09/02/2015 E7: Approche système Contenu « ?· Predictive control, LQ control ... – Contrôle / Commande…

  • Published on
    12-Sep-2018

  • View
    212

  • Download
    0

Embed Size (px)

Transcript

  • 09/02/2015

    1

    Olivier Sename 2013

    Mthodes danalyse et de commande des systmes dynamiques (12h CM)

    valuation : DS-CC

    Traitement du signal (12h CM)valuation : DS-CC

    PROJETS (38h)valuation : rapport et prsentation

    Rgulation de confort dans les btiments intelligents Analyse et commande d'un incinrateur de boues en vue de la matrise des missions de NOx Analyse des paramtres hydrauliques par mthodes ultra-sonores Surveillances des machines tournantes

    Objectifs: illustrer les principes gnraux de traitement du signal analyse spectrale, corrlation, mesures de paramtres physiques, dans le domaine E3, et apprendre, par la pratique, utiliser les notions de base de traitement du signal

    Objectifs:Modlisation des systmes dynamiques Mthodologie danalyse de performance et de robustesse des structures de commande,Etude avec Matlab dune mthode interactive assiste de synthse de rgulateurs

    E7: Approche systmepour lenvironnement

    Olivier Sename 2013

    Mthodes danalyse et de commande des systmes dynamiques (12h CM)

    valuation : DS

    Olivier Sename

    Professeur Grenoble INP/ENSE3

    GIPSA-lab, Department Automatique

    Bureau B 247

    Phone: 33 (0) 4 76 82 62 32

    Email:olivier.sename@gipsa-lab.grenoble-inp.fr

    www.gipsa-lab.fr/~o.sename

    BE et PROJET (19h)valuation : rapports, prsentation

    Hayate Khennouf,

    PRAG Grenoble INP / ENSE3

    Olivier Sename (PR Grenoble INP /

    GIPSA-lab)

    Christophe Brenguer (PR Grenoble

    INP / GIPSA-lab)

    Contenu Automatique

    Olivier Sename 2013

    Mthodes danalyse et de commande des systmes dynamiques/ Methods for analysis and control of dynamical systems(12h CM) valuation : DS

    Organisation

    5. Specific issues in control design

    - Time-delay- Actuator saturation

    4. Control design- Root locus design- Frequency design

    method

    3. Tools for performance analysis

    - Sensitivity functions- Robustness

    2. Modelling- Physisal equations- Linear/non linear

    systems

    1. Introduction - Problems- Applications

    7. Towards digital control

    - Discrete-time systems

    - Sampling problems

    Olivier Sename 2013

    BE et PROJET (19 h)valuation : rapports

    Objectif : illustrer, la mthodologie de lAutomatique par des applications

    typiques E3

    (travail en binme)

    + Bureaux dtudes : 8 h Conception dun systme de rgulation de

    temprature dans les btiments intelligents

    Modlisation (4 h)+Commande (2 h)+Analyse (2 h)

    Organisation

    + Projet : 8 h Analyse et commande dun incinrateur de boue en vue de la

    matrise des missions de Nox

    Analyse (4 h)+Commande (4 h)

    prsentation : 3H

  • 09/02/2015

    2

    Olivier Sename 2013

    Improved control is a key for advanced technology to:

    enhance product quality

    ensure waste and energy minimization

    allow for environmental protection

    provide a greater yield

    defer costly plant upgrades

    guarantee higher safety margins

    reduce global cost

    ..

    Why automatic control ?

    Today:

    More complex systems (many sensors, actuators )

    Higher requirements

    Olivier Sename 2013

    THE CONTROL SYSTEM DESIGN

    Goodwin et al, 01 : Success in control engineering depends on taking a holistic viewpoint. Some of the issues are :

    plant, i.e. the process to be controlled

    objectives

    sensors

    actuators

    communications

    computing

    algorithms

    architectures and interfacing

    accounting for disturbances and uncertainties

    Olivier Sename 2013

    THE CONTROL SYSTEM DESIGN

    Skogestad and Postlewaite, 96: The process of designing a control system makes many demands of the engineering team. The steps to be followed are:

    Plant study and modelling

    Determination of sensors and actuators (measured and controlled outputs, control inputs)

    Performance specifications

    Control design

    Simulation tests

    Implementation .

