Scheduling in anti windup controllers state and output feedback cases
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Scheduling in Anti-windup Controllers: State and Output Feedback Cases. Faryar Jabbari Mechanical an Aerospace Engineering Department University of California, Irvine (UCI) November 13, 2007. Thanks. Responsible Party: Solmaz Sajjadi-Kia Collaborators Thanh Nguyen Sharad Sirivastada

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Scheduling in anti windup controllers state and output feedback cases

Scheduling in Anti-windup Controllers: State and Output Feedback Cases

Faryar Jabbari

Mechanical an Aerospace Engineering Department

University of California, Irvine (UCI)

November 13, 2007


Thanks
Thanks Feedback Cases

  • Responsible Party:

    • Solmaz Sajjadi-Kia

  • Collaborators

    • Thanh Nguyen

    • Sharad Sirivastada

    • Emre Kose

  • Support

    • NSF Grants

    • US D. of Ed GAANN Grants


  • Surveys
    Surveys Feedback Cases

    • IJRNC: Michele and Bernstein, eds. (1995)

    • IJRNC: Saberi and Stoorvogel, eds. (1999)

    • Franco Blanchini's review article(TAC, 2000)

    • Tarbouriech, et al., Springer, (1999)

    • Kapila and Grigoriadis, Marcel Dekker (2003)

    • IJRNC: Saberi and Stoorvogel, eds. (2004)

    • Much more!


    Motivation
    Motivation Feedback Cases

    • Old Problem: actuator limitation is ubiquitous

    • `Safe' (Low gain) LTI controllers are often excessively conservative

    • Broad approaches:

      • Oldest: Anti-windup

        • Nominal high performance controller (linear design)

        • Anti-windup augmentation

      • Relatively new: Explicit account of saturation nonlinearity

        • Nonlinear design or low gain designs


    Current techniques to deal with saturation

    Direct Approach Feedback Cases

    Considers the controllers limitation at the very beginning of the design

    Anti-windup

    Augmentation on top of the nominal controller designed without considering controller bound

    Current Techniques to Deal with Saturation

    ||W||2<W2max


    Anti windup
    Anti-windup Feedback Cases

    • Starting in 60's (Sandberg, among many)

    • Huge body or work, at times intuitive or even ad-hoc

    • Many attempts at unifying, interpreting of all techniques

    • New rigorous stability and performance results

      • Morari group

      • Teel group

      • Many others (literally too numerous to review!)

      • Positivity, small gain, LMI's, etc.


    Anti windup continued
    Anti windup (continued) Feedback Cases

    • High performance when no saturation

    • Ideal for `occasional' saturation

    • Relatively weak performance when in saturation

    • Typically open loop performance -- so open-loop stability `often' needed (exceptions: Tell, et al. ACC-05, and a few references there)

    • A single controller/augmentations for all saturation levels (even almost zero?), disturbances, tracking signals, etc.


    Explicit direct approach
    Explicit – direct – approach Feedback Cases

    • Low-high gain (Saberi and Lin, 199x)

    • Early LPV : Nguyen and Jabbari (1999, 2000), Scorletti, et al (2001)

    • Scheduling: Older work (full state):

      • Gutman and Hagander (1985)

      • Wredenhagen and Belanger (1994)

      • Megretski (1996 IFAC)

    • Scheduling: Recent work}

      • Lin (1997), a little bit of observer

      • Teel (1995), Tarboriech, et al (1999, 2000) - state feedback

      • Wu, Packard and Grigoriadis (2000) - pure LPV

      • Stoustrup (2005-07)

      • Kose and Jabbari (2002, 2003)


    Direct approach
    Direct Approach Feedback Cases

    • Stability and performance guarantees

    • Performance not strong in small signal operation

      `Some' have nice properties:

    • A family of controllers (rather than one)

    • Computationally tractable (e.g., a convex search)

    • High actuator utilization

    • Performance guarantees dependent on actuator size and disturbance estimate

    • Approach flexible to incorporate different design approaches, actuator rate limits, state constraints, tracking, etc.


    Basic idea 1 combining with scheduling
    Basic Idea 1: Combining with Scheduling Feedback Cases

    • Start with a nominal controller (from somewhere!)

    • Keep it as long as possible

    • Once saturated, switch to a new (family of) of controller (s) that can avoid saturation but can provide guaranteed stability and performance

    • Make sure there are no `cracks' or escape routs!

      Assumptions:

    • Full state or full order controllers (relaxed later)

    • Disturbance attenuation problem (for now)

    • Information of worst case disturbance (e.g. energy or peak)

    • A small number of controllers (for now -- technical detail)


    System and controllers
    System and Controllers Feedback Cases

    Disturbance attenuation problem (ACC & CDC 07)

    Open loop system

    Assumption: known wmax (Possibly conservatively)

    Requirement: closed loop stability, boundedness (e.g., ISS), acceptable performance

    Key: Use of ellipsoids

    Given Nominal Controller

    State Feedback

    or

    Output Feedback


    A simple safe controller
    A simple `safe’ controller Feedback Cases

    • Objective:

      -Use Knom(s) as long as possible,

      -Once Knom(s) saturates, implement Ksafe(s) that ensure reasonable

      behavior

    • Steps:

      - Analysis:

      What is the largest disturbance the system can tolerate?

