Key Takeaways & Executive Findings
- •• Introduces a novel MFAC-SA-PID controller that integrates fuzzy self-adjusting PID with model-free adaptive control to handle strong nonlinearity in pH neutralization. • Provides rigorous proof of convergence and stability for the proposed MFAC-SA-PID method. • Demonstrates superior control performance over traditional MFAC and improved MFAC (IMFAC) methods in simulations, especially under step disturbances. • Offers a practical solution for pH process control with enhanced robustness and stability, addressing parameter tuning challenges in industrial applications.
Abstract
In this paper, a new model free adaptive control method based on self-adjusting PID algorithm (MFAC-SA-PID) is proposed to solve the problem that the pH process with strong nonlinearity is difficult to control near the neutralization point. The MFAC-SA-PID method also solves the problem that the parameters of the model free adaptive control (MFAC) method are not easy to be adjusted and the effect is not obvious by introducing a fuzzy self-adjusting algorithm to adjust the controller parameters. Then the convergence and stability of the MFAC-SA-PID method are proved in this paper. In the simulation study, the control performance of the MFAC-SA-PID method proposed in this paper is compared with the traditional MFAC method and the improved model free adaptive control (IMFAC) method, respectively. The results show that the proposed MFAC-SA-PID method has better control effect on the pH neutralization process. The MFAC-SA-PID control performance also outperforms the traditional MFAC method and IMFAC method when step input disturbances are added, which indicates that the MFAC-SA-PID method has better robustness and stability.
1. Introduction
As an important indicator in industrial processes, pH is widely used in chemical production, wastewater treatment and biological processes. Since the quality of pH process control can directly affect the safe operation of the whole system, its precise control has important practical significance [1e5].
Since the beginning of the 20th century, scholars have been studying pH process control. With the rapid development of computer technology, more control methods have been proposed. But taking into account the economic cost, production environment and other conditions, PID control method are mostly used in industrial practice. Because the pH process has serious exponential nonlinearity, large hysteresis and high sensitivity near the neutralization point, and there are also uncertainties in the flow and concentration of the neutralized liquid in the actual process, the traditional PID control method is limited by the problem of parameter tuning, so it is sometimes difficult to achieve a satisfactory control effect. As a result, the control of pH process has been a difficult problem in industrial process control at present [6e13].
For many years, pH process as a typical representative of nonlinear system, the research on pH process control method has received extensive attention from scholars at home and abroad. A. Nejati et al. compared the performance of adaptive inverse controllers and global linearized controllers in pH process control [14]. Chen et al. [15] proposed a sliding mode control method based on the closed-loop transfer function recovery method for the equivalent first-order model of the pH neutralization process. Although the above control methods achieve stable control of the pH process to some extent, most of them adopt model linearization treatment and the design of the controller relies on an accurate mathematical model, which results in poor control performance when the system has strong nonlinearity and uncertainty.
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Kang Liu, You Fan, Juan Chen (2024). A model free adaptive control method based on self-adjusting PID algorithm in pH neutralization process. Chinese Journal of Chemical Engineering. https://doi.org/10.1016/j_cjche_1448
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Frequently Asked Questions
What is the main contribution of the MFAC-SA-PID method?
The MFAC-SA-PID method combines model-free adaptive control with a fuzzy self-adjusting PID algorithm to handle strong nonlinearity in pH neutralization processes, improving control performance and robustness while simplifying parameter tuning.
How does the proposed method compare to traditional MFAC and IMFAC?
Simulation results show that MFAC-SA-PID outperforms both traditional MFAC and improved MFAC (IMFAC) in terms of control effect and robustness, especially when step input disturbances are introduced.
Is the stability of the MFAC-SA-PID method proven?
Yes, the paper provides a theoretical proof of convergence and stability for the proposed MFAC-SA-PID method.
What are the practical applications of this research?
The method is applicable to pH control in chemical production, wastewater treatment, and biological processes, where precise pH regulation is critical for safety and efficiency.
What is the significance of using fuzzy self-adjusting PID in MFAC?
The fuzzy self-adjusting algorithm automatically tunes the PID parameters, addressing the difficulty of parameter adjustment in traditional MFAC and enhancing the controller's adaptability to nonlinear and uncertain systems.
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