High-Speed and Low-Cost Implementation of Explicit Model Predictive Controllers

This paper presents a new form of piecewise-affine (PWA) solution, referred to as PWA hierarchical (PWAH), to approximate the explicit model predictive control (MPC) law, achieving a very rapid control response with the use of very few computational and memory resources. This is possible because PWAH controllers consist of single-input single-output PWA modules connected in cascade so that the parameters needed to define them increase linearly instead of exponentially with the input dimension of the control problem. PWAH controllers are not universal approximators but several explicit MPC controllers can be efficiently approximated by them. A methodology to design PWAH controllers is presented and validated with application examples already solved by MPC approaches. The designed PWAH controllers implemented in field-programmable gate arrays provide the highest control speed using the fewest resources compared with the other digital implementations reported in the literature.Ministerio de Economía, Industria y Competitividad TEC2014-57971-

Digital VLSI Implementation of Piecewise-Affine Controllers Based on Lattice Approach

This paper presents a small, fast, low-power consumption solution for piecewise-affine (PWA) controllers. To achieve this goal, a digital architecture for very-large-scale integration (VLSI) circuits is proposed. The implementation is based on the simplest lattice form, which eliminates the point location problem of other PWA representations and is able to provide continuous PWA controllers defined over generic partitions of the input domain. The architecture is parameterized in terms of number of inputs, outputs, signal resolution, and features of the controller to be generated. The design flows for field-programmable gate arrays and application-specific integrated circuits are detailed. Several application examples of explicit model predictive controllers (such as an adaptive cruise control and the control of a buck-boost dc-dc converter) are included to illustrate the performance of the VLSI solution obtained with the proposed lattice-based architecture

Digital VLSI Implementation of Piecewise-Affine Controllers Based on Lattice Approach

This paper presents a small, fast, low-power consumption solution for piecewise-affine (PWA) controllers. To achieve this goal, a digital architecture for very-large-scale integration (VLSI) circuits is proposed. The implementation is based on the simplest lattice form, which eliminates the point location problem of other PWA representations and is able to provide continuous PWA controllers defined over generic partitions of the input domain. The architecture is parameterized in terms of number of inputs, outputs, signal resolution, and features of the controller to be generated. The design flows for field-programmable gate arrays and application-specific integrated circuits are detailed. Several application examples of explicit model predictive controllers (such as an adaptive cruise control and the control of a buck-boost dc-dc converter) are included to illustrate the performance of the VLSI solution obtained with the proposed lattice-based architecture.Peer reviewe

Motion Planning for Autonomous Vehicles in Partially Observable Environments

Unsicherheiten, welche aus Sensorrauschen oder nicht beobachtbaren Manöverintentionen anderer Verkehrsteilnehmer resultieren, akkumulieren sich in der Datenverarbeitungskette eines autonomen Fahrzeugs und führen zu einer unvollständigen oder fehlinterpretierten Umfeldrepräsentation. Dadurch weisen Bewegungsplaner in vielen Fällen ein konservatives Verhalten auf. Diese Dissertation entwickelt zwei Bewegungsplaner, welche die Defizite der vorgelagerten Verarbeitungsmodule durch Ausnutzung der Reaktionsfähigkeit des Fahrzeugs kompensieren. Diese Arbeit präsentiert zuerst eine ausgiebige Analyse über die Ursachen und Klassifikation der Unsicherheiten und zeigt die Eigenschaften eines idealen Bewegungsplaners auf. Anschließend befasst sie sich mit der mathematischen Modellierung der Fahrziele sowie den Randbedingungen, welche die Sicherheit gewährleisten. Das resultierende Planungsproblem wird mit zwei unterschiedlichen Methoden in Echtzeit gelöst: Zuerst mit nichtlinearer Optimierung und danach, indem es als teilweise beobachtbarer Markov-Entscheidungsprozess (POMDP) formuliert und die Lösung mit Stichproben angenähert wird. Der auf nichtlinearer Optimierung basierende Planer betrachtet mehrere Manöveroptionen mit individuellen Auftrittswahrscheinlichkeiten und berechnet daraus ein Bewegungsprofil. Er garantiert Sicherheit, indem er die Realisierbarkeit einer zufallsbeschränkten Rückfalloption gewährleistet. Der Beitrag zum POMDP-Framework konzentriert sich auf die Verbesserung der Stichprobeneffizienz in der Monte-Carlo-Planung. Erstens werden Informationsbelohnungen definiert, welche die Stichproben zu Aktionen führen, die eine höhere Belohnung ergeben. Dabei wird die Auswahl der Stichproben für das reward-shaped Problem durch die Verwendung einer allgemeinen Heuristik verbessert. Zweitens wird die Kontinuität in der Reward-Struktur für die Aktionsauswahl ausgenutzt und dadurch signifikante Leistungsverbesserungen erzielt. Evaluierungen zeigen, dass mit diesen Planern große Erfolge in Fahrversuchen und Simulationsstudien mit komplexen Interaktionsmodellen erreicht werden

