Decentralised adaptive architectures for control of large-scale active–passive modular systems with stability and performance guarantees

ABSTRACT

Decentralised control of large-scale active–passive modular systems is considered in this paper. The considered class of large-scale systems consist of physically interconnected and generally heterogeneous modules, where local control signals can only be applied to a subset of these modules (i.e. active modules) and the rest do not admit any control signals (i.e. passive modules). Specifically, based on a set-theoretic model reference adaptive control approach predicated on restricted potential functions, we design and analyse decentralised command following control laws for each active module such that they can effectively perform their tasks in the presence of unknown physical interconnections between modules and module-level system uncertainties. The key feature of our framework allows the system error trajectories of the active modules to be contained within a-priori, user-defined compact sets. Thus, they are guaranteed to achieve strict performance guarantees, where this is of paramount importance for practical applications. In addition to our theoretical findings and research contributions, the efficacy of the proposed decentralised adaptive control architecture is demonstrated in an illustrative numerical example.     

Efficient Modular Squaring Algorithms for Hardware Implementation in GF(p)

ABSTRACT

Some of the most popular public key encryption algorithms use exponentiation as their core operation, which can be mostly broken into several modular squaring operations. In this paper, we present GF(p) modular squaring algorithms and efficiently implement them on hardware. We present different algorithms, two for squaring and one for reduction combined with the squaring, to provide a general modular squaring algorithm. The algorithms are implemented through datapaths that uses redundant Carry-Save Adders, making the computation time independent form the operands precision. The proposed algorithms are compared with each other as well as with the existing modular squaring algorithms. The experimental results are obtained by synthesizing the hardware designs for FPGA Virtex5 chip (xc5vlx50 – ff1153 technology), which showed interesting results and made our ideas very attractive.     

Modular Petri Net based modeling,analysis, synthesis and performance evaluation of random topology dedicated production systems

Ordinary t-timed modular Petri Nets are used for modeling, analysis, synthesis and performance evaluation of random topology dedicated production systems. Each system is first decomposed into production line, assembly, disassembly and parallel machine modules followed by derivation of their modular Petri Net models. Two sets of modules, generic and generalized respectively, are derived corresponding to the simplest and most general cases. Overall system Petri Net model is obtained via synthesis of the individual modules satisfying system features (production rates, buffer capacities, machine expected up, down or idle times). Detailed mathematical expressions are derived for modules P-invariants (and T-invariants when exist); they are further generalized for a random topology and complexity dedicated production system. Total number of the individual Petri Net module nodes as well as of the combined system Petri Net model is also calculated. Results show the applicability of the proposed methodology and justify its modeling power and generality.     

有向图中模块化航天器系统相对轨道的自适应分布式一致性

基于多智能体系统一致性理论,对模块化航天器相对轨道的分布式一致性问题进行了研究.各模块之间的信息交互拓扑结构为更具一般性的有向图.当存在模块质量不确定性的情形下,设计了仅依赖模块自身及其邻近模块信息且无需模块间相对速度信息的自适应控制算法.针对模型中存在外部干扰的情形,通过引入带有时变自适应参数的变结构控制项,实现了对未知上界干扰的补偿,并且证明了闭环系统是渐近稳定的.此外,本文所设计的算法具有分布式的特点,不会因为模块数量的增多而增加所提算法的复杂度.最后对6个模块组成的模块化航天器的编队飞行进行了仿真分析,仿真结果表明本文设计的控制律是有效可行的.     

A Framework for Proof Systems

Linear logic can be used as a meta-logic to specify a range of object-level proof systems. In particular, we show that by providing different polarizations within a focused proof system for linear logic, one can account for natural deduction (normal and non-normal), sequent proofs (with and without cut), and tableaux proofs. Armed with just a few, simple variations to the linear logic encodings, more proof systems can be accommodated, including proof system using generalized elimination and generalized introduction rules. In general, most of these proof systems are developed for both classical and intuitionistic logics. By using simple results about linear logic, we can also give simple and modular proofs of the soundness and relative completeness of all the proof systems we consider.     

THE SYSTEMIC FORMALIZATION OF KNOWLEDGE INVOLVING UNCERTAINTY

Abstract

We have developed generic models useful for modeling human expertise involving uncertainty. These generic models are based on fundamental work carried out in the field of systems science, in which various researchers have developed formalisms for modeling systems in general. In this paper, we present our Systemic U-Knowledge Framework, which utilizes our models and new mathematical constructs we have developed for modeling uncertainty. We have validated the resulting formalism by modeling the expertise of an education expert, and have used the model as a basis for automated problem-solving.     

