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

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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

  • Responsible Party:

    • Solmaz Sajjadi-Kia

  • Collaborators

    • Thanh Nguyen

    • Sharad Sirivastada

    • Emre Kose

  • Support

    • NSF Grants

    • US D. of Ed GAANN Grants


  • Surveys

    Surveys

    • 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

    • 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

    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

    • 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)

    • 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

    • 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

    • 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

    • 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

    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

    • 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

    x2

    x1

    Analysis

    2

    Wmax>Wnom

    Max β

    Wnom=(1/β)1/2


    Synthesis

    2

    3

    Safe

    1

    Nom

    1

    2

    3

    Synthesis

    Wmax>Wnom


    Full state feedback control acc 07

    Full State-Feedback Control (ACC 07)

    • Synthesis (Wmax>Wnom)

    Key condition

    MIN gamma or δ

    FSAFE=XQ-1


    Safe switch condition

    Safe Switch Condition

    Ensures Boundedness


    Scheduling

    Scheduling

    • Conservatism

    1)

    2) Elliptic invariant set is conservative


    Scheduling1

    Scheduling

    • Scheduling: Putting Intermediate Controllers


    Full state feedback control

    Full State-Feedback Control

    • 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)

    WLOG Assume

    Fact:

    Switch Condition


    A typical result

    A Typical result


    Full state feedback control1

    Full State-Feedback Control

    • Example

    Wnom=2.76

    Possible to be exposed to Wmax=15


    Full state feedback control2

    Full State-Feedback Control


    Full state feedback control3

    Full State-Feedback Control

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


    Full state feedback control4

    Full State-Feedback Control

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

    Switch history


    Output feedback example

    Output Feedback Example

    Given nominal controller in the form

    Analysis: Wnom=1.55

    Synthesis: Wmax=5


    Output feedback example one safe controller

    Output Feedback Example (One Safe Controller)


    Output feedback example scheduled safe controller

    Output Feedback Example (Scheduled Safe Controller)


    Output feedback

    Output Feedback


    Future work

    Future Work

    • 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 …….


    Scheduling in anti windup controllers state and output feedback cases

    Going the other way around:

    • 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


    Scheduling in anti windup controllers state and output feedback cases

    Static Anti-windup

    d

    y

    r

    u

    +

    Sat(.)

    K(s)

    P(s)

    -

    +

    -

    AW

    q


    Scheduling in anti windup controllers state and output feedback cases

    Static Anti-windup

    Stability and Wellposedness: Small Gain Theorem


    Scheduling in anti windup controllers state and output feedback cases

    Static Anti-windup

    Performance (stability): L2 Gain

    Q>0 ,

    M>0

    Λ=XM-1


    Scheduling in anti windup controllers state and output feedback cases

    Example (Static Anti-windup)

    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.


    Scheduling in anti windup controllers state and output feedback cases

    Example (Static Anti-windup)

    System output and input history when anti-windup augmentation applied


    Scheduling in anti windup controllers state and output feedback cases

    Over-saturated Anti-windup

    d

    y

    r

    u

    +

    Sat(.)

    K(s)

    P(s)

    -


    Scheduling in anti windup controllers state and output feedback cases

    Over-saturated Anti-windup

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

    Q>0


    Scheduling in anti windup controllers state and output feedback cases

    Over-saturated Anti-windup


    Scheduling in anti windup controllers state and output feedback cases

    Over-saturated Anti-windup


    Scheduling in anti windup controllers state and output feedback cases

    Over-saturated Anti-windup

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

    Q>0

    Λ=XM-1


    Scheduling in anti windup controllers state and output feedback cases

    Over-saturated Anti-windup

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

    Traditional Anti-windup:

    Over-saturated Anti-windup:


    Scheduling in anti windup controllers state and output feedback cases

    Example (Over-saturated Anti-windup)

    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.


    Scheduling in anti windup controllers state and output feedback cases

    Example (Over-saturated Anti-windup

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


    Scheduling in anti windup controllers state and output feedback cases

    Example (Over-saturated Anti-windup)

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


    Scheduling in anti windup controllers state and output feedback cases

    Summary

    • 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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