CS 367: Model-Based Reasoning Lecture 7 (02/05/2002) Gautam Biswas.

Slides:



Advertisements
Similar presentations
Use Case Diagrams Damian Gordon.
Advertisements

Theory of Computing Lecture 23 MAS 714 Hartmut Klauck.
Language and Automata Theory
Partial Order Reduction: Main Idea
1 Fault Diagnosis for Timed Automata Stavros Tripakis VERIMAG.
C O N T E X T - F R E E LANGUAGES ( use a grammar to describe a language) 1.
CS6133 Software Specification and Verification
Closure Properties of CFL's
CS 367: Model-Based Reasoning Lecture 2 (01/15/2002)
Use Case & Use Case Diagram
Supervisory Control of Hybrid Systems Written by X. D. Koutsoukos et al. Presented by Wu, Jian 04/16/2002.
CFGs and PDAs Sipser 2 (pages ). Long long ago…
LR-Grammars LR(0), LR(1), and LR(K).
January 7, 2015CS21 Lecture 21 CS21 Decidability and Tractability Lecture 2 January 7, 2015.
CS 603 Handling Failure in Commit February 20, 2002.
Properties of State Variables
FORMAL LANGUAGES, AUTOMATA, AND COMPUTABILITY
Parallel Scheduling of Complex DAGs under Uncertainty Grzegorz Malewicz.
1 CS 201 Compiler Construction Lecture 7 Code Optimizations: Partial Redundancy Elimination.
Diagnosis of Discrete Event Systems Meir Kalech Partly based on slides of Gautam Biswass.
ECE 877-J Discrete Event Systems 224 McKinley Hall.
CS21 Decidability and Tractability
Introduction to Computability Theory
CFGs and PDAs Sipser 2 (pages ). Last time…
1 Introduction to Computability Theory Lecture2: Non Deterministic Finite Automata Prof. Amos Israeli.
CS5371 Theory of Computation
Transparency No. 2-1 Formal Language and Automata Theory Chapter 2 Deterministic Finite Automata (DFA) (include Lecture 3 and 4)
Lecture 4&5: Model Checking: A quick introduction Professor Aditya Ghose Director, Decision Systems Lab School of IT and Computer Science University of.
1 CS 201 Compiler Construction Lecture 13 Instruction Scheduling: Trace Scheduler.
Page 1 Aalborg University Control in Discrete Event Systems.
THE OBJECT-ORIENTED DESIGN WORKFLOW Statechart Diagrams.
CS 603 Communication and Distributed Systems April 15, 2002.
FORMAL LANGUAGES, AUTOMATA AND COMPUTABILITY
Time, Clocks, and the Ordering of Events in a Distributed System Leslie Lamport (1978) Presented by: Yoav Kantor.
Lecture 4 Finite State Machine CS6133 Software Specification and Verification.
1 Introduction to Parsing Lecture 5. 2 Outline Regular languages revisited Parser overview Context-free grammars (CFG’s) Derivations.
ECE 720T5 Winter 2014 Cyber-Physical Systems Rodolfo Pellizzoni.
1 Object-Oriented Modeling Using UML (2) CS 3331 Fall 2009.
Zvi Kohavi and Niraj K. Jha 1 Memory, Definiteness, and Information Losslessness of Finite Automata.
Guide to State Transition Diagram. 2 Contents  What is state transition diagram?  When is state transition diagram used?  What are state transition.
Pushdown Automata (PDAs)
Modelling III: Asynchronous Shared Memory Model Chapter 9 by Nancy A. Lynch presented by Mark E. Miyashita.
Lecture 05: Theory of Automata:08 Kleene’s Theorem and NFA.
CS 367: Model-Based Reasoning Lecture 11 (02/19/2002) Gautam Biswas.
CIS 842: Specification and Verification of Reactive Systems Lecture Specifications: LTL Model Checking Copyright , Matt Dwyer, John Hatcliff,
CS 367: Model-Based Reasoning Lecture 5 (01/29/2002) Gautam Biswas.
1 Undecidable Problems of Decentralized Observation and Control Stavros Tripakis VERIMAG (based on [Puri,Tripakis,Varaiya-SCODES’01], [Tripakis-CDC’01],
Natallia Kokash (Accepted for PACO’2011) ACG, 31/05/ Input-output conformance testing for channel-based connectors 1.
Formal Methods for Software Engineering Part II: Modelling & Analysis of System Behaviour.
CS 203: Introduction to Formal Languages and Automata
Chapter 8 Asynchronous System Model by Mikhail Nesterenko “Distributed Algorithms” by Nancy A. Lynch.
CSC 3130: Automata theory and formal languages Andrej Bogdanov The Chinese University of Hong Kong Normal forms.
Great Theoretical Ideas In Computer Science John LaffertyCS Fall 2006 Lecture 22 November 9, 2006Carnegie Mellon University b b a b a a a b a b.
Operational Semantics Mooly Sagiv Tel Aviv University Sunday Scrieber 8 Monday Schrieber.
Equivalence with FA * Any Regex can be converted to FA and vice versa, because: * Regex and FA are equivalent in their descriptive power ** Regular language.
Parsing V LR(1) Parsers. LR(1) Parsers LR(1) parsers are table-driven, shift-reduce parsers that use a limited right context (1 token) for handle recognition.
1 Advanced Theory of Computation Finite Automata with output Pumping Lemma Theorem.
Formal Methods for Software Engineering
Context-Free Grammars: an overview
Non-deterministic Finite Automata (NFA)
High-Level Abstraction of Concurrent Finite Automata
Closure Properties for Regular Languages
CS 154, Lecture 3: DFANFA, Regular Expressions.
CHAPTER 2 Context-Free Languages
CS21 Decidability and Tractability
Using Use Case Diagrams
Lecture 5 Theory of AUTOMATA
Recap lecture 10 Definition of GTG, examples of GTG accepting the languages of strings:containing aa or bb, beginning with and ending in same letters,
Linear Time Properties
Presentation transcript:

CS 367: Model-Based Reasoning Lecture 7 (02/05/2002) Gautam Biswas

Today’s Lecture Last Lecture: Diagnoser Automata Notion of Diagnosability (Sampath paper) Supervisory Control Feedback control with supervisors: Complete and Partial Observation Specifications on Controlled Systems Today’s Lecture: Discussion of HW problems Diagnosability and I-Diagnosability Specifications on Controlled Systems Controllability Theorem

Diagnoser Automata G G obs G diag

Diagnosability

Definition: (informal) Let s be any trace generated by the system that ends in a failure event from set E fi and t is a sufficiently long continuation of s Diagnosability Diagnosability implies that every trace that belongs to the language that produces the same record of observable events as st should contain in it a failure event from E fi Along every continuation t of s one can detect the failure of type F i with finite delay, specifically in atmost n i transitions of the system after s Alternately, diagnosability requires that every failure event leads to observations distinct enough to enable unique identification of failure type with a finite delay Diagnosability must hold for all traces in L(G) that contain a failure event Relaxed definition: I-diagnosability – diagnosability condition holds only for those in which a failure is followed by certain indicator events associated with every failure type

Feedback Loop for Supervisory Control DES G S s S(s) s Assume all events are observable: s all events executed by G so far and S has seen them all How is control achieved? Controllable events of G can be dynamically enabled or disabled by S Formally, a supervisor is a function For each generated by G (supervised by S) is the set of enabled events that G can execute at it current state G cannot execute event unless it belons to S(s)

Control under Partial Observation G S S P [P(s)] Because of P supervisor cannot distinguish between s 1 and s 2, i.e., Control action under partial supervision S P : P-supervisor Control Action can change only after occurrence of an observable event; but this action happens before an unobservable event occurs P

Specifications of Controlled System Feedback supervisor S (S P ) introduced to eliminate “illegal” traces in G. Legal behavior of L(G) is L a, where a – admissible Partially observable, replace S by S P

Specifications of Controlled System L a (or L am ) obtained after accounting for all specifications of system; L am when L(G) has blocking states These specifications are themselves described by one or more (possible marked) languages, K s,i, i=1,…..,m If specification language K s,i is not given as subset of L(G) (or L m (G)), then we take

Example: Plain Old Telephone System (POTS) OFFHOOK INIT offho onho con10 con20 onho No one can call user 0 successfully if user 0 has picked up the handset Events that define call processing features: * phone i off hook * phone i on hook * request connection from user i to user j * establish connection between users i and j * forwarding calls from user i to j to k * connection cannot be established because of screening list of user j Consider 3 user telephone system Complete system model G is the shuffle of individual models Livelock occurs when: user 1 forwards his calls to user 2, user2 to user 3, and user 3 to user 1 Spec lang K s L a = L(G)  K s

Modifying Automata to Account for Illegal Behavior Illegal States in G: delete these states from G ( remove state, transitions, and perform Ac operation ) State Splitting: If spec requires remembering how state in G reached in order to determine what future behavior is legal, then split state Event Alternance: spec requires alternation of two events, build two state automata to capture this; parallel composition with G

Modifying Automata to Account for Illegal Behavior Illegal Substring: Remove all strings of L(G) that contain

Controllability Nonblocking Controllability Theorem (NCT) Consider a DES G where E uc  E is the set of uncontrollable events. Consider also the language K  L m (G), where K   There exits a nonblocking supervisor S for G such that L m (S/G) = K (  L(S/G) = K) iff the following two conditions hold: 1. [controllability] 2. [Lm(G)-closure]