A comparative evaluation of PID-based optimisation controller algorithms for DC motor
Controllers; DC motors; Electric control equipment; Particle swarm optimization (PSO); Proportional control systems; Three term control systems; Two term control systems; Backtracking search algorithms; Comparative analysis; Comparative evaluations; Controller algorithm; Industrial activities; Optim...
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2023
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my.uniten.dspace-256592023-05-29T16:12:21Z A comparative evaluation of PID-based optimisation controller algorithms for DC motor Ahamed S.R. Parumasivam P. Hossain Lipu M.S. Hannan M.A. Ker P.J. 57219451953 57219453858 36518949700 7103014445 37461740800 Controllers; DC motors; Electric control equipment; Particle swarm optimization (PSO); Proportional control systems; Three term control systems; Two term control systems; Backtracking search algorithms; Comparative analysis; Comparative evaluations; Controller algorithm; Industrial activities; Optimum parameters; Particle swarm optimisation; Proportional integral derivative controllers; Electric machine control DC motors are generally used in industrial activities due to its simple structure and higher reliability. However, a DC motor is unable to control the operational speed as per required by the system. Proportional integral derivative (PID) controller is used in common for motor application due to its ease of control and operation. Nevertheless, the setting of PID parameters in DC motor control is difficult when the system is highly nonlinear and complex. Hence, the development of an improved auto-adjusted PID controller is an urgent necessity. This paper develops a robust PID controller-based optimisation algorithms for DC motor for finding the optimum parameters setting of PID controller. A comprehensive comparative analysis between PID-based backtracking search algorithms (BSA) and PID-based particle swarm optimisation (PSO) is provided. The conventional PID, PSO PID, and BSA PID models are evaluated based on overshoot reduction and settling time under ramp step and unit step speed variations. The results demonstrate that the PID controller with BSA achieves an optimum output with better dynamic and static performance. Copyright � 2020 Inderscience Enterprises Ltd. Final 2023-05-29T08:12:20Z 2023-05-29T08:12:20Z 2020 Article 10.1504/IJAAC.2020.110076 2-s2.0-85092772575 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092772575&doi=10.1504%2fIJAAC.2020.110076&partnerID=40&md5=6f6f4180bc9464a1cc1429ceb3175ca3 https://irepository.uniten.edu.my/handle/123456789/25659 14 5-Jun 634 655 Inderscience Publishers Scopus |
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| description |
Controllers; DC motors; Electric control equipment; Particle swarm optimization (PSO); Proportional control systems; Three term control systems; Two term control systems; Backtracking search algorithms; Comparative analysis; Comparative evaluations; Controller algorithm; Industrial activities; Optimum parameters; Particle swarm optimisation; Proportional integral derivative controllers; Electric machine control |
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57219451953 |
| author_facet |
57219451953 Ahamed S.R. Parumasivam P. Hossain Lipu M.S. Hannan M.A. Ker P.J. |
| format |
Article |
| author |
Ahamed S.R. Parumasivam P. Hossain Lipu M.S. Hannan M.A. Ker P.J. |
| spellingShingle |
Ahamed S.R. Parumasivam P. Hossain Lipu M.S. Hannan M.A. Ker P.J. A comparative evaluation of PID-based optimisation controller algorithms for DC motor |
| author_sort |
Ahamed S.R. |
| title |
A comparative evaluation of PID-based optimisation controller algorithms for DC motor |
| title_short |
A comparative evaluation of PID-based optimisation controller algorithms for DC motor |
| title_full |
A comparative evaluation of PID-based optimisation controller algorithms for DC motor |
| title_fullStr |
A comparative evaluation of PID-based optimisation controller algorithms for DC motor |
| title_full_unstemmed |
A comparative evaluation of PID-based optimisation controller algorithms for DC motor |
| title_sort |
comparative evaluation of pid-based optimisation controller algorithms for dc motor |
| publisher |
Inderscience Publishers |
| publishDate |
2023 |
| _version_ |
1806428365697056768 |
| score |
13.222552 |