Nurul Najihah, Zulkifli and Mohd Syakirin, Ramli (2022) Comparative analysis of the model-free tuning techniques for integral state feedback controller of a liquid slosh suppression system. In: The 6th National Conference for Postgraduate Research (NCON-PGR 2022) , 15 November 2022 , Virtual Conference, Universiti Malaysia Pahang, Malaysia. p. 141..
|
Pdf
Comparative analysis of the model-free tuning techniques for integral state feedback controller of a liquid slosh suppression system.pdf Download (453kB) | Preview |
Abstract
This paper presents a comparative study of the model-free controller tuning for a liquid slosh suppression system. Data-driven Pole Placement (DPP) and Fictitious-Reference-Iterative-Tuning with Particle Swarm Optimization (FRIT-PSO) are the two algorithms proposed as the tuning methods for the selected controller structure. These techniques are desirable to obtain the optimal parameters gain of the state feedback controller with the integral term by utilizing only the recorded input-and-output data generated from a one-shot experiment. The system’s performance analysis of the controlled system is carried out using MATLAB Simulink. The assessment proves that the model-free control approaches exhibit a good response of the cart in terms of the trajectory tracking of the cart’s motion while maintaining the liquid slosh motion at the minimum level.
Item Type: | Conference or Workshop Item (Lecture) |
---|---|
Uncontrolled Keywords: | Integral state feedback controller; DPP; FRIT-PSO. |
Subjects: | T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Faculty/Division: | Institute of Postgraduate Studies Faculty of Electrical and Electronic Engineering Technology |
Depositing User: | Mr Muhamad Firdaus Janih@Jaini |
Date Deposited: | 14 Mar 2023 08:42 |
Last Modified: | 14 Mar 2023 08:42 |
URI: | http://umpir.ump.edu.my/id/eprint/37022 |
Download Statistic: | View Download Statistics |
Actions (login required)
![]() |
View Item |