FIG. 3B is a graph showing the concept of a continuous update interval and a discrete update interval for the next time calculation shown in FIG. 3A.
FIG. 4A is a conceptual diagram showing the notation system of the discrete event system model 110 shown in FIG.
FIG. 4B is an example of programming for the class interface of the discrete event system model shown in FIG. 4A.
FIG. 5A is a conceptual diagram showing the notation of the continuous-time system model 120 shown in FIG.
FIG. 5B is an example of programming for the class interface of the continuous-time system model shown in FIG. 5A.
FIG. 6 is a conceptual diagram showing the notation system of the coupled system model 130 shown in FIG.
FIG. 7 is an example of programming for the class interface of the coupled system model shown in FIG.
8 is a conceptual diagram showing a general continuous time system in a state space representation form.

While the invention is susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and will herein be described in detail. It is to be understood, however, that the invention is not to be limited to the specific embodiments, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.

Like reference numerals are used for similar elements in describing each drawing.

The terms first, second, etc. may be used to describe various components, but the components should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another.

For example, without departing from the scope of the present invention, the first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component. The term "and / or" includes any combination of a plurality of related listed items or any of a plurality of related listed items.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

Terms such as those defined in commonly used dictionaries are to be interpreted as having a meaning consistent with the contextual meaning of the related art and are to be interpreted as either ideal or overly formal in the sense of the present application Should not.

Hereinafter, an apparatus and method for modeling and simulating a hybrid system using assembly between a discrete event system model and a continuous time system model according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings.

1 is a conceptual diagram showing a basic interface and a combining method of a model class for combining a discrete event system model (DEVS) and a continuous time system model (Continuous Time) according to an embodiment of the present invention. Referring to FIG. 1, a discrete event system model 110, a continuous time system model 120, and a coupled system model 130 are constructed.

These discrete event system model 110, continuous time system model 120, and coupled system model 130 comprise system variables and system functions.

The system variables of the discrete event system model 110 are U (inports), Y (outports) and X_Discrete, and the system functions are External Transition, Internal Transition, Output, and Time Advance.

The system variables of the continuous time system model 120 are U (inports), Y (outports), X_Continuous, X_mode, and the system functions are External Transition, Derivative, Output, Step, Output and StateEvent.

The system variables of the coupled system model 110 are U (inports), Y (outports), M (components), and the system functions are EIC, EOC, IC, and Select.

The hybrid system, such as a weapon system, is characterized by a hybrid system consisting of various parts. For example, a complex system such as a missile may include a fire command (not shown), a propulsion (not shown), an induction controller (not shown), a fuse (not shown) a war head (not shown), and a seeker (not shown).

Most of these are described in mathematical specifications, where physics-based analog systems such as propulsion or warheads are represented by differential equations.

Alternatively, a digital system that performs tactic determination or algorithmic computation, such as a fire controller or an inductive controller, may be represented by a difference equation, a finite state machine (FSM), or a discrete event system specification do.

The Hybrid System is a hybrid system in which analog systems such as a weapon system, a continuous-time system, a digital system, and a discrete event system are mixed, and the characteristics of the respective systems are maintained. have.

Therefore, in order to analyze a hybrid system such as a weapon system, the mathematical specification of the continuous time system and the discrete event system should be reflected and assembled to analyze the dynamic characteristics of the whole system.

The mathematical specification of the continuous time system is represented by the Differential Equation System Specification (DESS) and is shown in FIG. 8 will be described later.

With continued reference to FIG. 1, the mathematical specification of a continuous or more continuous time system model can be briefly expressed as the following set expression.

[Definition 1] : Continuous-time system model

DESS Model = <Ucont, Ycont, Xcont, f, g>

Ucont: set of continuous input variables

Ycont: Set of continuous output variables

Xcont: set of continuous state variables

f: Xcont × Ucont → Xcont: Continuous state transition function

g: Xcont × Ucont → Ycont: Continuous output function

One embodiment of the present invention in the above generic continuous-time system representation defines a continuous-time system model as follows for hybrid simulations coupled with a discrete event system.

