Designing of PID Controllers for pH Neutralization Process

Ram, S. Sakthiya; Kumar, D. Dinesh; Meenakshipriya, B.

doi:10.17485/ijst/2016/v9i12/89940

Cited by 10 publications

(1 citation statement)

References 12 publications

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“…With the help of the BFO Algorithm the Kp, K i , K d values of PID and I-PD controllers are designed (Dwyer, 2006;Sakthiya Ram, Dinesh Kumar and Meenakshipriya;2016;. Much iterationis done and the mean value is considered for the comparison.…”

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confidence: 99%

Design of Heuristic Algorithm for Non-linear System

2016

Rev. Téc. Ing. Univ. Zulia

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In most of the industries tanks are used for mixing process. Normally, cylindrical tanks, cylindrical tanks with conical bottoms are used. Spherical tanks can be used to replace the conventional tanks, beacause of its increased production efficiency due to thorough mixing and discharging of materials, due to its cross section area. Controlling liquid level in it is highly challenging. Interacting spherical two tank system (ISTTS) is considered as nonlinear system in this paper. ISTTS is highly nonlinear system due to variation in cross area with respect to flow of liquid. Controlling the liquid level is highly challenging task in this system. Hence, heuristic algorithm such as Bacterial foraging optimization (BFO) based PID, BFO based I-PD controller is designed for the system. Heuristic algorithm is an optimization technique, which solves problem more easily than classic methods. BFO I-PD controller has no peak overshoot when compared to BFO PID controller in the servo response.

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confidence: 99%

Design of Heuristic Algorithm for Non-linear System

2016

Rev. Téc. Ing. Univ. Zulia

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Identification of First Order Plus Dead Time for a pH Neutralization Process Using Open Loop Test

Zainal,

Wahab,

Yusof

et al. 2023

Communications in Computer and Information Science

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Hybrid Approaches-Based Sliding-Mode Control for pH Process Control

et al. 2022

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This paper presents two hybrid control topologies; the topologies are designed by combining artificial intelligence approaches and sliding-mode control methodology. The first topology mixes the learning algorithm for multivariable data analysis (LAMDA) approach with sliding-mode control. The second offers a Takagi–Sugeno multimodel approach, internal model, and sliding-mode control. The process under study is a nonlinear pH neutralization process with high nonlinearities and time-varying parameters. The pH process is simulated for multiple reference changes, disturbance rejection, and noise in the transmitter. Performance indices are used to compare the proposed approaches quantitatively. The hybrid control topologies enhance the performance and robustness of the pH process under study.

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Designing of PID Controllers for pH Neutralization Process

Cited by 10 publications

References 12 publications

Design of Heuristic Algorithm for Non-linear System

Design of Heuristic Algorithm for Non-linear System

Identification of First Order Plus Dead Time for a pH Neutralization Process Using Open Loop Test

Hybrid Approaches-Based Sliding-Mode Control for pH Process Control

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