Decentralized PID Controller Tuning Based on Nonlinear Optimization to Minimize the Disturbance Effects in Coupled Loops

Thiago A M Euzebio,Moises T Da Silva,Andre S Yamashita

doi:10.1109/access.2021.3127795

Thiago A M Euzebio, Moises T Da Silva + Show 1 more

Open Access

https://doi.org/10.1109/access.2021.3127795

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Abstract

Decentralized proportional-integral-derivative (PID) control systems are widely used for multiple-input multiple-output (MIMO) control problems. However, decentralized controllers cannot suppress the plant interactions in multivariable systems, which are addressed in the controller tuning phase. In this paper, a decentralized PID tuning method is proposed in order to minimize the undesirable effects of the coupling between the inputs and outputs of the closed-loop system. For this purpose, the PID parameter tuning method solves a nonlinear optimization problem. This optimization problem is formulated with the criteria of the performance, robustness and multivariable stability of the closed-loop system. A single design parameter is required to specify the trade-off between performance and robustness. Simulation studies are conducted to demonstrate the effectiveness of the proposed method. The performance is compared to that of alternative tuning techniques from the literature. Results show that the proposed approach is a feasible candidate for industrial application, as it is simple to implement and capable of addressing robustness and stability concerns of plant operators.

Highlights

Decentralized proportional-integral-derivative (PID) controllers are frequently used in the regulatory control layer of industrial process plants
Single-input single-output (SISO) control is the dominating control structure in the industry for many reasons: it maintains the simplicity of the control system; it is easier to maintain; there are fewer tuning parameters compared to full multivariable controllers; it provides flexibility; and it can be made fault-tolerant [1]
Even when multiple-input multiple-output (MIMO) control strategies are used, such as model predictive control (MPC), they typically operate in a supervisory mode with decentralized PID controllers at the lower level [2]

Summary

Introduction

Decentralized proportional-integral-derivative (PID) controllers are frequently used in the regulatory control layer of industrial process plants. Even when multiple-input multiple-output (MIMO) control strategies are used, such as model predictive control (MPC), they typically operate in a supervisory mode with decentralized PID controllers at the lower level [2]. Regardless of their practical benefits, single-loop controllers cannot suppress the interactions between variables in MIMO processes; every system input affects every system output to some extent, unless static and dynamic relationships between a given input-output pair are nonexistent. Applying SISO tuning methods for a MIMO system often leads to poor performance and stability [3]

Methods

Results

Conclusion