Project methodology: concepts, principles and requirements

Prof., DSc. B.V. Sokolov

Presentation Outline

1. Conceptual description of Natural-Technological Objects (NTO) Monitoring and Control Systems (MCS)

2. Problems Statement

3. Project methodology: concepts, principles and requirements

Slide 2

Great Varity of Monitoring Data

Source: IGMASS Project_2011

3 20.02.2014

The Seaport

20.02.2014 4

The Rail Center

20.02.2014 5

The Logistic terminal

20.02.2014 6

Monitored

object systems

experts

Local (client)

workstations

Local network

Database server

Measuring information

Global network

Commutator (router)

Monitoring technology realization scheme

Measuring information acquisition system

Transport net

Pipe line

Power Grid-system

Telecommunication net

j h level of CTS Variants of multi- structural

states

Types of structures

)(

0

jS )(1

jS ... )( jK

S

Topological structure )( jtopS

...

Technology structure )( jtS

...

Technical structure )( jtecS

...

Structure of special software

and mathematical tools )( jsfS ...

Information structure )( jinS

...

Organizational structure )( jorS

...

)( jtopS

1 t 1 2 3 4

2 3 4 )( jtS

1 t 1 2 3 4

2 3 4 )( jtecS

1 t 1 2 3 4

2 3 4

)( j

inS 1

t 1 2 3 4

2 3 4

)( j

sfS

1 t 1 2 3 4

2 3 4 )( jorS

1 t 1 2 3 4

2 3 4

Fig.1.1.Diagrams of NTO structure dynamics Fig. 1.2. Possible variants of

NTO structure dynamics

In Fig.1.1, Fig.1.2 S( j) is a number of NTO structural states. In Fig.1.2 the

points on the abscissa axis of the diagrams are discrete time instants. The

axis of ordinates shows the numbers of the NTO structural states. In

Fig.1.2 each diagram represents a particular structure type.

tj tj+1

Business Process

(BP)

Information System

(IS)

Virtual Enterprise (VE) B1

VE (B2)

IS2

ISl

IS1 IS2

ISn

Structure State R1

ISl

IS1 IS2

ISn

Structure State R2

ISl

IS1 IS2

ISn

Structure State R3

IS1 IS2

ISn

Structure State R4

ISl

IS1

ISn

Structure State R5

ISl

IS1

Structure State R6

IS1 IS2

Structure State R7

VE (Bn)

ISn

VE (Bl)

ISl

Telecommunicational

System (TS)

Structures

state sensors

Aggregates

and equipment

state sensors

Aerospace

ERS means

Monitored

object

Processing

means 1

Processing

means 2

Processing

means 3

Image of

object 1

Image of

object 2

Image of

object 3

DMP

11 20.02.2014

in

automated

a

Mainframes

Personal computers

Client-server systems Internet-based systems

Service-oriented systems Web-services

Business-oriented systems

1980’s – automation of

internal processes (back

office). Main goal:

stability and reliability.

1990’s – automation of

personal office work (front

office). Main goal: speed.

Now – automation of the whole IT-

infrastructure, ability to adapt to

requirements of business. Main goal:

stability, reliability, speed, and return on

investments.

Convergence between cybernetics and computer science

1. Interim report – Guidelines for FP7 «Control System Investigation in ES» (2005).

2. К.Ostrem. Report «Present Development in Control Applications» IFAC Conference ( September 2006)

3. First Russia multi-conference of control problems

(October 2006 г.).

C3=control+communication+computing.

4. Yusupov R.М. On 90th anniversary of Academician E.P. Popov // Informac. Upravl. Syst., 2005, no. 1, pp. 51-57.

Neocybernetics = Cybernetics + Computer Science +General System

Theory =C2S2

Computing

Control Physics Biology Mathema

tics

Communi cation

C3BMP

Social-Cyber-Physical Modeling

The methodological and methodical basis for structure-dynamics control at NTO exploitation period is being developed in the study.

