DEVS-Based Building Blocks and Architectural Patterns for Intelligent Hybrid Cyberphysical System Design

The DEVS formalism has been recognized to support generic open architectures that allow incorporating multiple engineering domains within integrated simulation models. What is missing for accelerated adoption of DEVS-based methodology for intelligent cyberphysical system design is a set of building blocks and architectural patterns that can be replicated and reused in system development. As a start in this direction, this paper offers a notional architecture for intelligent hybrid cyberphysical system design and proceeds to focus on the decision layer to consider DEVS models for basic behaviors such as choice of alternatives, perception of temporal event relations, and recognition and generation of finite state languages cast into DEVS time segments. We proceed to describe a methodology to define DEVS-based building blocks and architectural patterns for design of systems employing fast, frugal, and accurate heuristics. We identify some elements of this kind and establish their status as minimal realizations of their defined behaviors. As minimal realizations such designs must ipso facto underlie any implementation of the same cognitive behaviors. We discuss architectures drawn from the cognitive science literature to show that the fundamental elements drawn from the fast, frugal, and accurate paradigm provide insights into intelligent hybrid cyberphysical system design. We close with open questions and research needed to confirm the proposed concepts.

Design of a Matlab toolbox and GUI for minimal realizations

<p>Minimal realization for linear systems has been studied extensively in the literature. Techniques proposed differ in terms of the configuration of the state space form, the time efficiency of the algorithm and the reduction of memory storage. The minimal realization toolbox presented in this paper offers the possibility to test different methods and choose the most suitable form depending on the application. The given system can be represented by a transfer function or by raw (frequency or time domain) data. A graphical user interface (GUI) was implemented in order to ease the use of this toolbox and allow to rapidly test the methods and display the results.</p>

Minimal dirac neutrino mass models from $$\hbox {U}(1)_{\mathrm{R}}$$ gauge symmetry and left–right asymmetry at colliders

In this work, we propose minimal realizations for generating Dirac neutrino masses in the context of a right-handed abelian gauge extension of the Standard Model. Utilizing only $$U(1)_R$$U(1)R symmetry, we address and analyze the possibilities of Dirac neutrino mass generation via (a) tree-level seesaw and (b) radiative correction at the one-loop level. One of the presented radiative models implements the attractive scotogenic model that links neutrino mass with Dark Matter (DM), where the stability of the DM is guaranteed from a residual discrete symmetry emerging from $$U(1)_R$$U(1)R. Since only the right-handed fermions carry non-zero charges under the $$U(1)_R$$U(1)R, this framework leads to sizable and distinctive Left–Right asymmetry as well as Forward–Backward asymmetry discriminating from $$U(1)_{B-L}$$U(1)B-L models and can be tested at the colliders. We analyze the current experimental bounds and present the discovery reach limits for the new heavy gauge boson $$Z^{\prime }$$Z′ at the LHC and ILC. Furthermore, we also study the associated charged lepton flavor violating processes, dark matter phenomenology and cosmological constraints of these models.

Mixed Order Fractional Observers for Minimal Realizations of Linear Time-Invariant Systems

Adaptive and non-adaptive minimal realization (MR) fractional order observers (FOO) for linear time-invariant systems (LTIS) of a possibly different derivation order (mixed order observers, MOO) are studied in this paper. Conditions on the convergence and robustness are provided using a general framework which allows observing systems defined with any type of fractional order derivative (FOD). A qualitative discussion is presented to show that the derivation orders of the observer structure and for the parameter adjustment are relevant degrees of freedom for performance optimization. A control problem is developed to illustrate the application of the proposed observers.