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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.

Design of Distributed Fractional Order PID Type Dynamic Matrix Controller for Large-Scale Process Systems