[Definition 2] : A modified continuous-time system model according to an embodiment of the present invention

DESS Model = <Ucont, Ycont, Xcont, f, g, c, Xmode>

Ucont: set of continuous input variables

Ycont: Set of continuous output variables

Xcont: set of continuous state variables

Xmode: A set of discrete state variables representing fractional continuation intervals

f: Xcont × Ucont → Xcont Continuous state transition function

g: Xcont × Ucont → Ycont: Continuous output function

c: Xcont × Xmode → bool: Status event condition function

This is because the continuous-time system must be able to cause the discrete event of a change in the continuous state variable. Therefore, the state-condition function c, which identifies the change of the continuous-time state variable in the definition of the general continuous- Add the variable Xmode.

The mathematical specification of the discrete event system is represented by the DEVS (Discrete EVent system Specification Formalism). Unlike the mathematical specification of the continuous-time system, a time progress function is additionally defined to determine the internal state transition function and the execution time point of the internal state transition function to express the state change at the discrete time.

[Definition 2] : Discrete event system model

DEVS Model = <Udisc, Ydisc, Xdisc, Δext, Δint, λ, ta>

Udisc: set of input events

Ydisc: set of output events

Xdisc: A set of discrete states

δext: Q × Udisc → Xdisc: External state transition function

Q = {(s, e) | sxS, 0? E? Ta (s)}

s: current state, e: time remaining in current state

Q: The overall state of the atomic model

λ: Xdisc → Ydisc: Output function

δint: Xdisc → Xdisc: Internal state transition function

ta: Xdisc → R0, ∞: time progress function

Hybrid systems can be represented by a variety of modeling methodologies as a system with a continuous time system and a discrete time system. The hybrid system according to an embodiment of the present invention is defined as a combined system model 130 of the discrete event system model 110 and the continuous time system model 130 as follows.

[Definition 3] : Hybrid System Model

Hybrid Model = <U, Y, M, EIC, EOC, IC, SELECT>

U = Ucont∪Udisc: Discrete event, set of consecutive inputs

Y = Ycont∪Ydisc: Set of discrete events, continuous output

M⊂DESS∪DEVS∪Hybrid: set of internal models

EIC: External Input Coupling Relation

(External input event connection relationship)

EOC: External Output Coupling Relation

(External output event connection relation)

IC: Internal Coupling Relation

(Internal case connection relationship)

SELECT: Priority selection function between internal models for handling external input events

2 is a conceptual diagram of the coupled system model shown in FIG. Referring to FIG. 2, coupled system model 130 is an integrated system of discrete event system model 110 and continuous-time system model 120.

3A is a flowchart illustrating an integrated simulation process between a discrete event system model and a continuous time system model according to an embodiment of the present invention. Referring to FIG. 3A, the initial conditions are set by initializing the functions (step S310).

As the initialization is made, the next time is calculated (step S311).

In accordance with the next time, it is checked whether the event block type is continuous or discrete (step S315).

As a result, if the event block type is a continuous time system model, an output is calculated, a delivery output variable is calculated according to the calculated output, a step Fcn call for solving the derivative is calculated, and a zero- And calculates a status event Fcn call for detection (steps S320, S321, S323, S325).

Thereafter, it is confirmed whether zero crossing is detected (step S340). As a result of checking, if a zero crossing is detected, the time-step is adjusted and steps S323 to S340 are repeated (step S360).

Otherwise, if no zero crossing is detected in step S340, an internal state transition Fcn call is generated and step S311 is performed (step S350).

In step S315, if the event block type is a discrete event system model, the output is calculated, the transfer output variable is calculated according to the calculated output, the Fcn call is updated, the internal state transition Fcn call is calculated, and the time high Fcn call is calculated , And performs step S311 (steps S330, S331, S333, S335, and S337).

FIG. 3B is a graph showing the concept of a continuous update time interval and a discrete update time interval for next time calculation shown in FIG. 3A. FIG. Referring to FIG. 3B, several consecutive update time intervals are configured for each discrete update time interval.