Computer Aided Verification

This open access two-volume set LNCS 13371 and 13372 constitutes the refereed proceedings of the 34rd International Conference on Computer Aided Verification, CAV 2022, which was held in Haifa, Israel, in August 2022. The 40 full papers presented together with 9 tool papers and 2 case studies were carefully reviewed and selected from 209 submissions. The papers were organized in the following topical sections: Part I: Invited papers; formal methods for probabilistic programs; formal methods for neural networks; software Verification and model checking; hyperproperties and security; formal methods for hardware, cyber-physical, and hybrid systems. Part II: Probabilistic techniques; automata and logic; deductive verification and decision procedures; machine learning; synthesis and concurrency. This is an open access book

Numerical scalar curvature deformation and a gluing construction

In this work a new numerical technique to prepare Cauchy data for the initial value problem (IVP) formulation of Einstein's field equations (EFE) is presented. Our method is directly inspired by the exterior asymptotic gluing (EAG) result of Corvino (2000). The argument assumes a moment in time symmetry and allows for a composite, initial data set to be assembled from (a finite subdomain of) a known asymptotically Euclidean initial data set which is glued (in a controlled manner) over a compact spatial region to an exterior Schwarzschildean representative. We demonstrate how (Corvino, 2000) may be directly adapted to a numerical scheme and under the assumption of axisymmetry construct composite Hamiltonian constraint satisfying initial data featuring internal binary black holes (BBH) glued to exterior Schwarzschild initial data in isotropic form. The generality of the method is shown in a comparison of properties of EAG composite initial data sets featuring internal BBHs as modelled by Brill-Lindquist and Misner data. The underlying geometric analysis character of gluing methods requires work within suitably weighted function spaces, which, together with a technical impediment preventing (Corvino, 2000) from being fully constructive, is the principal difficulty in devising a numerical technique. Thus the single previous attempt by Giulini and Holzegel (2005) (recently implemented by Doulis and Rinne (2016)) sought to avoid this by embedding the result within the well known Lichnerowicz-York conformal framework which required ad-hoc assumptions on solution form and a formal perturbative argument to show that EAG may proceed. In (Giulini and Holzegel, 2005) it was further claimed that judicious engineering of EAG can serve to reduce the presence of spurious gravitational radiation - unfortunately, in line with the general conclusion of (Doulis and Rinne, 2016) our numerical investigation does not appear to indicate that this is the case. Concretising the sought initial data to be specified with respect to a spatial manifold with underlying topology R×S² our method exploits a variety of pseudo-spectral (PS) techniques. A combination of the eth-formalism and spin-weighted spherical harmonics together with a novel complex-analytic based numerical approach is utilised. This is enabled by our Python 3 based numerical toolkit allowing for unified just-in-time compiled, distributed calculations with seamless extension to arbitrary precision for problems involving generic, geometric partial differential equations (PDE) as specified by tensorial expressions. Additional features include a layer of abstraction that allows for automatic reduction of indicial (i.e., tensorial) expressions together with grid remapping based on chart specification - hence straight-forward implementation of IVP formulations of the EFE such as ADM-York or ADM-York-NOR is possible. Code-base verification is performed by evolving the polarised Gowdy T³ space-time with the above formulations utilising high order, explicit time-integrators in the method of lines approach as combined with PS techniques. As the initial data we prepare has a precise (Schwarzschild) exterior this may be of interest to global evolution schemes that incorporate information from spatial-infinity. Furthermore, our approach may shed light on how more general gluing techniques could potentially be adapted for numerical work. The code-base we have developed may also be of interest in application to other problems involving geometric PDEs

Constructive Formal Control Synthesis through Abstraction and Decomposition

Control synthesis is the problem of automatically constructing a control strategy that induces a system to exhibit a declared behavior. Synthesis algorithms vary widely across different classes of system dynamics and specifications.While continuous optimization has traditionally been used to construct stabilizing controllers for physical systems modeled with differential equations, temporal logic synthesis for finite state machines heavily leverages discrete algorithms and data structures.Hybrid systems are a class of systems that exhibit both continuous and discrete behaviors, which are necessary to capture phenomena such as impacts for legged robots and congestion shockwaves in freeways. Tractable control synthesis remains elusive because hybrid systems violate many of the fundamental topological assumptions made by prior algorithms for purely continuous or discrete systems.This thesis exploits compositionality and system structure to provide a suite of algorithmic and theoretical techniques to tackle acute computational bottlenecks in hybrid control synthesis.The first half of this thesis provides a framework for engineers to model control systems and construct algorithmic pipelines for control synthesis.By explicitly capturing system structure, this framework gives users the flexibility to rapidly iterate over and leverage a library of optimizations for control synthesis.We demonstrate this framework in the context of abstraction-based control, a synthesis workflow that translates continuous systems into finite state machines by throwing away high precision information. Different optimization techniques such as multi-scale grids, lazy abstraction, and decomposed synthesis, can all be expressed as modifications to a computational pipeline. We demonstrate computational gains while synthesizing safe motion primitives for numerous robotic examples.The second half addresses distributed control synthesis where multiple controllers act as agents that seek to jointly satisfy a specification and are restricted by some communication topology. We introduce parametric assume-guarantee contracts as a formalism to derive guarantees about the closed loop behavior of a collection of interacting components. Dynamic contracts allow contract parameters to change at runtime and enable coordination of multiple interacting sub-systems.These results are demonstrated in the context of a freeway ramp meter and an adjacent arterial network