The theory of structure-dynamics control as a scope of

interdisciplinary investigations

System analysis

Operations

research

Control theory System theory

Artificial

intelligence

NTO structure

dynamics control

theory

The problem of NTO structure-dynamics control consists of the following groups of tasks:

the tasks of structure dynamics analysis of NTO;

the tasks of evaluation (observation) of structural states and NTO structural dynamics;

the problems of optimal program synthesis for structure dynamics control in different situations

the tasks of NTO integrated modeling and simulation

3.

Methodological basis of NTO SDC includes:

the methodologies of the generalized system analysis

the modern optimal control theory for NTO with re- configurable structures

The methodologies find their concrete reflection in the corresponding principles. The main principles are:

the principle of goal programmed control

the principle of external complement

the principle of necessary variety

the principles of multiple-model and multi-criteria approaches

the principle of new problems.

The concept of proactive control and monitoring of complex objects

18

Complex

Object

Reactive

Control Incident

Proactive

Forecasting

Complex

Object

Proactive

Control State

The concept

of system

modeling

In contrast to the commonly used

reactive control, oriented on rapid

response and subsequent

prevention of incidents, proactive management involves prevention of incidents

by the establishment of appropriate monitoring and control system

of innovative predictive and proactive capabilities in formulating and implementing

control actions based on the concept of the system (complex) modeling.

interaction state

facilities state

motion state

resource state

INTERACTION interaction

control

FACILITIES

M O T I O N

R E S O U R C E

perturbations

perturbations

perturbations

facility control

motion control

resource

control

perturbations

environment status or characteristics of other AMO

General block diagram of Active Moving Object

Concept Model for COTS Structure-

Dynamics Control Processes

Space-crafts

and orbital

system

Other dynamics

objects

Ground-based

moving objects

and systems

Ships and

submarines

Aircraft

Active Moving

Object (AMO)

Elements of

flexible

manufacturing

The fragment of a diagram for transitions from AMO-I general states

Concept Model for NTO MCS Structure- Dynamics Control Processes

AMO-I movement

after target

tasks execution

AMO-I technical

service and repair

functioning in

a reserve state

of the first type

AMO-I movement

to execute the

target tasks

fulfillment of

AMO-I target task

functioning in a

reserve state

of the second type

Ground-based

and floating

stations

Seaport and

riverside

stations

Other systems

of dynamics

objects

Flexible

manufacturing

Junctions and

transport

stations

Airdromes,

aircraft carrier

Active Service

System

The fragment of diagram for transitions from AMO-II (AMO-I interacting station) general states

Concept Model for NTO MCS Structure- Dynamics Control Processes

transceiving of

unprocessed

information from

one IS to another

transceiving of

unprocessed

information from

one IS to another

transceiving of

processed information

from IS to AMO-I

storing received

information in IS

receiving of

processed

information by IS

from another IS

processing of

received

information in IS

receiving of unpro-

cessed information by

interacting station

(IS) from AMO-I

receiving of

unprocessed

information by IS

from another IS

Generalized description of models and multi-model complexes

XX YX

J

XXX YXX

J

Classes of models

n

card

X

dim

X

Конструкция основной ступени шкалы множеств

J

J

1

M11

M12

M13

M14

M15

M16

M17

M18

1

n

m

M21

M22

M23

M24

M25

M26

M27

M28

0

1

M31

M32

M33

M34

M35

M36

M37

M38

0

m

M41

M42

M43

M44

M45

M46

M47

M48

1

1

M51

M52

M53

M54

M55

M56

M57

M58

1

m

M61

M62

M63

M64

M65

M66

M67

M68

2

M71

M72

M73

M74

M75

M76

M77

M78

Table 1 Multiple-models interconnections Models of CBS

SDC Procedu- res of CBS SDC tasks solving

)(extr)(0 a

af )(extr)(

0 u

af )()( extr)(

0 ua

af )(extr)(

0 a

uf )(extr)(

0 u

uf )()(

extr)(0 uauf

AOM AN C +

SOM AN C + + +

AOM SOM AN C + +

(AOM SOM) AN C +

(SOM AOM) AN C + + +

CAN

AOM

SOM

AOM1

2

+ + +

Multiple-models interconnections

The method of computational intelligence and its

applications

Combination

two methods three methods four methods

Fuzzy-deduction systems. Fzelips 6.04 Matlab

Fuzzy neural networks Fuzzy probabilistic neural networks

Fuzzy probabilistic neural networks with the genetic algorithm (*)