Construction and locomotion analysis of modular robots with pneumatic-actuated and binary-controlled expandable cubes

This paper presents the construction and locomotion analysis of the modular robots composed of expandable cubes (E-Cubes). The kinematic properties and experiment research of the assembled modular robots are the main focus of the paper. The E-Cube consisted of only prismatic joints is a cubic module with three degrees of freedom corresponding to three mutually perpendicular directions. The modular robots are constructed by connecting the vertex or edge of the adjacent modules. In this paper, first, the modular robot system including the E-Cube hardware, connection method of modules and a potential binary control strategy is described. And then, the detailed kinematics, stability and motion simulations of three configurations assembled with four modules are analysed. After that, a set of experimental pneumatic-based robotic system is built. At last, the gait experiments of the configurations are carried out to testify the feasibility and validity of design and locomotion functions. The experiment results show the reliability of the mechanical, control and pneumatic systems and the programming and control efficiency of the binary control strategy. As extension, a modular robot with eight modules is assembled, and its different locomotion gaits are simulated accordingly.     

Drivers for free‐form modular displays

Abstract— When displays of different sizes and shapes are required, a modular display system seems to be a good solution. Many systems offer only a limited freedom of shapes. The display can be scaled, but no irregular shapes can be created. If those shapes can be created, the configuration is often manual. A more intelligent modular system allows all shapes to be created and configures automatically. This paper presents two drivers that can be used in such a modular system. The first driver ensures that the data finds its way to every module and is displayed, even if there are some “holes” in the display due to missing modules. The second driver adds some extra functionality. The precise display configuration can be detected, and in the graphical user interface (used for controlling the display) the user sees an updated view of the display configuration when modules are added or removed. Both drivers have been proven successful and results are presented in this paper.     

Accomplishing the layered modular architecture in digital innovation: The case of the car’s driver information module

Architectural theory of digital innovation contends that, to enhance physical products with digital capabilities, a layered modular architecture is required. This architecture hybridizes hierarchically arranged components of physical products with modules of digital functionality configured into layers. Despite considerable research adopting this architectural perspective on digital innovation, questions of how this hybrid architecture is accomplished organizationally and technologically lack both conceptual clarity and empirical illustration. Noting pervasive tensions that characterize digital innovation efforts and the contradictions between hierarchical and layered modular configurations, this paper seeks to answer the following research question: Given that the layered modular architecture needs to hybridize modular arrangements with opposing logics, how is it accomplished?Employing the concepts of digitalization, physical product hierarchy and digital control system to better theorize a product architecture’s movement from a modular to a layered modular architecture accompanied by organizational structures that enable this change, we abductively analyze the increasing digitization of a car’s Driver Information Module (DIM) over a 10 year period. We conclude by proposing three transformations through which the layered modular architecture is accomplished.     

Neural and Neuro-Fuzzy Integration in a Knowledge-Based System for Air Quality Prediction

In this paper we propose a unified approach for integrating implicit and explicit knowledge in neurosymbolic systems as a combination of neural and neuro-fuzzy modules. In the developed hybrid system, training data set is used for building neuro-fuzzy modules, and represents implicit domain knowledge. The explicit domain knowledge on the other hand is represented by fuzzy rules, which are directly mapped into equivalent neural structures. The aim of this approach is to improve the abilities of modular neural structures, which are based on incomplete learning data sets, since the knowledge acquired from human experts is taken into account for adapting the general neural architecture. Three methods to combine the explicit and implicit knowledge modules are proposed. The techniques used to extract fuzzy rules from neural implicit knowledge modules are described. These techniques improve the structure and the behavior of the entire system. The proposed methodology has been applied in the field of air quality prediction with very encouraging results. These experiments show that the method is worth further investigation.     

Higher-order logics for handling uncertainty in expert systems

We argue that the current performance of expert systems is being limited by their capacity to cope with uncertainty. Probabilistic logics alone are not enough to cope with the many kinds of uncertainty that can occur. We show how modal and quantified logics have been devised to express different types of knowledge and are each a partial solution to the problem. Logic, however, can only express a limited amount of knowledge and this shortcoming is crucially affecting the knowledge engineering of expert systems. We argue that fuzzy logic and the associated Test-Score Semantics have a role in the development of expert systems, since they enable the representation of uncertainty and a topic-dependent semantics.     

THE LANGUAGE COMPONENT OF THE FASTY TEXT PREDICTION SYSTEM

ABSTRACT

This paper describes the language component of FASTY, a text prediction system designed to improve text input efficiency for disabled users. The FASTY language component is based on state-of-the-art n-gram-based word-level and part-of-speech-level prediction and on a number of innovative modules (morphological analysis, collocation-based prediction, compound prediction) that are meant to enhance performance in languages other than English. Together with its modular architecture, these novel techniques make it adaptable to a wide range of languages without sacrificing performance. Currently, versions for Dutch, German, French, Italian, and Swedish are supported. The system can be parameterized to be used with different user interfaces and for a range of different applications. In this paper, we discuss each of the modules in detail and we present a series of experimental evaluations of the system.     

