Service-Based Socio-Cyberphysical Network Modeling for Guided Self-Organization

AbstractSocio-cyberphysical networks tightly integrate humans, real-world objects and IT infrastructure. In some cases of cyberphysical networks, their configuration can be done in a centralized way (e.g., automated production line configuration). However, for socio-cyberphysical networks the centralized control is not possible due to the independence and autonomy of the network members (e.g., employees of an enterprise). The paper proposes an approach to model such network via a set of interacting socio-inspired services. Such services are capable to model behavior of the network participants taking into account their preferences, strategies and social norms. The interoperability of the services is achieved due to the usage of common standards (such as WSDL and SOAP) at the technological level, and common ontology at the semantic level. The developed conceptual model of socio-inspired service is presented together with behavior patterns and methods for their processing

Feature Models as Support for Business Model Implementation of Cyber-Physical Systems

From a business perspective Cyber-Physical Systems (CPS) can contribute to process innovation, product innovation or business model innovation. In this paper, the focus is on business model innovation based on CPS, i.e. we take the perspective of enterprises using CPS as basis for new customer services. In order to create viable CPS solutions, stakeholders from different enterprise functions should be involved, including business perspective and technical perspective. However, the business-related stakeholders often do not understand the technical possibilities and the technology-related stakeholders do understand the business opportunities. The paper proposes to use feature models as mediation support between business-oriented and technology-oriented stakeholders. Feature models conventionally are used for controlling variability, i.e. as a means for engineers to plan and design features for configuration and implementation. We propose to use them as a way to identify value propositions based on features. The main contributions of the paper are (a) to identify the potential feature models for alignment of business and technology-related stakeholders, (b) to propose feature model “slices” as support for business model development of CPS, and (c) an industrial case illustrating feasibility and utility of the approach

Time-annotated game graphs for synthesis from abstracted systems

The construction of discrete abstractions is a crucial part of many methods for control synthesis of hybrid systems subject to formal specifications. In general, the product of discrete abstractions may not be a discrete abstraction for the product of the underlying continuously-valued systems. Addressing this, we present a control synthesis method for transition systems that are built from components with uncertain timing characteristics. The new device, called here time-annotated game graphs, is demonstrated in a variety of examples. While it is applicable generally to parity games, we consider it in the context of control subject to GR(1) specifications. We show how a nominal strategy obtained without time knowledge can be modified to recover correctness when time information becomes available. The methods are applied to a brief case study of an aircraft electric power system

Identifying and exploiting tolerance to unexpected jumps in synthesized strategies for GR(1) specifications

When used as part of a hybrid controller, finite-memory strategies synthesized from LTL specifications rely on an accurate dynamics model in order to ensure correctness of trajectories. In the presence of uncertainty about this underlying model, there may exist unexpected trajectories that manifest as unexpected transitions under control of the strategy. While some disturbances can be captured by augmenting the dynamics model, such approaches may be conservative in that bisimulations may fail to exist for which strategies can be synthesized. In this paper, we characterize the tolerance of such hybrid controllers - synthesized for generalized reactivity(1) specifications- to disturbances that appear as unexpected jumps (transitions) to states in the discrete strategy part of the controller. As a first step, we show robustness to certain unexpected transitions that occur in a finite-manner, i.e., despite a certain number of unexpected jumps, the sequence of states obtained will still meet a stricter specification and hence the original specification. Additionally, we propose algorithms to improve robustness by increasing tolerance to additional disturbances. A robot gridworld example is presented to demonstrate the application of the developed ideas and also to obtain empirical computational and memory cost estimates

Distributed Real-time Anomaly Detection in Networked Industrial Sensing Systems

Reliable real-time sensing plays a vital role in ensuring the reliability and safety of industrial cyber-physical systems (CPSs) such as wireless sensor and actuator networks. For many reasons, such as harsh industrial environments, fault-prone sensors, or malicious attacks, sensor readings may be abnormal or faulty. This could lead to serious system performance degradation or even catastrophic failure. Current anomaly detection approaches are either centralized and complicated or restricted due to strict assumptions, which are not suitable for practical large-scale networked industrial sensing systems (NISSs), where sensing devices are connected via digital communications, such as wireless sensor networks or smart grid systems. In this paper, we introduce a fully distributed general anomaly detection (GAD) scheme, which uses graph theory and exploits spatiotemporal correlations of physical processes to carry out real-time anomaly detection for general large-scale NISSs. We formally prove the scalability of our GAD approach and evaluate the performance of GAD for two industrial applications: building structure monitoring and smart grids. Extensive trace-driven simulations validate our theoretical analysis and demonstrate that our approach can significantly outperform state-of-the-art approaches in terms of detection accuracy and efficiency

