Page 235 - Distributed model predictive control for plant-wide systems

10

Networked Distributed

Predictive Control with Inputs

and Information Structure

Constraints

10.1 Introduction

As mentioned in Chapter 7, the main advantage of distributed model predictive control
(DMPC) is that it has the characteristics of good flexibility and error tolerance. These charac-
teristics are based on the fact that the subsystem-based controllers are relevantly independent
to each other. It means that if the number of subsystems that each subsystem-based MPC
communicates will decrease, the flexibility and the ability of error tolerance of the whole
closed-loop control system will increase. In addition, in some fields or processes the global
information are unavailable to controllers (e.g., in multi-intelligent vehicle system) for the
management or the system scale reasons. Thus to design a DMPC that could significantly
improve the global performance of the closed-loop system with limited information structure
constraints is valuable.
In an effort to achieve a tradeoff between the global performance of the entire system and
the computational burden, an intuitively appealing strategy is proposed in Chapter 7, where
each subsystem-based MPC only considers the cost of its own subsystem and those of the
subsystems it directly impacts on. Such a design can be referred to as networked distributed
MPC (N-DMPC). Chapter 7 applies this design idea to a metallurgy system and explains
why this coordination strategy could improve the global performance. Numerical and prac-
tical experiments show that this coordination strategy could obtain a performance close to that
of a classical centralized MPC. However, the method introduced in Chapter 7 does not take
constraints into consideration in the DMPC design.
Under the DMPC framework, Ref. [51] provides a design for nonlinear continuous sys-
tems, which uses a constraint to limit the error between the future state sequences (or called

Distributed Model Predictive Control for Plant-Wide Systems, First Edition. Shaoyuan Li and Yi Zheng.
© 2015 John Wiley & Sons (Asia) Pte Ltd. Published 2015 by John Wiley & Sons (Asia) Pte Ltd.