    Olivier Sename 2013

    THE CONTROL SYSTEM DESIGNSteps :

    Controlmodel

    Industrial and academic

    performances specifications

    Controlsynthesis

    Identitification and/or Modelling: 1. Formulate a nonlinear state-space model based on physical knowledge.2. Determine the steady-state operating point about which to linearize.3. Introduce deviation variables and linearize the model.

    needs good system knowledgeneeds criteria choice

    Us of various methods:Internal model control, Pole

    placementPredictive control, LQ control

    Hinf control ..

  • 09/02/2015

    3

    Olivier Sename 2013

    INTRODUCTION

    Modern industrial plants have sophisticated control systems crucial to their successful operation

    Robotics

    Process engineering : water, nuclear, chemical plants

    Oil & gas industry

    Aerospace

    Olivier Sename 2013

    Transport

    Olivier Sename 2013

    Automotive industry

    Intelligent highways

    SI and Diesel engine controlSuspension controlBraking controlGlobal chassis controldriver supervision.

    Transport

    Olivier Sename 2013

    AUTOMOTIVE CONTROLSome actual important fields of investigation concern:

    1. Environmental protection (Limiting of pollutant emissions )

    Engine controlAutomatic drivingTraffic optimisationEnergy consumption optimisationElectrical and Hybrid vehicles

    2. Road safety and monitoring

    Braking in dangerous situationsDetection of critical situationsChassis controlTraffic controlDriver assistance (stop & start, anti-collision)by wire technologyDiagnosis of embedded system

  • 09/02/2015

    4

    Olivier Sename 2013

    European norms for pollutant emission

    Olivier Sename 2013

    Engine control

    injection control (Common Rail) idle-speed control air to fuel ratio control cylinder balancing Torque control throttle control EGR + VGT driveline control Post-treatment Energy recovery Downsizing

    Olivier Sename 2013

    Ex: Le systme dinjection Common Rail

    Olivier Sename 2013

    Modlisation Common Rail

    Injecteurs

    PompeHP

    Actionneur de

    remplissage

    Actionneur de

    dcharge

    Rail

    Uimv

    Uhpv

    pulse Pressionrail

    Qppe

    Qinj

    Qhpv

  • 09/02/2015

    5

    Olivier Sename 2013

    ModlisationActionneur de dcharge

    Circuitmagntique

    Circuitlectrique

    SystmeMasseressort

    Systmehydraulique

    tension courant force position dbit

    [V] [A] [N] [m] [m3.s-1]

    Forcehydraulique

    Force dejet

    pression[Pa]

    [Pa]

    pression

    [Pa]

    Olivier Sename 2013

    ModlisationRail

    Le rail est un intgrateur

    La pression du carburant volue en fonction du signe de la diffrence des dbits entrant et sortant.

    V : volume HP (rail, tubes, etc.) K : coefficient de compressibilit T : temprature du carburant

    Olivier Sename 2013

    ESP: Electronic Stability Program

    AUTOMOTIVE CONTROL

    Olivier Sename 2013

    ESP: Electronic Stability Program

    AUTOMOTIVE CONTROL

  • 09/02/2015

    6

    Olivier Sename 2013

    SINGLE-TRACK MODEL: equations

    Dynamic equation of lateral motion:

    ( ) ( ) trtfrfs FFVmmm +=+++ &&..