FIG. 4A is a conceptual diagram showing the notation system of the discrete event system model 110 shown in FIG. Referring to FIG. 4A, a state is also referred to as a mode, which means a sequential state indicating a mode of an event model. The state includes a phenomenon that the state transition is updated continuously or discretely or at a predetermined time when an internal transition occurs.

The external transition may be indicated by the solid arrow 401. The external transition is linked from one mode 420 to another mode 430 when an external event is input. That is, a transition is performed when the condition is matched, and is defined as an action such as an operation when a transition is performed, a function call, and an event trigger.

The internal transition may be indicated by the dotted arrow 402. The internal transition is linked from the current mode 430 to the other mode 420 when the remaining time of the current mode disappears.

Conditions are used in conjunction with events to specify a valid transition. External transitions and internal transitions are dependent on whether the conditional expression inside the brackets is true. At the same time, the object 440 includes the object data / function 441 of the object.

FIG. 4B is an example of programming for the class interface of the discrete event system model shown in FIG. 4A. Of course, such programming is merely an example, and it is possible to write using another programming language.

FIG. 5A is a conceptual diagram showing the notation of the continuous-time system model 120 shown in FIG. Referring to FIG. 5A, an external transition may be indicated by a solid line arrow 501. The external transition is linked from one mode 520 to another mode 530 when an external event is input. That is, a transition is performed when the condition is matched, and is defined as an action such as an operation when a transition is performed, a function call, and an event trigger.

Internal transitions may be indicated by dashed arrows 502. The internal transition is linked from the current mode 530 to the other mode 520 when the remaining time of the current mode disappears.

Conditions are used in conjunction with events to specify a valid transition. External transitions and internal transitions are dependent on whether the conditional expression inside the brackets is true. In addition, the object 540 includes the object data / function 541 of the object.

FIG. 5B is an example of programming for the class interface of the continuous-time system model shown in FIG. 5A. Of course, such programming is merely an example, and it is possible to write using another programming language.

FIG. 6 is a conceptual diagram showing the notation system of the coupled system model 130 shown in FIG. Referring to FIG. 6, the discrete time system model 110 includes a first discrete event system model 110-1 and a second discrete event system model 110-2.

FIG. 7 is an example of programming for the class interface of the coupled system model shown in FIG. Of course, such programming is merely an example, and it is possible to write using another programming language.

8 is a conceptual diagram showing a general continuous time system in a state space representation form. Referring to FIG. 8, it can be expressed in the form of a state space representation based on state variables and transition functions.

Transforms the physical law 810 into a differential spin 820 using ODE (Ordinary Differential Equation) and transforms it into a state-space form 830. This is widely known and will not be described further.

Those skilled in the art will appreciate that the various illustrative logical blocks, and algorithm steps described in connection with the embodiments disclosed herein, may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality.

Whether such functionality is implemented as hardware or software depends upon the design constraints and specific applications imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the exemplary embodiments of the present invention.

The various illustrative logical blocks, modules, and circuits described in connection with the embodiments disclosed herein may be implemented or performed with a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array Or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein.

A general purpose processor may be a microprocessor, but, in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.

The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in a memory such as a random access memory (RAM), a flash memory, a read only memory (ROM), an electrically programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), registers, CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such that the processor can read information from, and write information to, the storage medium.

Alternatively, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. Alternatively, the processor and the storage medium may reside as discrete components in a user terminal.

In one or more exemplary embodiments, the functions described may be implemented in hardware, software, firmware, or any combination thereof. When implemented in software, the functions may be stored or transmitted as one or more instructions or code on a computer-readable medium. The computer-readable medium includes both a communication medium and a computer storage medium, including any medium that facilitates transfer of a computer program from one place to another. The storage medium may be any available media that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can be stored in RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, And any other medium which can be used to carry or store the desired program code and which can be accessed by a computer.

