Eventos Anais de eventos
COBEM 2023
27th International Congress of Mechanical Engineering
A Comparative Study of PID Controller Tuning Methods using Bio-Inspired Algorithms and IMC Approach for a Nonlinear Tank System
Submission Author:
Matheus Bawden Silverio de Castro , DF
Co-Authors:
Matheus Bawden Silverio de Castro, Gabriel da Silva Lima, Vinicius Rafael de Freitas, Eduardo Liberato, José Oniram de Aquino Limaverde Filho, Eugenio Fortaleza, Rafael Valladares de Almeida
Presenter: Matheus Bawden Silverio de Castro
doi://10.26678/ABCM.COBEM2023.COB2023-2168
Abstract
Proportional Integral Derivative (PID) control tuning based on Internal Model Control (IMC) is widely used in industrial control loops due to its simplicity and robustness. It is particularly common in the petroleum, chemical, pharmaceutical, and food industries, when it comes to tank level control. For nonlinear plants, the main drawbacks of the IMC tuning technique are: i) it is difficult to determine the optimal value of its only tuning parameter (closed-loop time constant), and ii) the need of a linearized model around an operation point, which can lead to significant errors. To overcome these limitations, bio-inspired algorithms such as Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) can be used as tuning methods. These algorithms can determine the PID controller gains only using the knowledge of the nonlinear model of the plant and a cost function, mitigating the errors associated with linearization while satisfying multiple control performance requirements, such as minimization of overshoot and rise time. In this study, in order to test the effectiveness of PSO and GWO as PID controller tuning method in comparison to IMC, numerical analyses were conducted to design a water level control for a nonlinear plant consisting of a pump, a cylindrical tank, and a conical tank, both connected in series. Different scenarios with one or more control performance requirements were evaluated for the three algorithms. The findings indicated that designing a PID controller based on PSO and GWO has improved the control performance of the nonlinear plant when compared to the well-known IMC approach, even in the presence of unknown disturbances or model uncertainties. Therefore, with the advancement of technology and the increasing demand for multiple control performance requirements in PID controller design, bio-inspired algorithms like PSO and GWO could be key players in the future of industrial control systems for nonlinear plants.
Keywords
Internal model control, Particle Swarm Optimization, Grey Wolf Optimization, PID tuning method, Nonlinear Tank System