    Wheel sideslip angles:

    =

    +=

    &

    &

    V

    lV

    l

    rr

    ff

    f

    Longitudinal CG velocity V is constant

    Small angles

    Linear lateral tire forces: Fti=- C.i (i=f front; i=r rear)

    f

    yr

    CG

    lr

    lf

    xr

    carVr

    ( )zdM,&

    f

    r

    Ftr

    Ftf

    ( ) zdrtrftfrrffzz MlFlFlmlmI +=++ ..... 22 &&Dynamic equation of yaw motion:

    Olivier Sename 2013

    AUTOMOTIVE CONTROLGlobal Chassis control or Active Body Control :

    Active chassis control system to increase driving comfort and safety Compensation of pitching and rolling motions Active leveling and damping regulation depending on the condition of the road, manner of driving and driver input

    Olivier Sename 2013

    THE FULL VEHICLE MODEL CONCEPT (1/3)

    z0

    4+3 dof :

    Bounce zs

    Pitch

    Roll

    4 vertical musdisplacements

    3+4+2 inputs:

    3 ms disturbances

    4 road profiles z0

    2 horizontal accelerations ax, ay

    4 control inputs

    Damper forces

    Olivier Sename 2013

    THE FULL VEHICLE MODEL CONCEPT (2/3)

    3 dof :

    Longitudinal vx

    Lateral vy

    Yaw st

    6 external inputs:

    Lateral dist Fyd

    Yaw dist Mzd

    4 tire loads Fzt

    6 control inputs

    Steering angle v (front + rear ?)

    wheel braking

    torques

    Only lateral tire Paceijka model(depends on Fzt)

  • 09/02/2015

    7

    Olivier Sename 2013

    THE FULL VEHICLE MODEL CONCEPT (3/3)

    Full car vertical model

    Full car hotrizontalmodel

    7 + 3 dof

    10 control inputs

    Fzd MydMxd

    Olivier Sename 2013

    Development and integration of new mechatronics subsystems

    Olivier Sename 2013

    AUTOMOTIVE CONTROL

    Olivier Sename 2013

    Aerospace

  • 09/02/2015

    8

    Olivier Sename 2013

    Philippe GOUPIL, Flight Control System Engineer, Airbus France (Runion GT S3, GDR MACS, 2007)

    Olivier Sename 2013

    Philippe GOUPIL, Flight Control System Engineer, Airbus France (Runion GT S3, GDR MACS, 2007)

    Olivier Sename 2013

    Philippe GOUPIL, Flight Control System Engineer, Airbus France (Runion GT S3, GDR MACS, 2007)

    Olivier Sename 2013

    Robotics, micro and

    nanosytems

  • 09/02/2015

    9

    Olivier Sename 2013

    Robotics for manufacturing

    Olivier Sename 2013

    Biped Robotics

    Olivier Sename 2013

    Robotics for Marine technology

    Olivier Sename 2013

    Robotique mdicale

    asservissements visuels (exploitent la dynamique du robot manipulateur. )

    -Compensation des mouvements cardiaques

    Robot porte endoscope TIMC / INP G

  • 09/02/2015

    10

    Olivier Sename 2013

    Quadrirotor helicopterSurveillance des fissures dans les btiments ou dans les ouvragesSurveillance des lignes Haute tension Recherche de personnes

    industrie du jouet pollinisation artificielle

    Olivier Sename 2013

    FLYING ROBOTS

    Raffaelo DAndrea ETH Zurich : vimeo.com/110346531

    Olivier Sename 2013

    Water industry

    Olivier Sename 2013

    Hydraulic Networks

    - Open Channel and mixt irrigation systems

    - Minimising Water Losses vsMatching Customer Needs

    - Nonlinear Modelling and Control

    - Fault detection

    An irrigation Network : Canal de la Bourne (near Grenoble)

  • 09/02/2015

    11

    Olivier Sename 2013

    Les apports du Systme dInformation

    Aujourdhui : 1 systme dinformation par acteur Contrle / Commande Optimisation, simulation Prvision

