11,056 research outputs found
Diagnosis and Repair for Synthesis from Signal Temporal Logic Specifications
We address the problem of diagnosing and repairing specifications for hybrid
systems formalized in signal temporal logic (STL). Our focus is on the setting
of automatic synthesis of controllers in a model predictive control (MPC)
framework. We build on recent approaches that reduce the controller synthesis
problem to solving one or more mixed integer linear programs (MILPs), where
infeasibility of a MILP usually indicates unrealizability of the controller
synthesis problem. Given an infeasible STL synthesis problem, we present
algorithms that provide feedback on the reasons for unrealizability, and
suggestions for making it realizable. Our algorithms are sound and complete,
i.e., they provide a correct diagnosis, and always terminate with a non-trivial
specification that is feasible using the chosen synthesis method, when such a
solution exists. We demonstrate the effectiveness of our approach on the
synthesis of controllers for various cyber-physical systems, including an
autonomous driving application and an aircraft electric power system
Optimality and robustness in multi-robot path planning with temporal logic constraints
In this paper we present a method for automatically generating optimal robot paths satisfying high-level mission specifications. The motion of the robot in the environment is modeled as a weighted transition system. The mission is specified by an arbitrary linear temporal-logic (LTL) formula over propositions satisfied at the regions of a partitioned environment. The mission specification contains an optimizing proposition, which must be repeatedly satisfied. The cost function that we seek to minimize is the maximum time between satisfying instances of the optimizing proposition. For every environment model, and for every formula, our method computes a robot path that minimizes the cost function. The problem is motivated by applications in robotic monitoring and data-gathering. In this setting, the optimizing proposition is satisfied at all locations where data can be uploaded, and the LTL formula specifies a complex data-collection mission. Our method utilizes Büchi automata to produce an automaton (which can be thought of as a graph) whose runs satisfy the temporal-logic specification. We then present a graph algorithm that computes a run corresponding to the optimal robot path. We present an implementation for a robot performing data collection in a road-network platform.This work was supported in part by the Office of Naval Research (grant number MURI N00014-09-1051), Army Research Office (grant number W911NF-09-1-0088), Air Force Office of Scientific Research (grant number YIP FA9550-09-1-020), National Science Foundation (grant number CNS-0834260), Singapore-MIT Alliance for Research and Technology (SMART) Future of Urban Mobility Project and by Natural Sciences and Engineering Research Council of Canada. (MURI N00014-09-1051 - Office of Naval Research; W911NF-09-1-0088 - Army Research Office; YIP FA9550-09-1-020 - Air Force Office of Scientific Research; CNS-0834260 - National Science Foundation; Singapore-MIT Alliance for Research and Technology (SMART); Natural Sciences and Engineering Research Council of Canada
Towards Cancer Hybrid Automata
This paper introduces Cancer Hybrid Automata (CHAs), a formalism to model the
progression of cancers through discrete phenotypes. The classification of
cancer progression using discrete states like stages and hallmarks has become
common in the biology literature, but primarily as an organizing principle, and
not as an executable formalism. The precise computational model developed here
aims to exploit this untapped potential, namely, through automatic verification
of progression models (e.g., consistency, causal connections, etc.),
classification of unreachable or unstable states and computer-generated
(individualized or universal) therapy plans. The paper builds on a
phenomenological approach, and as such does not need to assume a model for the
biochemistry of the underlying natural progression. Rather, it abstractly
models transition timings between states as well as the effects of drugs and
clinical tests, and thus allows formalization of temporal statements about the
progression as well as notions of timed therapies. The model proposed here is
ultimately based on hybrid automata, and we show how existing controller
synthesis algorithms can be generalized to CHA models, so that therapies can be
generated automatically. Throughout this paper we use cancer hallmarks to
represent the discrete states through which cancer progresses, but other
notions of discretely or continuously varying state formalisms could also be
used to derive similar therapies.Comment: In Proceedings HSB 2012, arXiv:1208.315
Probabilistic Plan Synthesis for Coupled Multi-Agent Systems
This paper presents a fully automated procedure for controller synthesis for
multi-agent systems under the presence of uncertainties. We model the motion of
each of the agents in the environment as a Markov Decision Process (MDP)
and we assign to each agent one individual high-level formula given in
Probabilistic Computational Tree Logic (PCTL). Each agent may need to
collaborate with other agents in order to achieve a task. The collaboration is
imposed by sharing actions between the agents. We aim to design local control
policies such that each agent satisfies its individual PCTL formula. The
proposed algorithm builds on clustering the agents, MDP products construction
and controller policies design. We show that our approach has better
computational complexity than the centralized case, which traditionally suffers
from very high computational demands.Comment: IFAC WC 2017, Toulouse, Franc
Model Predictive Control for Signal Temporal Logic Specification
We present a mathematical programming-based method for model predictive
control of cyber-physical systems subject to signal temporal logic (STL)
specifications. We describe the use of STL to specify a wide range of
properties of these systems, including safety, response and bounded liveness.
For synthesis, we encode STL specifications as mixed integer-linear constraints
on the system variables in the optimization problem at each step of a receding
horizon control framework. We prove correctness of our algorithms, and present
experimental results for controller synthesis for building energy and climate
control
Real-Time Synthesis is Hard!
We study the reactive synthesis problem (RS) for specifications given in
Metric Interval Temporal Logic (MITL). RS is known to be undecidable in a very
general setting, but on infinite words only; and only the very restrictive BRRS
subcase is known to be decidable (see D'Souza et al. and Bouyer et al.). In
this paper, we precise the decidability border of MITL synthesis. We show RS is
undecidable on finite words too, and present a landscape of restrictions (both
on the logic and on the possible controllers) that are still undecidable. On
the positive side, we revisit BRRS and introduce an efficient on-the-fly
algorithm to solve it
An Adaptive Design Methodology for Reduction of Product Development Risk
Embedded systems interaction with environment inherently complicates
understanding of requirements and their correct implementation. However,
product uncertainty is highest during early stages of development. Design
verification is an essential step in the development of any system, especially
for Embedded System. This paper introduces a novel adaptive design methodology,
which incorporates step-wise prototyping and verification. With each adaptive
step product-realization level is enhanced while decreasing the level of
product uncertainty, thereby reducing the overall costs. The back-bone of this
frame-work is the development of Domain Specific Operational (DOP) Model and
the associated Verification Instrumentation for Test and Evaluation, developed
based on the DOP model. Together they generate functionally valid test-sequence
for carrying out prototype evaluation. With the help of a case study 'Multimode
Detection Subsystem' the application of this method is sketched. The design
methodologies can be compared by defining and computing a generic performance
criterion like Average design-cycle Risk. For the case study, by computing
Average design-cycle Risk, it is shown that the adaptive method reduces the
product development risk for a small increase in the total design cycle time.Comment: 21 pages, 9 figure
Formal Model Engineering for Embedded Systems Using Real-Time Maude
This paper motivates why Real-Time Maude should be well suited to provide a
formal semantics and formal analysis capabilities to modeling languages for
embedded systems. One can then use the code generation facilities of the tools
for the modeling languages to automatically synthesize Real-Time Maude
verification models from design models, enabling a formal model engineering
process that combines the convenience of modeling using an informal but
intuitive modeling language with formal verification. We give a brief overview
six fairly different modeling formalisms for which Real-Time Maude has provided
the formal semantics and (possibly) formal analysis. These models include
behavioral subsets of the avionics modeling standard AADL, Ptolemy II
discrete-event models, two EMF-based timed model transformation systems, and a
modeling language for handset software.Comment: In Proceedings AMMSE 2011, arXiv:1106.596
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