Coordinated Distributed Moving Horizon State Estimation for Linear Systems

  • Author / Creator
  • Industrial chemical plants are typically large-scale systems with a number of processing units or subsystems, which are connected together via material, energy and information flows. The decentralized control frameworks which in general gives sub- optimal control performance is normally used for the control of these large-scale chemical processes. With the increasing scales of industrial processes and the interactions between subsystems, it is more challenging to design control systems to achieve the optimal plant operation, as well as to satisfy the increasing requirements on process safety and environmental regulations. In recent years, the distributed framework has been recognized as a promising framework for the control of large-scale systems with interactions. It is shown that the distributed framework has the potential to achieve the centralized framework performance, while maintaining the flexibility of the decentralized control scheme. This thesis focuses on the development of coordinated distributed state estimation schemes. Specially, we propose coordination algorithms for distributed moving horizon state estimators (MHEs) for discrete-time linear systems. In particular, the class of linear system is composed of several subsystems that interact with each other via their states. Two coordination algorithms are studied: the price-driven coordination algorithm and the prediction-driven coordination algorithm. In the proposed coordinated distributed MHE (CDMHE) schemes, each subsystem is associated with a local MHE. In the design of a local MHE, a coordinating term is incorporated into its cost function which is determined by an upper-layer coordinator. It is shown that both CDMHE schemes are able to achieve the estimation performance of the corresponding centralized design if convergence at each sampling time is ensured.

  • Subjects / Keywords
  • Graduation date
    Fall 2016
  • Type of Item
  • Degree
    Master of Science
  • DOI
  • 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.