Distributed Moving Horizon State Estimation of Nonlinear Systems

• Author / Creator

  Zhang, Jing

• Large-scale complex chemical processes increasingly appear in the modern process industry due to their economic efficiency. Such a large-scale complex chemical process usually consists of several unit operations (subsystems), which are connected together through material and energy flows. Because of the increased process scale and the significant interactions between different subsystems, it poses great challenges in the design of automatic control systems for such large-scale complex chemical processes which are desired to fulfill the fundamental safety, environmental sustainability and profitability requirements. In recent years, distributed predictive process control has emerged as an attractive control approach to handle the scale and interactions of large-scale complex chemical processes. It has been demonstrated that distributed predictive process control can achieve improved closed-loop performance compared with decentralized control while preserving the flexibility of the decentralized framework. However, almost all of the existing distributed predictive process control designs are developed under the assumption that the state measurements of subsystems or the entire system are available. This assumption does not hold in many applications.

  This thesis presents a robust distributed moving horizon state estimation (DMHE) scheme that is appropriate for output feedback distributed predictive control of nonlinear systems as well as approaches for reducing the communication demand of the proposed DMHE scheme and a strategy for handling delays in the communication between subsystem estimators. First, the proposed robust DMHE scheme is presented for a class of nonlinear systems that are composed of several subsystems. It is assumed that the subsystems interact with each other via their states only. Subsequently, two triggered communication algorithms are introduced for the proposed DMHE scheme to reduce the number of information transmissions between subsystems. Following this, an approach is proposed to handle the potential time-varying delays in the communication between the subsystem estimators. The applicability and effectiveness of the proposed approaches are illustrated via their applications to chemical process examples.

• Subjects / Keywords

  • Moving horizon estimation
  • Distributed state estimation
  • Chemical processes
  • Nonlinear systems

• Graduation date

  Fall 2014

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/R34X0D

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.