Real-Time Wireless Sensor-Actuator Networks for Cyber-Physical Systems

A cyber-physical system (CPS) employs tight integration of, and coordination between computational, networking, and physical elements. Wireless sensor-actuator networks provide a new communication technology for a broad range of CPS applications such as process control, smart manufacturing, and data center management. Sensing and control in these systems need to meet stringent real-time performance requirements on communication latency in challenging environments. There have been limited results on real-time scheduling theory for wireless sensor-actuator networks. Real-time transmission scheduling and analysis for wireless sensor-actuator networks requires new methodologies to deal with unique characteristics of wireless communication. Furthermore, the performance of a wireless control involves intricate interactions between real-time communication and control. This thesis research tackles these challenges and make a series of contributions to the theory and system for wireless CPS. (1) We establish a new real-time scheduling theory for wireless sensor-actuator networks. (2) We develop a scheduling-control co-design approach for holistic optimization of control performance in a wireless control system. (3) We design and implement a wireless sensor-actuator network for CPS in data center power management. (4) We expand our research to develop scheduling algorithms and analyses for real-time parallel computing to support computation-intensive CPS

Cyber-Physical Co-Design of Wireless Control Systems

Wireless sensor-actuator network (WSAN) technology is gaining rapid adoption in process industries because of its advantages in lowering deployment and maintenance cost in challenging environments. While early success of industrial WSANs has been recognized, significant potential remains in exploring WSANs as unified networks for industrial plants. This thesis research explores a cyber-physical co-design approach to design wireless control systems. To enable holistic studies of wireless control systems, we have developed the Wireless Cyber-Physical Simulator (WCPS), an integrated co-simulation environment that integrates Simulink and our implementation of WSANs based on the industrial WirelessHART standard. We further develop novel WSAN protocols tailored for advanced control designs for networked control systems. WCPS now works as the first simulator that features both linear and nonlinear physical plant models, state-of-art WirelessHART protocol stack, and realistic wireless network characteristics. A realistic wireless structural control study sheds light on the challenges of WSC and the limitations of a traditional structural control approach under realistic wireless conditions. Systematic emergency control results demonstrate that our real-time emergency communication approach enables timely emergency handling, while allowing regular feedback control loops to effectively share resources in WSANs during normal operations. A co-joint study of wireless routing and control highlights the importance of the co-design approach of wireless networks and control

Holistic Control for Cyber-Physical Systems

The Industrial Internet of Things (IIoT) are transforming industries through emerging technologies such as wireless networks, edge computing, and machine learning. However, IIoT technologies are not ready for control systems for industrial automation that demands control performance of physical processes, resiliency to both cyber and physical disturbances, and energy efficiency. To meet the challenges of IIoT-driven control, we propose holistic control as a cyber-physical system (CPS) approach to next-generation industrial automation systems. In contrast to traditional industrial automation systems where computing, communication, and control are managed in isolation, holistic control orchestrates the management of cyber platforms (networks and computing platforms) and physical plant control at run-time in an integrated architecture. Specifically, this dissertation research comprises the following primary components. Holistic wireless control: The core of holistic wireless control is a holistic controller comprising a plant controller and a network controller cooperating with each other. At run-time the holistic controller generates (1) control commands to the physical plant and (2) network reconfiguration commands to wireless networks based on both physical and network states. This part of dissertation research focused on the design and evaluation of holistic controllers exploiting a range of network reconfiguration strategies: (1) adapting transmission redundancy, (2) adapting sampling rates, (3) self-triggered control, and (4) dynamic transmission scheduling. Furthermore, we develop novel network reconfiguration protocols (NRP) as actuators to control network configurations in holistic control. Holistic edge control: This part of dissertation research explores edge computing as a multitier computing platform for holistic control. The proposed switching multi-tier control (SMC) dynamically switches controllers located on different computation platforms, thereby exploiting the trade-off between computation and communication in a multi-tier computing platform. We also design the stability switch between local and edge controllers under information loss from another perspective, based on co-design of edge and local controllers that are designed via a joint Lyapunov function. Real-time wireless cyber-physical simulators: To evaluate holistic control, we extend the Wireless Cyber-Physical Simulator (WCPS) to integrate simulated physical plants (in Simulink) with real wireless networks (WCPS-RT) and edge computing platforms (WCPS-EC). The real-time WCPS provides a holistic environment for CPS simulations that incorporate wireless dynamics that are challenging to simulate accurately, explore the impacts and trade-off of computation and communication of multi-tier platforms, and leverage simulation support for controllers and plants