    Demain : 1 systme dinformation global pour optimiser la gestion de cette ressource commune Planification de son utilisation Anticipation des excs et des manques deau Anticipation des consquences de ces excs et manques sur :

    La production dlectricit Lirrigation La navigation Lalimentation en eau potable Lalimentation des industriels Les rejets autorises La faune et la flore

    Olivier Sename 2013

    La production deau potable

    Principales fonctions lies la gestion de leau : Calcul des consommations prvisionnelles laboration des programmes de pompage Optimisation du remplissage des rservoirs en minimisant les cots

    dnergie Calcul des bilans hydrauliques et chimiques Surveillance des grandeurs (autonomie, temps sjour, corrlations,

    etc.) Calcul des volumes mis en distribution, surveillance et dtection des

    fuites

    Olivier Sename 2013

    Le traitement des eaux uses

    Principales fonctions lies la gestion de leau : Surveillance des coulements des effluents Optimisation des flux par temps de pluie Calculs des dbits pour quantifier les dversements des eaux

    uses en rivire Surveillance de la qualit des eaux rejetes en rivire Traitements des boues

    Eaux rsiduelles urbaines Eviter les problmes due lincinration (mission de gaz)

    Olivier Sename 2013

    Energy

  • 09/02/2015

    12

    Olivier Sename 2013

    Electrical Networks

    - Stabilisation of transport networks (inter-area oscillations)

    - Maximisation of Power Transfer

    - Optimal Sensor and Actuator Placement

    - Local Control of FACTS

    - Fault detectionA four machine agragated network

    G en 11

    ~

    ~ ~

    G en 1

    G en 2

    G en 12

    ~

    Zon e 1

    Zon e 2

    PS S

    R FC

    P M U

    PM UP M U

    P M U

    S PM

    S PMS PM

    SP M

    Z/16 Z/8 Z/5 Z/4

    1000

    1100

    1200

    1300

    1400

    1500

    1600

    Impdance de la l ligne

    Ptransit

    (MW)

    AVR

    1-PSS

    1-PSS/2-PMU

    MAX

    A 29 Machine Network

    sec.

    @+100MW@nominal

    MW

    Olivier Sename 2013

    Wind turbines

    Simulation:Full ADAMS model includes 193 DOFs to represent fully flexible tower, drive-train, and blade components

    Problems :Different operating conditions according to the wind speed

    Control objectives:Maximize power Enhance damping in the first drive train torsion mode design a smooth transition different modes ensure a trouble-free control system (reliability, fault diagnosis)Prevent runaway

    Controled oriented model:Linear electro-mechanical equations (aerodynamics, transmission, generator)

    Olivier Sename 2013

    Intelligent buildings

    Olivier Sename 2013

    Intelligent buildings

  • 09/02/2015

    13

    Olivier Sename 2013

    Intelligent buildings

    High comfort level: Learn the comfort zone from the users preference, and guarantee a high comfort level (thermal, air quality and illuminance) and good dynamic performance. Energy savings: Combine the comfort conditions control with an energy saving strategy. Air quality control: Provide CO2-based demand-controlled ventilation (DCV) systems.

    Goals of an intelligent management system for energy and comfort (Dounis, Energy&Building 2009) :

    Shading systems, to control incoming solar radiation and natural light. Windows opening for natural ventilation or mechanical ventilation systems, to regulate natural airflow and indoor air change, thus affecting thermal comfort and indoor air quality. Electric lighting systems. Auxiliary heating/cooling systems.

    Satisfaction of the above requirements demands control of the following actuators/effectors:

    Olivier Sename 2013

    Intelligent buildings

    =2

    1

    Tdsp Ex: structure of the building components within the airflow control system :

    Structure of the entire ventilation unit control system integrated with the temperature control and airflow

    control :

    Olivier Sename 2013

    Intelligent buildings

    Concept of the airflow control system :

Recommended

View more >