James Moyne

Bio: James Moyne is an academic researcher from University of Michigan. The author has contributed to research in topics: Process control & Control system. The author has an hindex of 28, co-authored 129 publications receiving 4703 citations. Previous affiliations of James Moyne include Applied Materials & Massachusetts Institute of Technology.

Performance evaluation of control networks: Ethernet, ControlNet, and DeviceNet

Abstract: Many different network types have been promoted for use in control systems. In this article, we compare three of them: the Ethernet bus, with carrier sense multiple access with collision detection, token-passing bus (e.g., ControlNet), and controller area network bus (e.g., DeviceNet). We consider how each control network can be used as a communication backbone for a networked control system connecting sensors, actuators, and controllers. A detailed discussion of the medium access control sublayer protocol for each network is provided. For each protocol, we study the key parameters of the corresponding network when used in a control situation, including network utilization, magnitude of the expected time delay, and characteristics of time delays. Simulation results are presented for several different scenarios, and the advantages and disadvantages of each network are summarized.

Network design consideration for distributed control systems

Abstract: This paper discusses the impact of network architecture on control performance in a class of distributed control systems called networked control systems (NCSs) and provides design considerations related to control quality of performance as well as network quality of service. The integrated network-control system changes the characteristics of time delays between application devices. This study first identifies several key components of the time delay through an analysis of network protocols and control dynamics. The analysis of network and control parameters is used to determine an acceptable working range of sampling periods in an NCS. A network-control simulator and an experimental networked a machine tool have been developed to help validate and demonstrate the performance analysis results and identify the special performance characteristics in an NCS. These performance characteristics are useful guidelines for choosing the network and control parameters when designing an NCS.

Using deadbands to reduce communication in networked control systems

Abstract: The most effective way to improve networked control systems (NCSs) performance is to reduce network traffic. By adapting a system to a network configuration, the communication medium is more efficiently used and time-delays are minimized. Adjustable deadbands are explored as a solution to reduce network traffic in NCSs. The stability of deadband control is derived and then verified via simulation. A method to determine the size of the deadbands is presented that relies on a performance metric that takes into account system response as well as network traffic. The effectiveness of deadband control with different controllers is studied as well as the effect of disturbances and plant uncertainty.

The Emergence of Industrial Control Networks for Manufacturing Control, Diagnostics, and Safety Data

Abstract: The most notable trend in manufacturing over the past five years is probably the move towards networks at all levels. At lower levels in the factory infrastructure, networks provide higher reliability, visibility, and diagnosability, and enable capabilities such as distributed control, diagnostics, safety, and device interoperability. At higher levels, networks can leverage internet services to enable factory-wide automated scheduling, control, and diagnostics; improve data storage and visibility; and open the door to e-manufacturing. This paper explores current trends in the use of networks for distributed, multilevel control, diagnostics, and safety. Network performance characteristics such as delay, delay variability, and determinism are evaluated in the context of networked control applications. This paper also discusses future networking trends in each of these categories and describes the actual application of all three categories of networks on a reconfigurable factory testbed (RFT) at the University of Michigan. Control, diagnostics, and safety systems are all enabled in the RFT utilizing multitier networked technology including DeviceNet, PROFIBUS, OPC, wired and wireless Ethernet, and SafetyBUS p. This paper concludes with a discussion of trends in industrial networking, including the move to wireless for all categories, and the issues that must be addressed to realize these trends

The emergence of industrial control networks for manufacturing control, diagnostics, and safety data : There is wide use of ethernet for system diagnostics and control, and inclusion of safety features on the same network is being debated; the trend is towards wireless communications

Abstract: The most notable trend in manufacturing over the past five years is probably the move towards networks at all levels. At lower levels in the factory infrastructure, networks provide higher reliability, visibility, and diagnosability, and enable capabilities such as distributed control, diagnostics, safety, and device interoperability. At higher levels, networks can leverage internet services to enable factory-wide automat- ed scheduling, control, and diagnostics; improve data storage and visibility; and open the door to e-manufacturing. This paper explores current trends in the use of networks for distributed, multilevel control, diagnostics, and safety. Network performance characteristics such as delay, delay variability, and determinism are evaluated in the context of networked control applications. This paper also discusses future network- ing trends in each of these categories and describes the actual application of all three categories of networks on a reconfigur- able factory testbed (RFT) at the University of Michigan. Control, diagnostics, and safety systems are all enabled in the RFT utilizing multitier networked technology including Device- Net, PROFIBUS, OPC, wired and wireless Ethernet, and Safe- tyBUS p. This paper concludes with a discussion of trends in industrial networking, including the move to wireless for all categories, and the issues that must be addressed to realize these trends.

An introduction to event-triggered and self-triggered control

Abstract: Recent developments in computer and communication technologies have led to a new type of large-scale resource-constrained wireless embedded control systems. It is desirable in these systems to limit the sensor and control computation and/or communication to instances when the system needs attention. However, classical sampled-data control is based on performing sensing and actuation periodically rather than when the system needs attention. This paper provides an introduction to event- and self-triggered control systems where sensing and actuation is performed when needed. Event-triggered control is reactive and generates sensor sampling and control actuation when, for instance, the plant state deviates more than a certain threshold from a desired value. Self-triggered control, on the other hand, is proactive and computes the next sampling or actuation instance ahead of time. The basics of these control strategies are introduced together with a discussion on the differences between state feedback and output feedback for event-triggered control. It is also shown how event- and self-triggered control can be implemented using existing wireless communication technology. Some applications to wireless control in process industry are discussed as well.