Design of a cyber physical industrial robotic manipulator

A key component of Cyber Physical Production Systems (CPPS) are connected Cyber Physical Machines (CPMs), or smart machines, which can act independently to each other and communicate in situation dependant ways. This new era of connected manufacturing has brought about new requirements for machines which are being deployed to the manufacturing shop floor. Cyber physical machines are not only required to execute industrial or manufacturing process, but they need to be capable of meeting other requirements, such as self-diagnoses, intelligent decision making, modularity and networkability. This research explores the design process of cyber physical machines as it is applied to the design of an industrial robotic manipulator.peer-reviewe

Generative design in the development of a robotic manipulator

The emergence of cyber physical production systems has brought with it an increased utilization of robotics in collaborative manufacturing environments. An approach to meet this demand is to democratize robotics by making cheaper more customizable robots that can be implemented by small and medium enterprises. To tackle this problem this research looks at using rapid prototyping techniques for the development of customizable robotic manipulators which can be implemented in cyber physical production systems. This research therefore contributes an approach for designing connected and rapid prototyped robotic manipulators. This approach considers both the software and hardware development required for implementing a robotic manipulator. Furthermore generative design, an evolutionary and artificial intelligence based approach, is used to design the link modules between the robot joints. This component has been identified as the ideal to be designed with this approach as it benefits most of the generative design approach coupled with rapid prototyping. This paper also explores a robotic manipulator control structure based on Ethernet control technology for implementation within cyber physical production systems.peer-reviewe

Enhancing tolerance to unexpected jumps in GR(1) games

When used as part of a hybrid controller, finite-memory strategies synthesized from linear-time temporal logic (LTL) specifications rely on an accurate dynamics model in order to ensure correctness of trajectories. In the presence of uncertainty about the underlying model, there may exist unexpected trajectories that manifest as unexpected transitions under control of the strategy. While some disturbances can be captured by augmenting the dynamics model, such approaches may be conservative in that bisimulations may fail to exist for which strategies can be synthesized. In this paper, we consider games of the GR(1) fragment of LTL, and we characterize the tolerance of hybrid controllers to perturbations that appear as unexpected jumps (transitions) to states in the discrete strategy part of the controller. As a first step, we show robustness to certain unexpected transitions that occur in a finite manner, i.e., despite a certain number of unexpected jumps, the sequence of states obtained will still meet a stricter specification and hence the original specification. Additionally, we propose algorithms to improve robustness by increasing tolerance to additional disturbances. A robot gridworld example is presented to demonstrate the application of the developed ideas and also to perform empirical analysis

Data analytics for stochastic control and prognostics in cyber-physical systems

In this dissertation, several novel cyber fault diagnosis and prognosis and defense methodologies for cyber-physical systems have been proposed. First, a novel routing scheme for wireless mesh network is proposed. An effective capacity estimation for P2P and E2E path is designed to guarantee the vital transmission safety. This scheme can ensure a high quality of service (QoS) under imperfect network condition, even cyber attacks. Then, the imperfection, uncertainties, and dynamics in the cyberspace are considered both in system model and controller design. A PDF identifier is proposed to capture the time-varying delays and its distribution. With the modification of traditional stochastic optimal control using PDF of delays, the assumption of full knowledge of network imperfection in priori is relaxed. This proposed controller is considered a novel resilience control strategy for cyber fault diagnosis and prognosis. After that, we turn to the development of a general framework for cyber fault diagnosis and prognosis schemes for CPSs wherein the cyberspace performance affect the physical system and vice versa. A novel cyber fault diagnosis scheme is proposed. It is capable of detecting cyber fault by monitoring the probability of delays. Also, the isolation of cyber and physical system fault is achieved with cooperating with the traditional observer based physical system fault detection. Next, a novel cyber fault prognosis scheme, which can detect and estimate cyber fault and its negative effects on system performance ahead of time, is proposed. Moreover, soft and hard cyber faults are isolated depending on whether potential threats on system stability is predicted. Finally, one-class SVM is employed to classify healthy and erroneous delays. Then, another cyber fault prognosis based on OCSVM is proposed --Abstract, page iv