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Hybrid Systems

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Title: Hybrid Systems


1
Hybrid Systems
  • Presented by
  • Arnab De
  • Anand S

2
An Intuitive Introduction to Hybrid Systems
  • Discrete program with an analog environment.
  • What does it mean?
  • Sequence of discrete steps in each step the
    system evolves continuously according to some
    dynamical law until a transition occurs.
    Transitions are instantaneous.

3
A Motivating Example Thermostat
  • The heater can be on or off.
  • When the heater is on, the temperature increases
    continuously according to some formula.
  • When the heater is off, the temperature
    decreases.
  • Thermostat keeps the temperature within some
    limit by putting the heater on or off.

4
Formal Model of Hybrid Systems
  • Model Hybrid Systems as graphs
  • Vertices represent continuous activities.
  • Edges represent transition.

5
Formal Model contd
  • H (Loc, Var, Lab, Edg, Act, Inv)
  • Loc finite set of vertices (locations)
  • Var finite set of real-valued variables.
  • A valuation v(x) assignes a real value to each
    variable. V is the set of valuations.
  • A state is a pair (l, v), l ? Loc, v ? V.

6
Formal Model contd
  • Lab finite set of synchronization labels,
    containing the stutter label t
  • Edg finite set of edges (transitions). e
    (l, a, µ, l)
  • Stutter transition (l, µ, IdCon, l).
  • Act set of activities, maps non-negative reals
    to valuations.
  • Inv set of invariants at a location.

7
Time-deterministic hybrid system
  • There is at most one activity for each location
    and each valuation such that
  • f(0) v
  • Denoted by flv.

8
Runs of a Hybrid System
  • A state can change in two ways
  • Discrete and Instantaneous transition that
    changes both l and v.
  • Time delay that changes only v according to
    activities of the location.
  • Some transition must be taken before the
    invariant becomes false.
  • Run

9
Thermostat example revisited
10
Hybrid Systems as Transition Systems
11
Composition of Hybrid Systems
12
Linear Hybrid System
  • A time-deterministic hybrid system is linear if
  • The activity functions are of the form
  • The invariant for each location is defined by a
    linear formula over Var.

13
Linear Hybrid System contd
  • For all transitions, the transition relation µ is
    defined by a guarded set of non-deterministic
    assignments
  • If ax ßx, we write

14
Special Cases of Linear Hybrid Systems
  • If Act(l,x) 0 for all locations, then x is a
    discrete variable.
  • A discrete variable x is a proposition if
  • for all transitions.
  • A finite-state system is a linear hybrid system
    all of whose variables are propositions.

15
Special cases contd
  • If Act(l,x) 1 for each location and
  • for each transition, then x is a clock.
  • A timed automaton is a LHS all of whose variables
    are either propositions or clocks and the linear
    expressions are boolean combination of
    inequalities of the form xc or x-yc (c
    non-negative integer).

16
Special cases contd
  • If for each location and
  • for each edge, then x is an
    integrator. An integrator system is a LHS all of
    whose variables are propositions or integrators.

17
Example of LHS Leaking Gas Burner
18
Reachability problem
  • Given two states, does there exist any run that
    starts at first state and ends at another.
  • Verification of some invariant property is
    equivalent to the reachability question.
  • Reachability is undecidable in general but
    decidable for some special cases.

19
Verification of Linear Hybrid Systems
  • H(Loc,Var,lab,Edg,Act,Inv)
  • Do a reachability analysis
  • Iteratively find out the reachable states
  • Forward analysis computes step successors of a
    given set of states
  • Backward analysis

20
Forward analysis
  • Forward time closure
  • Set of valuations reachable from some v ?P by
    letting time progress
  • .
  • (l,v) ?t (l,v)
  • Post condition of P w.r.t an edge e,
  • The set of valuations reachable from v ? P by
    executing transition e
  • .
  • (l,v) ?a (l,v)

21
Forward Analysis (contd)
  • Region A set of states
  • Define (l,P) (l,v) v ? P
  • Extension to regions for RUl?Loc(l,Rl)

22
Forward Analysis (contd)
  • A symbolic run on H is (in)infinite sequence
  • ? (l0,P0)(l1,P1),(li,Pi)
  • .
  • The region (li,Pi) is the set of states reachable
    from (l0,v0) after executing e0,.ei-1
  • Every run of H can be represented by some
    symbolic run of H
  • Given I (subset of S), the reachable region (I?)
    is the set of states reachable from I
  • .

23
Forward Analysis (contd)
  • Reachable region is least fixed point of
  • .
  • Or Rl of valuations for l ? Loc if lfp of
  • .
  • ? set of valuations that satisfy ?
  • ? is a linear formula
  • PÍv is linear if P? for some ?

24
Forward Analysis (contd)
  • For linear H, if P is linear, then so is ltPgtl?
    and posteP
  • pc ? Var is a control var with range Loc
  • A region R is linear of all Rl(?l) are linear
  • Region R is defined by
  • Do successive approx.
  • Terminate for simple mutirated timed systems

25
Example leaking gas burner
  • .
  • .

26
Backward Analysis
  • Backward time closure
  • .
  • Precondition
  • .
  • Extension

27
Backward Analysis (contd)
  • Initial region
  • .
  • Equations Initial region if lfp
  • .
  • .
  • ltPgtl? and preeP are linear
  • In example, we find set of states from which
    ?Ry60? 20z y is reachable. We get null set

28
Model Checking (Timed CTL)
  • Check if H satisfies a requirement expressed in
    real-time temporal logic
  • Define C (disjoint with Var)
  • State predicate is a linear formula over Var U C
  • The grammer
  • .
  • ? is state predicate and z?C
  • Formulas of TCTL are interpreted over state space
    of H

29
Timed CTL (contd)
  • Clocks can be used to express timing constraints
  • .
  • A run ?s0 ?t0 s1 ?t1
  • For a state ?i(li,vi), position ?(i,t)
  • (0t ti)
  • Positions are lexicographically ordered
  • .

30
TCTL (contd)
  • For all positions ?(i,t)
  • Clock valuation ? C?R0
  • ?t and ?z0
  • Extended state (s, ?)

31
Model Checking (contd)
  • (s, ?) F, if

32
Model Checking algorithm
  • s F, of (s,?) F for all ? evaluations
  • Computes Characteristic set F
  • (l,v) ? (R ? R) iff
  • Single step until operator
  • If R and R are linear so is R ? R
  • Thus the modalities can be computed iteratively
    using ?
  • Will terminate in simple multirate timed system

33
Examples
  • F?U F computed as UiRi with
  • ??c F computed as UiRiz0 with

34
Thank you
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