170 research outputs found
Towards Scalable Synthesis of Stochastic Control Systems
Formal control synthesis approaches over stochastic systems have received
significant attention in the past few years, in view of their ability to
provide provably correct controllers for complex logical specifications in an
automated fashion. Examples of complex specifications of interest include
properties expressed as formulae in linear temporal logic (LTL) or as automata
on infinite strings. A general methodology to synthesize controllers for such
properties resorts to symbolic abstractions of the given stochastic systems.
Symbolic models are discrete abstractions of the given concrete systems with
the property that a controller designed on the abstraction can be refined (or
implemented) into a controller on the original system. Although the recent
development of techniques for the construction of symbolic models has been
quite encouraging, the general goal of formal synthesis over stochastic control
systems is by no means solved. A fundamental issue with the existing techniques
is the known "curse of dimensionality," which is due to the need to discretize
state and input sets and that results in an exponential complexity over the
number of state and input variables in the concrete system. In this work we
propose a novel abstraction technique for incrementally stable stochastic
control systems, which does not require state-space discretization but only
input set discretization, and that can be potentially more efficient (and thus
scalable) than existing approaches. We elucidate the effectiveness of the
proposed approach by synthesizing a schedule for the coordination of two
traffic lights under some safety and fairness requirements for a road traffic
model. Further we argue that this 5-dimensional linear stochastic control
system cannot be studied with existing approaches based on state-space
discretization due to the very large number of generated discrete states.Comment: 22 pages, 3 figures. arXiv admin note: text overlap with
arXiv:1407.273
Dynamics-Based Reactive Synthesis and Automated Revisions for High-Level Robot Control
The aim of this work is to address issues where formal specifications cannot
be realized on a given dynamical system subjected to a changing environment.
Such failures occur whenever the dynamics of the system restrict the robot in
such a way that the environment may prevent the robot from progressing safely
to its goals. We provide a framework that automatically synthesizes revisions
to such specifications that restrict the assumed behaviors of the environment
and the behaviors of the system. We provide a means for explaining such
modifications to the user in a concise, easy-to-understand manner. Integral to
the framework is a new algorithm for synthesizing controllers for reactive
specifications that include a discrete representation of the robot's dynamics.
The new approach is demonstrated with a complex task implemented using a
unicycle model.Comment: 25 pages, 8 figure
Automated Formal Synthesis of Digital Controllers for State-Space Physical Plants
We present a sound and automated approach to synthesize
safe digital feedback controllers for physical plants represented as linear,
time-invariant models. Models are given as dynamical equations with
inputs, evolving over a continuous state space and accounting for errors
due to the digitization of signals by the controller. Our counterexample
guided inductive synthesis (CEGIS) approach has two phases: We synthesize a static feedback controller that stabilizes the system but that
may not be safe for all initial conditions. Safety is then verified either
via BMC or abstract acceleration; if the verification step fails, a counterexample is provided to the synthesis engine and the process iterates until a safe controller is obtained. We demonstrate the practical value of this approach by automatically synthesizing safe controllers for intricate physical plant models from the digital control literature
Formal Techniques for Component-based Design of Embedded Systems
Embedded systems have become ubiquitous - from avionics and automotive over consumer electronics to medical devices. Failures may entailmaterial damage or compromise safety of human beings. At the same time, shorter product cycles, together with fast growing complexity of the systems to be designed, create a tremendous need for rigorous design techniques. The goal of component-based construction is to build complex systems from simpler components that are well understood and can be (re)used so as to accelerate the design process. This document presents a summary of the formal techniques for component-based design of embedded systems I have (co-)developed
Distributed Control for Cyber-Physical Systems
Networked Cyber-Physical Systems (CPS) are fundamentally constrained by the tight coupling and closed-loop control and actuation of physical processes. To address actuation in such closed-loop wireless control systems there is a strong need to re-think the communication architectures and protocols for maintaining stability and performance in the presence of disturbances to the network, environment and overall system objectives. We review the current state of network control efforts for CPS and present two complementary approaches for robust, optimal and composable control over networks. We first introduce a computer systems approach with Embedded Virtual Machines (EVM), a programming abstraction where controller tasks, with their control and timing properties, are maintained across physical node boundaries. Controller functionality is decoupled from the physical substrate and is capable of runtime migration to the most competent set of physical controllers to maintain stability in the presence of changes to nodes, links and network topology.
We then view the problem from a control theoretic perspective to deliver fully distributed control over networks with Wireless Control Networks (WCN). As opposed to traditional networked control schemes where the nodes simply route information to and from a dedicated controller, our approach treats the network itself as the controller. In other words, the computation of the control law is done in a fully distributed way inside the network. In this approach, at each time-step, each node updates its internal state to be a linear combination of the states of the nodes in its neighborhood. This causes the entire network to behave as a linear dynamical system, with sparsity constraints imposed by the network topology. This eliminates the need for routing between “sensor → channel → dedicated controller/estimator → channel → actuator”, allows for simple transmission scheduling, is operational on resource constrained low-power nodes and allows for composition of additional control loops and plants. We demonstrate the potential of such distributed controllers to be robust to a high degree of link failures and to maintain stability even in cases of node failures
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