Also, any connection is properly termed a computer-readable medium. For example, if the software is transmitted from a web site, server, or other remote source using wireless technologies such as coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or infrared, wireless and microwave, Wireless technologies such as cable, fiber optic cable, twisted pair, DSL, or infrared, radio, and microwave are included within the definition of media. As used herein, discs and discs include compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disc and Blu-ray disc, ) Typically reproduce data autonomously, but discs use lasers to optically reproduce the data. Also, the above combinations should be included within the scope of computer-readable media.

110: Discrete event system model
120: Continuous Time System Model
130: Coupled system model

Claims (11)

A method for modeling and simulating a hybrid system using assembly between a discrete event system model and a continuous time system model,
An initialization step of setting an initial condition for initialization;
A next time calculation step of calculating the next time as the initial condition is set;
Determining whether the event block type corresponds to the continuous time system model or the discrete event system model according to the initial condition being set;
Determining whether the next time calculation step or the zero crossing is detected according to whether the zero crossing is detected in the continuous time system model; And
A discrete event system model execution step of performing an internal state transition and performing a time advance call (FTC) call according to the discrete event system model to perform the next time calculation step;
The method comprising the steps &lt; RTI ID = 0.0 &gt; of: &lt; / RTI &gt;
The method according to claim 1,
Wherein the hybrid system is a combined system model of the discrete event system model and the continuous time system model.
The method according to claim 1,
Wherein the continuous time system model includes a state condition function that identifies a change in a continuous time state variable such that a change in the continuous state variable causes a discrete event and a generated discrete event state variable that is generated for the modeling and simulation of the hybrid system. Way.
The method according to claim 1,
Wherein the discrete event system model includes an internal state transition function for expressing a state change at a discrete time and a time progress function for determining an execution time point of the internal state transition function. .
The method of claim 3,
The continuous time system model is defined by the following mathematical specification DESS Model = <Ucont, Ycont, Xcont, f, g, c, Xmode> (where Ucont is a set of consecutive input variables; Ycont is a set of consecutive output variables; Xcont × Continuous state transition function g: Xcont × Ucont → Ycont: Continuous output function c: Xcont × Xmode → bool: State event condition function). &Lt; RTI ID = 0.0 &gt; 11. &lt; / RTI &gt;
5. The method of claim 4,
The discrete event system model includes DEVS Model = Udisc, Ydisc, Xdisc, δext, δint, λ, ta (where Udisc is a set of input events; Ydisc is a set of output events; Xdisc is a set of discrete states; δext: Q × Udisc → Xdisc: External state transition function Q = {(s, e) | s × S, 0≤e≤ta (s) : Xdisc → Ydisc: output function; δint: Xdisc → Xdisc: internal state transition function; ta: Xdisc → R0, ∞: time progress function) And methods for simulations.
3. The method of claim 2,
The hybrid system includes the following mathematical specification Hybrid Model = (U = Ucont∪Udisc: Discrete event, set of consecutive inputs; Y = Ycont∪Ydisc: Discrete event , EOC: external output event connection relation, IC: internal event connection relation, SELECT: external input event handling, EOC: external output event connection relation, IC: internal event connection relation, MISDES∪DEVS∪Hybrid: A priority selection function between the internal models). &Lt; Desc / Clms Page number 13 >
The method according to claim 1,
Wherein the next time calculation is made of a continuous update time interval and a discrete update time interval and has a number of consecutive update time intervals for each of the discrete update time intervals.
The method according to claim 1,
Wherein the discrete event system model is expressed using the discrete event system model and the graphical notation system of the continuous time system.
The method according to claim 1,
And when the internal state transition occurs, the state transition is updated continuously, discrete, or at a predetermined time.
1. An apparatus for modeling and simulating a hybrid system using assembly between a discrete event system model and a continuous time system model,
Determining whether the event block type corresponds to the continuous time system model or the discrete event system model when the initial condition is set,
If it is determined that the continuous time system model corresponds to the continuous time system model, the continuous time system model may again check whether the next time calculation step or the zero crossing is detected,
If it is determined that the discrete event system model corresponds to the discrete event system model, the discrete event system model performs an internal state transition and performs a time advance Fcn call to perform the next time calculation. And apparatus for simulation.

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