5,136 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
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Oracle-Guided Design and Analysis of Learning-Based Cyber-Physical Systems
We are in world where autonomous systems, such as self-driving cars, surgical robots, robotic manipulators are becoming a reality. Such systems are considered \textit{safety-critical} since they interact with humans on a regular basis. Hence, before such systems can be integrated into our day to day life, we need to guarantee their safety. Recent success in machine learning (ML) and artificial intelligence (AI) has led to an increase in their use in real world robotic systems. For example, complex perception modules in self-driving cars and deep reinforcement learning controllers in robotic manipulators. Although powerful, they introduce an additional level of complexity when it comes to the formal analysis of autonomous systems. In this thesis, such systems are designated as Learning-Based Cyber-Physical Systems~(LB-CPS). In this thesis, we take inspiration from the Oracle-Guided Inductive Synthesis~(OGIS) paradigm to develop frameworks which can aid in achieving formal guarantees in different stages of an autonomous system design and analysis pipeline. Furthermore, we show that to guarantee the safety of LB-CPS, the design (synthesis) and analysis (verification) must consider feedback from the other. We consider five important parts of the design and analysis process and show a strong coupling among them, namely (i) Robust Control Synthesis from High Level Safety Specifications; (ii) Diagnosis and Repair of Safety Requirements for Control Synthesis; (iii) Counter-example Guided Data Augmentation for training high-accuracy ML models; (iv) Simulation-Guided Falsification and Verification against Adversarial Environments; and (v) Bridging Model and Real-World Gap. Finally, we introduce a software toolkit \verifai{} for the design and analysis of AI based systems, which was developed to provide a common formal platform to implement design and analysis frameworks for LB-CPS
Prescribed Performance Control for Signal Temporal Logic Specifications
Motivated by the recent interest in formal methods-based control for dynamic
robots, we discuss the applicability of prescribed performance control to
nonlinear systems subject to signal temporal logic specifications. Prescribed
performance control imposes a desired transient behavior on the system
trajectories that is leveraged to satisfy atomic signal temporal logic
specifications. A hybrid control strategy is then used to satisfy a finite set
of these atomic specifications. Simulations of a multi-agent system, using
consensus dynamics, show that a wide range of specifications, i.e., formation,
sequencing, and dispersion, can be robustly satisfied.Comment: 9 pages - this an extended version of the 56th IEEE Conference on
Decision and Control (2017) versio
RULES BASED MODELING OF DISCRETE EVENT SYSTEMS WITH FAULTS AND THEIR DIAGNOSIS
Failure diagnosis in large and complex systems is a critical task. In the realm of discrete event systems, Sampath et al. proposed a language based failure diagnosis approach. They introduced the diagnosability for discrete event systems and gave a method for testing the diagnosability by first constructing a diagnoser for the system. The complexity of this method of testing diagnosability is exponential in the number of states of the system and doubly exponential in the number of failure types. In this thesis, we give an algorithm for testing diagnosability that does not construct a diagnoser for the system, and its complexity is of 4th order in the number of states of the system and linear in the number of the failure types. In this dissertation we also study diagnosis of discrete event systems (DESs) modeled in the rule-based modeling formalism introduced in [12] to model failure-prone systems. The results have been represented in [43]. An attractive feature of rule-based model is it\u27s compactness (size is polynomial in number of signals). A motivation for the work presented is to develop failure diagnosis techniques that are able to exploit this compactness. In this regard, we develop symbolic techniques for testing diagnosability and computing a diagnoser. Diagnosability test is shown to be an instance of 1st order temporal logic model-checking. An on-line algorithm for diagnosersynthesis is obtained by using predicates and predicate transformers. We demonstrate our approach by applying it to modeling and diagnosis of a part of the assembly-line. When the system is found to be not diagnosable, we use sensor refinement and sensor augmentation to make the system diagnosable. In this dissertation, a controller is also extracted from the maximally permissive supervisor for the purpose of implementing the control by selecting, when possible, only one controllable event from among the ones allowed by the supervisor for the assembly line in automaton models
Working Notes from the 1992 AAAI Workshop on Automating Software Design. Theme: Domain Specific Software Design
The goal of this workshop is to identify different architectural approaches to building domain-specific software design systems and to explore issues unique to domain-specific (vs. general-purpose) software design. Some general issues that cut across the particular software design domain include: (1) knowledge representation, acquisition, and maintenance; (2) specialized software design techniques; and (3) user interaction and user interface