      Wnom

      - Synthesis

      Constructing the safe controller


    Analysis

    x Feedback Cases2

    x1

    Analysis

    2

    Wmax>Wnom

    Max β

    Wnom=(1/β)1/2


    Synthesis

    2 Feedback Cases

    3

    Safe

    1

    Nom

    1

    2

    3

    Synthesis

    Wmax>Wnom


    Full state feedback control acc 07
    Full State-Feedback Control (ACC 07) Feedback Cases

    • Synthesis (Wmax>Wnom)

    Key condition

    MIN gamma or δ

    FSAFE=XQ-1


    Safe switch condition
    Safe Switch Condition Feedback Cases

    Ensures Boundedness


    Scheduling
    Scheduling Feedback Cases

    • Conservatism

    1)

    2) Elliptic invariant set is conservative


    Scheduling1
    Scheduling Feedback Cases

    • Scheduling: Putting Intermediate Controllers


    Full state feedback control
    Full State-Feedback Control Feedback Cases

    • SchedulingWN=WL<WN-1<…W2<W1=Wmax ; QN=Qnom

    For i=1:N-1

    Min

    Ki =Xi Qi-1 i=1,2,..N


    Output feedback cdc 07
    Output Feedback (CDC 07) Feedback Cases

    WLOG Assume

    Fact:

    Switch Condition


    A typical result
    A Typical result Feedback Cases


    Full state feedback control1
    Full State-Feedback Control Feedback Cases

    • Example

    Wnom=2.76

    Possible to be exposed to Wmax=15



    Full state feedback control3
    Full State-Feedback Control Feedback Cases

    W1=Wmax=15; W2=10; W3=5; W4=Wnom=2.76


    Full state feedback control4
    Full State-Feedback Control Feedback Cases

    Sys. res. in scheduled case vs. the original sys. Res.

    Switch history


    Output feedback example
    Output Feedback Example Feedback Cases

    Given nominal controller in the form

    Analysis: Wnom=1.55

    Synthesis: Wmax=5


    Output feedback example one safe controller
    Output Feedback Example Feedback Cases(One Safe Controller)


    Output feedback example scheduled safe controller
    Output Feedback Example Feedback Cases(Scheduled Safe Controller)


    Output feedback
    Output Feedback Feedback Cases


    Future work
    Future Work Feedback Cases

    • Continuous (e.g., spline based) family of controllers: messy but straight forward (will place a bound on how fast the gain can be increased)

    • Mismatch in order of controller and plant: augment the order of the controller

    • Tracking

    • Non-ellipsoidal sets

    • Adding scheduling to the traditional anti-windup scheme …….


    Going the other way around: Feedback Cases

    • Start with a basic Ant-windup set up

    • Use Different anti-windups for different levels of saturation

    • Shouldn’t small saturation leave to better performance guarantee than a sever saturation? (Ans: yes!)

    • But first: Something interesting shows up!!

    • Let us review the basic `Static’ anti-windup set up


    Static Anti-windup Feedback Cases

    d

    y

    r

    u

    +

    Sat(.)

    K(s)

    P(s)

    -

    +

    -

    AW

    q


    Static Anti-windup Feedback Cases

    Stability and Wellposedness: Small Gain Theorem


    Static Anti-windup Feedback Cases

    Performance (stability): L2 Gain

    Q>0 ,

    M>0

    Λ=XM-1


    Example (Static Anti-windup) Feedback Cases

    Grimm, G., Teel, A.R., and Zaccarian, L., “Results on Linear LMI-Based External Anti-windup Design”, IEEE Trans.

    on Automatic Control, Vol. 48, No. 9, Sep. 2003.


    Example (Static Anti-windup) Feedback Cases

    System output and input history when anti-windup augmentation applied


    Over-saturated Anti-windup Feedback Cases

    d

    y

    r

    u

    +

    Sat(.)

    K(s)

    P(s)

    -


    Over-saturated Anti-windup Feedback Cases

    Performance of saturated system for G(t)є [g,1]

    Q>0




    Over-saturated Anti-windup Feedback Cases

    Performance (stability) of Over-saturated Anti-windup: L2 Gain

    Q>0

    Λ=XM-1


    Over-saturated Anti-windup Feedback Cases

    System response: Anti-windup, Over-saturated Anti-Windup, Unconstrained Nominal

    Traditional Anti-windup:

    Over-saturated Anti-windup:


    Example (Over-saturated Anti-windup) Feedback Cases

    Simulation example of F8 aircraft

    Elevator, limited to ±25 degree

    Flapron, limited to ±25 degree

    input

    Pitch angle

    Flight path angle

    output

    Kapasouris, P., Athans, M., and Stein, G., “Design of Feedback Control Systems for Stable Plants with Saturating

    Actuators”, Proceeding of the 27th IEEE Conf. on Decision and Control, Austin, TX, December 1988.


    Example (Over-saturated Anti-windup Feedback Cases

    System response: Unconstrained Nominal, Anti-windup, Unconstrained Nominal


    Example (Over-saturated Anti-windup) Feedback Cases

    System response: Anti-windup, Over-saturated Anti-Windup, Unconstrained Nominal


    Summary Feedback Cases

    • Tradeoff between `matched uncertainty’ vs better performance guarantee

    • Dynamic Anti-windup case: Reasonably straight forward: the uncertainly is of the LPV (self-scheduled) variety – constant Lyapunov functions suffice

    • Combine `over saturation’ and scheduling is next!


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