6,349 research outputs found
Exploiting the Temporal Logic Hierarchy and the Non-Confluence Property for Efficient LTL Synthesis
The classic approaches to synthesize a reactive system from a linear temporal
logic (LTL) specification first translate the given LTL formula to an
equivalent omega-automaton and then compute a winning strategy for the
corresponding omega-regular game. To this end, the obtained omega-automata have
to be (pseudo)-determinized where typically a variant of Safra's
determinization procedure is used. In this paper, we show that this
determinization step can be significantly improved for tool implementations by
replacing Safra's determinization by simpler determinization procedures. In
particular, we exploit (1) the temporal logic hierarchy that corresponds to the
well-known automata hierarchy consisting of safety, liveness, Buechi, and
co-Buechi automata as well as their boolean closures, (2) the non-confluence
property of omega-automata that result from certain translations of LTL
formulas, and (3) symbolic implementations of determinization procedures for
the Rabin-Scott and the Miyano-Hayashi breakpoint construction. In particular,
we present convincing experimental results that demonstrate the practical
applicability of our new synthesis procedure
Fluent temporal logic for discrete-time event-based models
Fluent model checking is an automated technique for verifying that an event-based operational model satisfies some state-based declarative properties. The link between the event-based and state-based formalisms is defined through fluents which are state predicates whose value are determined by the occurrences of initiating and terminating events that make the fluents values become true or false, respectively. The existing fluent temporal logic is convenient for reasoning about untimed event-based models but difficult to use for timed models. The paper extends fluent temporal logic with temporal operators for modelling timed properties of discrete-time event-based models. It presents two approaches that differ on whether the properties model the system state after the occurrence of each event or at a fixed time rate. Model checking of timed properties is made possible by translating them into the existing untimed framework. Copyright 2005 ACM
Robust Temporal Logic Model Predictive Control
Control synthesis from temporal logic specifications has gained popularity in
recent years. In this paper, we use a model predictive approach to control
discrete time linear systems with additive bounded disturbances subject to
constraints given as formulas of signal temporal logic (STL). We introduce a
(conservative) computationally efficient framework to synthesize control
strategies based on mixed integer programs. The designed controllers satisfy
the temporal logic requirements, are robust to all possible realizations of the
disturbances, and optimal with respect to a cost function. In case the temporal
logic constraint is infeasible, the controller satisfies a relaxed, minimally
violating constraint. An illustrative case study is included.Comment: This work has been accepted to appear in the proceedings of 53rd
Annual Allerton Conference on Communication, Control and Computing,
Urbana-Champaign, IL (2015
A Learning Based Approach to Control Synthesis of Markov Decision Processes for Linear Temporal Logic Specifications
We propose to synthesize a control policy for a Markov decision process (MDP)
such that the resulting traces of the MDP satisfy a linear temporal logic (LTL)
property. We construct a product MDP that incorporates a deterministic Rabin
automaton generated from the desired LTL property. The reward function of the
product MDP is defined from the acceptance condition of the Rabin automaton.
This construction allows us to apply techniques from learning theory to the
problem of synthesis for LTL specifications even when the transition
probabilities are not known a priori. We prove that our method is guaranteed to
find a controller that satisfies the LTL property with probability one if such
a policy exists, and we suggest empirically with a case study in traffic
control that our method produces reasonable control strategies even when the
LTL property cannot be satisfied with probability one
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