Abstract

As a typical representative of distributed model predictive control, distributed dynamic matrix control (DDMC) is able to satisfy the basic control requirements for large-scale systems. However, the constraints and disturbances in actual industrial process usually lead to the slow set-point target tracking, large overshoot and weak anti-interference ability of the system. Therefore, the relevant requirements may not be met for some complex industrial processes. The existing distributed PID type dynamic matrix control (PID-DDMC) method can improve the control performance, but it maybe not accurate enough in some cases. Based on this background, this article introduces fractional order PID (FOPID) into distributed dynamic matrix control, and proposes a distributed fractional order PID type dynamic matrix control (FOPID-DDMC) algorithm. To compare with the conventional PID control, it expands the control and parameter setting range of the controller, and makes the control effect of the controller more accurate. Furthermore, the coupling effect among subsystems is dispelled by adopting the Nash optimal theory, and information interaction between the subsystems through network communication is realized, thereby, completing the optimization of the whole large-scale system. Finally, through a numerical simulation example and a level-temperature control process, the feasibility of the proposed algorithm is demonstrated by comparing with the traditional DDMC and PID-DDMC.

Highlights

  • With the development of modern society, the progress of science and technology and the growth of communication network, the industrial system is developing towards to large-scale and complex

  • Richard et al put forward a novel distributed model predictive control (DMPC) for coupled constraint system in [11], which transforms a single large-scale optimization problem into several smaller optimization problems, among which all decisions meet coupling constraints by transferring relevant plan data

  • After introducing fractional order PID, a controller based on distributed dynamic matrix control is designed, it divides the complicated large-scale system into subsystems, with each subsystem being controlled through a corresponding FOPID dynamic matrix controller, and uses Nash optimal theory to eliminate the coupling effect among subsystems, which can ensure the overall performance of large-scale system, and make up for the shortcomings of traditional distributed dynamic matrix control

Read more

Summary

INTRODUCTION

With the development of modern society, the progress of science and technology and the growth of communication network, the industrial system is developing towards to large-scale and complex. In order to control large-scale system more accurately, a distributed FOPID dynamic matrix control algorithm is proposed by combining FOPID and DDMC, which guarantees the good control performance of large-scale system, as well as further improves the freedom of control parameter design. After introducing fractional order PID, a controller based on distributed dynamic matrix control is designed, it divides the complicated large-scale system into subsystems, with each subsystem being controlled through a corresponding FOPID dynamic matrix controller, and uses Nash optimal theory to eliminate the coupling effect among subsystems, which can ensure the overall performance of large-scale system, and make up for the shortcomings of traditional distributed dynamic matrix control. Compared with the traditional distributed integer order PID type dynamic matrix control optimization method, the integral order and differential order are added to expand the control range and parameter setting range of the controller, so that the system control effect is more superior, and the system flexibility, robustness and overall control performance are improved.

PRELIMINARIES OF FRACTIONAL ORDER PID
TUNING RULES OF FRACTIONAL ORDER PID PARAMETERS
PREDICTION MODEL IN DISTRIBUTED DYNAMIC MATRIX CONTROL
DESIGN OF DISTRIBUTED FRACTIONAL ORDER PID
SIMULATION STUDY
CASE 2
CONCLUSION
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call