Neural networks. Neurosolution 3.0 Fuzzy-and-probabilistic deduction systems Guru

Probabilistic neural networks with the genetic algorithm (*)

–

Probabilistic reasoning. Expert system Prospector

Fuzzy-deduction system with genetic algorithm

Fuzzy neural networks with genetic algorithm. Fungen 1.2

–

Genetic algorithms. Professional Version 1.2

Probabilistic neural networks Trajan 2.1 Matlab

Fuzzy-and-probabilistic deduction systems with the genetic algorithm (*)

–

NeuroGenetic Optimizer Neural networks with the genetic algorithm

– –

Probabilistic deduction systems with the genetic algorithm

– –

Multiple-models interconnections

Process logic Flow model

Process structure Functional model

Process data In-forma-

tion model

Behavior of objects

Dynamic model

Organiza-tion

IDEF2CPN STD

IDEF3

IDEF0DFD

IDEF1XERD

Interpreting system

Object state recognition system

Measuring path

Monitoring object

Monitored Object and Computation Process States

Invariance Conception

Monitored object state

Measuring information

Computation system

Monitored object states class

Computation process state estimation

Monitored object state estimation

28

The generalized technique of estimation and control of the quality of models

5 Model of the

investigated system

1. Goals of

functioning

opOb

4 Modeled system

mOb mOb 1

3 Setting

goals of

modeling

2.Input Actions

7 Controlling

6 Estimation

of the Quality

8 Parameters

9 Structure

10 Changing the

concept

Fig 1

Slide 29

Generation of information

Calculation of a plan (sched-ule) or genera-tion regulatory

control

Simulation of control

External-adapter functions

Complex-Business System (CBS)

Recording and moni-toring functions

Internal-adapter functions

Formal and qualitative analysis

The main phases of NTO adaptive control

Possible Modeling Scenarios for Structure Dynamics Control Processes

1t

2t

1

1,

tM

1

1

t

2

1,

tM

2

1

t

For example: 1t

- Active Moving Object

functional structure at time “t1” 1

1

t

- Active Moving Object technical

structure at time “t1” The dynamic alternative multi-graphs

1tG , 1

1

tG describe functional and

technical structure dynamics.

Fig.7.2

The Active Moving Object structure dynamics

(structure reconfiguration)

An – Active Moving

Object number “n”

m – material flows

e – energy flows

i – information flows

t = ts

Fig.7.3

t = ts+1

Fig.7.4

Task of the schedule

planning

• Linear programming • Traffic task • Dynamic programming • Heuristics

Operation research

Task of the operational

control

• Feedback control • Monitoring • Adaptive control • Steadiness analysis

Management theory

Task of the interaction of

supply chain

• Activities goals and interests coordination

• Taking into account the subjectivity of the decision-

making

• Competence modeling • Active elements modeling

МАС / КАС

Exterior

Adapter

Control

Goals

Schedule

Planning

Plan

Analysis

Inner Adapter

Plan

realization

Process Monitoring Perturbations

Execution

Analysis

Problem Statement

,,..1,,,.., 21 WIIMMMMM W

w =||w(1)T , w(2)T,w(3)T ||T

Several variants of NTO models:

Sub vector of parameters:

Vector of parameters being adjusted through

the internal adapter

Vector of parameters being adjusted through

the external adapter

Vector of parameters being adjusted within structural adaptation

of NTO models

Algorithm of Parametric Adaptation residual of characteristics estimation

(1)

(2) perturbation impacts

are described via stochastic models

structure with the best measure (minimal residual) should be chosen

(4)