A modular approach to defining and characterising notions of simulation

We propose a modular approach to defining notions of simulation, and modal logics which characterise them. We use coalgebras to model state-based systems, relators to define notions of simulation for such systems, and inductive techniques to define the syntax and semantics of modal logics for coalgebras. We show that the expressiveness of an inductively defined logic for coalgebras w.r.t. a notion of simulation follows from an expressivity condition involving one step in the definition of the logic, and the relator inducing that notion of simulation. Moreover, we show that notions of simulation and associated characterising logics for increasingly complex system types can be derived by lifting the operations used to combine system types, to a relational level as well as to a logical level. We use these results to obtain Baltag’s logic for coalgebraic simulation, as well as notions of simulation and associated logics for a large class of non-deterministic and probabilistic systems.     

Building modular legal knowledge systems

A practical legal knowledge system must be versatile and capable of supporting many fundamentally different aspects of the lawyer's work. In this paper a general framework for building knowledge systems from distinct but communicating modules is proposed. There are currently three different kinds of modules: computation, data storage, and environmental interaction. These modules include inference engines, database managers, and hypertext. Several strategies for coupling these modules are discussed. This framework is used to construct expert systems for two distinct domains: a legal expert system for labour law and a real-time expert system for process control in a pulp plant. The legal application shows that this system can be used to construct an “intelligent library”, guiding the user to relevant documents, rather than merely retrieving documents on request.     

Modular formal verification of specifications of concurrent systems

In this paper, we propose a bottom‐up approach for the verification of systems with modular structure: we prove that when the modules are composed in specific ways, the complete software system verifies a composition of the properties each component does. We focus on the process of upgrading systems with new functionalities, where the validity of old requirements needs to be ensured, but also an understanding of the new properties the upgraded system would enjoy is useful. In this work, we assume each component to be specified by a CCS process, and the properties to be expressed by selective mu‐calculus formulae. Copyright © 2007 John Wiley & Sons, Ltd.     

带未知干扰的模块化航天器系统相对轨道的队形控制

基于多智能体系统一致性理论,在有向拓扑结构中对模块化航天器相对轨道的队形控制问题进行研究.考虑与状态相关的未知外部干扰,在存在模块质量不确定性的情形下,基于自适应增益技术,设计仅依赖模块自身及其邻近模块信息的分布式控制算法,并通过Lyapunov稳定性方法证明闭环系统是渐近稳定的.最后在Matlab/Simulink中对6个模块组成的模块化航天器系统的队形进行仿真分析,仿真结果表明所设计的控制律是有效且可行的.     

基于知识工程的真空镀膜机模块化设计系统

提出了一种真空镀膜机的模块化设计方法,这种方法以专家系统和案例库为支撑,构建基于知识工程的真空镀膜机模块化设计系统。论述了数据库和案例推理方法为基础的专家系统,并且讨论了知识体系的结构,模块化设计方法以及案例推理的方法。由基础设计参数、设计约束、设计规则寻找最适合的型号和配置。通过设计后的数据到专家系统中寻找型号,再从案例库中获得此型号配置,并自动生成设计式样书和物料清单等,解决了目前CAD技术在真空镀膜机设计过程中存在的错误以及数据共享的问题,实现了结构设计、工艺设计、产品数据管理一体化过程。     

PSPACE-completeness of Modular Supervisory Control Problems*

In this paper we investigate computational issues associated with the supervision of concurrent processes modeled as modular discrete-event systems. Here, modular discrete-event systems are sets of deterministic finite-state automata whose interaction is modeled by the parallel composition operation. Even with such a simple model process model, we show that in general many problems related to the supervision of these systems are PSPACE-complete. This shows that although there may be space-efficient methods for avoiding the state-explosion problem inherent to concurrent processes, there are most likely no time-efficient solutions that would aid in the study of such large-scale systems. We show our results using a reduction from a special class of automata intersection problem introduced here where behavior is assumed to be prefix-closed. We find that deciding if there exists a supervisor for a modular system to achieve a global specification is PSPACE-complete. We also show many verification problems for system supervision are PSPACE-complete, even for prefix-closed cases. Supervisor admissibility and online supervision operations are also discussed.*This research was supported in part by NSF grant CCR-0082784.     

Modular Simulation in Multibody System Dynamics

The dynamic analysis of complex engineering systems likeautomobiles is often relieved by a modular approach to make it treatableby a team of engineers. The modular decomposition is based onengineering intuition of corresponding engineering disciplines. In thispaper, a modular formulation of multibody systems is proposed which isbased on the block representation of a multibody system withcorresponding input and output quantities. Advantages of this modularapproach range from independent and parallel modeling of subsystems overthe easy exchange of the resulting modules to the use of differentsoftware for each module. However, the modular simulation of the globalsystem by coupling of simulators may result in an unstable integrationif an algebraic loop exists between the subsystems. This numericalphenomenon is analyzed and a method of simulator coupling whichguarantees stability for general systems including algebraic loops isintroduced. Numerical results of the modular simulation of aslider-crank mechanism are presented.     

Logics to formalise p-adic valued probability and their applications

Abstract

In this paper, we focus on the main results which we have developed to obtain different propositional logics for reasoning about p-adic valued probabilities. Each of these logics is a sound, complete, and decidable extension of classical propositional logic. Also, we show some applications of these logics in modelling cognitions.