423 research outputs found
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
Linear Time Logic Control of Discrete-Time Linear Systems
The control of complex systems poses new challenges that fall beyond the traditional methods of control theory. One of these challenges is given by the need to control, coordinate and synchronize the operation of several interacting submodules within a system. The desired objectives are no longer captured by usual control specifications such as stabilization or output regulation. Instead, we consider specifications given by linear temporal logic (LTL) formulas. We show that existence of controllers for discrete-time controllable linear systems and LTL specifications can be decided and that such controllers can be effectively computed. The closed-loop system is of hybrid nature, combining the original continuous dynamics with the automatically synthesized switching logic required to enforce the specification
Barrier-Based Test Synthesis for Safety-Critical Systems Subject to Timed Reach-Avoid Specifications
We propose an adversarial, time-varying test-synthesis procedure for
safety-critical systems without requiring specific knowledge of the underlying
controller steering the system. From a broader test and evaluation context,
determination of difficult tests of system behavior is important as these tests
would elucidate problematic system phenomena before these mistakes can engender
problematic outcomes, e.g. loss of human life in autonomous cars, costly
failures for airplane systems, etc. Our approach builds on existing,
simulation-based work in the test and evaluation literature by offering a
controller-agnostic test-synthesis procedure that provides a series of
benchmark tests with which to determine controller reliability. To achieve
this, our approach codifies the system objective as a timed reach-avoid
specification. Then, by coupling control barrier functions with this class of
specifications, we construct an instantaneous difficulty metric whose minimizer
corresponds to the most difficult test at that system state. We use this
instantaneous difficulty metric in a game-theoretic fashion, to produce an
adversarial, time-varying test-synthesis procedure that does not require
specific knowledge of the system's controller, but can still provably identify
realizable and maximally difficult tests of system behavior. Finally, we
develop this test-synthesis procedure for both continuous and discrete-time
systems and showcase our test-synthesis procedure on simulated and hardware
examples
Learning Robust and Correct Controllers from Signal Temporal Logic Specifications Using BarrierNet
In this paper, we consider the problem of learning a neural network
controller for a system required to satisfy a Signal Temporal Logic (STL)
specification. We exploit STL quantitative semantics to define a notion of
robust satisfaction. Guaranteeing the correctness of a neural network
controller, i.e., ensuring the satisfaction of the specification by the
controlled system, is a difficult problem that received a lot of attention
recently. We provide a general procedure to construct a set of trainable High
Order Control Barrier Functions (HOCBFs) enforcing the satisfaction of formulas
in a fragment of STL. We use the BarrierNet, implemented by a differentiable
Quadratic Program (dQP) with HOCBF constraints, as the last layer of the neural
network controller, to guarantee the satisfaction of the STL formulas. We train
the HOCBFs together with other neural network parameters to further improve the
robustness of the controller. Simulation results demonstrate that our approach
ensures satisfaction and outperforms existing algorithms.Comment: Submitted to CDC 202
Model-Checking-based vs. SMT-based Consistency Analysis of Industrial Embedded Systems Requirements: Application and Experience
Industry relies predominantly on manual peer-review techniques for assessing the correctness of system specifications. However, with the ever increasing size, complexity and intricacy of the specifications, it becomes difficult to assure their correctness with respect to certain criteria such as consistency. To cope with this challenge, a set of techniques based on formal methods, called \textit{sanity checks} have been proposed to automatically assess the quality of system specifications in a systematic and rigorous manner. The predominant way of assessing the sanity of system specifications is by model checking, which in literature is reported to be expensive for analysis as it takes a long time for the procedure to terminate. Recently, another approach for checking the consistency of a system's specification using Satisfiability Modulo Theories has been proposed in order to reduce the analysis time. In this paper, we compare the two approaches for consistency analysis, by applying them on a relevant industrial use case, using the same definition for consistency and the same set of requirements. The comparison is carried out with respect to: i) time for generating the model and the latter's complexity, and ii) consistency analysis time. Contrary to the currently available data, our preliminary results show no significant difference in analysis time when applied on the same system specification under the same definition of consistency, but show significant difference in the time of creating the model for analysis
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