Real-Time Sensor Networks and Systems for the Industrial IoT

The Industrial Internet of Things (Industrial IoT—IIoT) has emerged as the core construct behind the various cyber-physical systems constituting a principal dimension of the fourth Industrial Revolution. While initially born as the concept behind specific industrial applications of generic IoT technologies, for the optimization of operational efficiency in automation and control, it quickly enabled the achievement of the total convergence of Operational (OT) and Information Technologies (IT). The IIoT has now surpassed the traditional borders of automation and control functions in the process and manufacturing industry, shifting towards a wider domain of functions and industries, embraced under the dominant global initiatives and architectural frameworks of Industry 4.0 (or Industrie 4.0) in Germany, Industrial Internet in the US, Society 5.0 in Japan, and Made-in-China 2025 in China. As real-time embedded systems are quickly achieving ubiquity in everyday life and in industrial environments, and many processes already depend on real-time cyber-physical systems and embedded sensors, the integration of IoT with cognitive computing and real-time data exchange is essential for real-time analytics and realization of digital twins in smart environments and services under the various frameworks’ provisions. In this context, real-time sensor networks and systems for the Industrial IoT encompass multiple technologies and raise significant design, optimization, integration and exploitation challenges. The ten articles in this Special Issue describe advances in real-time sensor networks and systems that are significant enablers of the Industrial IoT paradigm. In the relevant landscape, the domain of wireless networking technologies is centrally positioned, as expected

From Open CNC systems to Cyber-Physical machine tools: a case study

The aim of next-generation Computer Numerical Control (CNC) is shifting from an open architecture, which has better flexibility, adaptability, versatility and expansibility, to a cyber-physical model, which offers real-time monitoring and control of the machining processes. This paper introduces a real case study to demonstrate such tendency from Open CNC systems to Cyber-Physical Machine Tools (CPMT) based on a low-power embedded platform. Firstly, a new open CNC architecture is presented, which is able to achieve high-precision, high-efficiency, and low-power consumption. Secondly, the open CNC architecture is extended to a CPMT by using Wireless Sensor Networks (WSN), where WSN is utilized to enable monitor and control the machining processes, and the integrated development platform is termed as CPMT. Finally, a case of health monitoring system for CPMT is designed and its system testing is carried out

Securing industrial cyber-physical systems: A run-time multi-layer monitoring

Industrial Cyber-Physical Systems (ICPSs) are widely deployed in monitoring and control of the nation's critical industrial processes such as water distribution networks and power grids. ICPSs are the tight integration of cyber (software) and physical entities connected via communication networks. Communication networks are typically realised via wireless channels to reduce the cost of wires and installation. However, they are also inherently unreliable, easy to disrupt and subvert, which makes them a potential target for cyber attacks. The failure of communication can cause data loss or delays, which can compromise system functionality and have catastrophic consequences due to the strict real-time requirements of ICPSs. Current run-time security monitors protect ICPSs either at communication level (through network intrusion monitors) or application level (through threat detection monitors). Such monitors are layer-specific and thus fail to detect advanced threats arising from the multi-layer disruption. In this paper, we present a multi-layer run-time security monitor that can detect discrepancies caused by interdependent application and communication layer attacks and prevent their propagation into the system's control loops. We demonstrate the effectiveness of the approach via an example of the ICPS used for control and monitoring of a water distribution network