(3) f (.) -«forgetting» coefficient

Algorithm of Structural Adaptation

Problem C1 Problem C2

AD MQ(l),Pcs( )®min

t s t

w ( 3 ) , M

Q ( l ) ( ) t s t

M Q ( l ) ϵ M ,

w ( 3 ) W ( 3 )

MQ(l ) = F MQ

(l-1),w(3),Pcs( )

tst w(3),MQ

(l )( )®min

A D M Q

( l ) , P c s ( ) ɛ 2

M Q ( l ) M ,

w ( 3 ) W ( 3 )

MQ(l ) = F MQ

(l-1),w(3),Pcs( )

General formal statements for structure adaptation of NTO modules can be written as problems:

ϵ ϵ

≤ ≤

ϵ

Complexity

management

Attenuation of

environmental variety

Amplification of

control variety

control of plant structural dynamics (for example, on the basis of a flexible

combination of hierarchical and network control principles)

structure-dynamics control

self-similar recursive description and modeling of the objects under

investigation (using notions of macro state, structural state, multi-

structural state)

formation of temporary solutions

reduction of dimensionality and uncertainty in description of a data

domain using decomposition (composition) aggregation (disaggregation),

coordination, approximation, linearization, relaxation, and reduction

methods

search for a rational multi-criterion (compromise) solutions under

unavoidable threshold information and time restrictions

classification and ordering of models, establishing their interrelations

poly-model description of data domain

alteration of NTO functioning means and objectives

alteration of the order of observation tasks, and control tasks solving

redistribution of functions, problems and control algorithms between NTO levels

reserve resources control

control of motion of NTO elements and subsystems

reconfiguration of NTO different structures

Мg – dynamic model of NTO motion control; Мk – dynamic model of NTO channel control; Мо – dynamic model of NTO operations control; Мn – dynamic model of NTO flow control; Мр – dynamic model of NTO resource control; Ме – dynamic model of NTO operation parameters control; Мс – dynamic model of NTO structure dynamic control; Мn – dynamic model of NTO auxiliary operation control

)(ox

)(eu

)(ex

)(

0

ex )()( fe Tx

)(eJ )(eξ

)(nx

)(gJ

)(

0

nx )()( fTx )(cJ

)(cx

)е()()(

)()()(

J,J,J

,J,J,J

np

ogk

)(

0

cx

)(cξ )(x

)(kx

)(u

)( pu

)(

0

gx )(gξ

)(

0

ox )(oξ

)(

0x

p

)(ξ

p

)(

0x )(

ξ

М 4

Мp 5

Мk 1

Мo 3

Мc 8

Мп 6 Мg

2

Ме 7

)(

0

kx

)(x

p

)(kJ

)(kJ

)(ku

)(cu

)(J

)(gu )(gx )(nu

)(nJ )(nξ

)(

0

ou

)(oJ

)(kξ

)( pJ

The scheme of models interconnection

The main results Implementations of the results

Criteria for existence of a solution in NTO structure- dynamics control (SDC) problems

Model verification for NTO SDC

Criteria for controllability and attainability in NTO SDC problems

Control processes verification for a given time interval/ Determination of the constraints restricting NTO goal abilities and information technology abilities

Criteria for uniqueness of optimal program control in NTO SDC problems

Analysis of possibility to obtain an optimal plan for NTO SDC

Necessary and sufficient conditions of optimality in NTO SDC problems

Preliminary analysis of optimal program controls; generation of basic formulas for NTO planning algorithms

Criteria for stability and sensitivity in NTO SDC problems

Evaluation of NTO SDC stability and sensitivity for environmental impacts and for alteration of input data

Structures

state sensors

Aggregates

state sensors

Aerospace

ERS

means

DMP

KB

Intelligent Monitoring Interface

Integral

image of

object

Models for decision

support

Unified

processing

means

The

generalized

information on

a situation

Monitored

object

41 20.02.2014

Thank You for Your Attention!

43

Contact information:

Prof. Boris Sokolov

E-mail:

sokol@iias.spb.su

http:litsam.ru

Phone:

+7 812 328 0103

Fax:

+7 812 328 4450

mailto:sokol@iias.spb.su