Metrics for Signal Temporal Logic Formulae
Signal Temporal Logic (STL) is a formal language for describing a broad range
of real-valued, temporal properties in cyber-physical systems. While there has
been extensive research on verification and control synthesis from STL
requirements, there is no formal framework for comparing two STL formulae. In
this paper, we show that under mild assumptions, STL formulae admit a metric
space. We propose two metrics over this space based on i) the Pompeiu-Hausdorff
distance and ii) the symmetric difference measure, and present algorithms to
compute them. Alongside illustrative examples, we present applications of these
metrics for two fundamental problems: a) design quality measures: to compare
all the temporal behaviors of a designed system, such as a synthetic genetic
circuit, with the "desired" specification, and b) loss functions: to quantify
errors in Temporal Logic Inference (TLI) as a first step to establish formal
performance guarantees of TLI algorithms.Comment: This paper has been accepted for presentation at, and publication in
the proceedings of, the 2018 IEEE Conference on Decision and Control (CDC),
to be held in Fontainebleau, Miami Beach, FL, USA on Dec. 17-19, 201
Contract-Based Specification Refinement and Repair for Mission Planning
We address the problem of modeling, refining, and repairing formal
specifications for robotic missions using assume-guarantee contracts. We show
how to model mission specifications at various levels of abstraction and
implement them using a library of pre-implemented specifications. Suppose the
specification cannot be met using components from the library. In that case, we
compute a proxy for the best approximation to the specification that can be
generated using elements from the library. Afterward, we propose a systematic
way to either 1) search for and refine the `missing part' of the specification
that the library cannot meet or 2) repair the current specification such that
the existing library can refine it. Our methodology for searching and repairing
mission requirements leverages the quotient, separation, composition, and
merging operations between contracts
Advanced information processing system: The Army fault tolerant architecture conceptual study. Volume 2: Army fault tolerant architecture design and analysis
Described here is the Army Fault Tolerant Architecture (AFTA) hardware architecture and components and the operating system. The architectural and operational theory of the AFTA Fault Tolerant Data Bus is discussed. The test and maintenance strategy developed for use in fielded AFTA installations is presented. An approach to be used in reducing the probability of AFTA failure due to common mode faults is described. Analytical models for AFTA performance, reliability, availability, life cycle cost, weight, power, and volume are developed. An approach is presented for using VHSIC Hardware Description Language (VHDL) to describe and design AFTA's developmental hardware. A plan is described for verifying and validating key AFTA concepts during the Dem/Val phase. Analytical models and partial mission requirements are used to generate AFTA configurations for the TF/TA/NOE and Ground Vehicle missions
DESIGN OF OPTIMAL PROCEDURAL CONTROLLERS FOR CHEMICAL PROCESSES MODELLED AS STOCHASTIC DISCRETE EVENT SYSTEMS
This thesis presents a formal method for the the design of optimal and provably correct
procedural controllers for chemical processes modelled as Stochastic Discrete Event Systems
(SDESs). The thesis extends previous work on Procedural Control Theory (PCT) [1],
which used formal techniques for the design of automation Discrete Event Systems (DESs).
Many dynamic processes for example, batch operations and the start-up and shut down of
continuous plants, can be modelled as DESs. Controllers for these systems are typically
of the sequential type.
Most prior work on characterizing the behaviour of DESs has been restricted to deterministic
systems. However, DESs consisting of concurrent interacting processes present
a broad spectrum of uncertainty such as uncertainty in the occurrence of events. The
formalism of weighted probabilistic Finite State Machine (wp-FSM) is introduced for
modelling SDESs and pre-de ned failure models are embedded in wp-FSM to describe
and control the abnormal behaviour of systems. The thesis presents e cient algorithms
and procedures for synthesising optimal procedural controllers for such SDESs.
The synthesised optimal controllers for such stochastic systems will take into consideration
probabilities of events occurrence, operation costs and failure costs of events in
making optimal choices in the design of control sequences. The controllers will force the
system from an initial state to one or more goal states with an optimal expected cost and
when feasible drive the system from any state reached after a failure to goal states.
On the practical side, recognising the importance of the needs of the target end
user, the design of a suitable software implementation is completed. The potential of both
the approach and the supporting software are demonstrated by two industry case studies.
Furthermore, the simulation environment gPROMS was used to test whether the operating
speci cations thus designed were met in a combined discrete/continuous environment
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