Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization
Controller that uses PID parameters requires a good tuning method in order to improve the control system performance. Especially on hydraulic positioning system that is highly nonlinear and difficult to be controlled whereby PID parameters needs to be tuned to obtain optimum performance criteria. Tu...
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eprints |
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ump-115142017-04-03T04:06:32Z http://umpir.ump.edu.my/id/eprint/11514/ Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization Nur Iffah , Mohamed Azmi TJ Mechanical engineering and machinery Controller that uses PID parameters requires a good tuning method in order to improve the control system performance. Especially on hydraulic positioning system that is highly nonlinear and difficult to be controlled whereby PID parameters needs to be tuned to obtain optimum performance criteria. Tuning PID control method is divided into two namely the classical methods and the methods of artificial intelligence. Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. Previously, researchers had integrated PSO algorithms in the PID parameter tuning process. This research aims to improve the PSO-PID tuning algorithms by integrating the tuning process with the Variable Weight Grey-Taguchi Design of Experiment (DOE) method. This is done by conducting the DOE on the two PSO optimizing parameters: the limit of change in particle velocity and the weight distribution factor. Computer simulations and physical experiments were conducted by using the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE and the classical Ziegler-Nichols methods. They are implemented on the hydraulic positioning system. Simulation results show that the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE has reduced the rise time by 48.13% and settling time by 48.57% compared to the Ziegler-Nichols method. Physical experiment results also show that the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE tuning responds better than Ziegler-Nichols tuning. In conclusion, this research has improved the PSO-PID parameter by applying the PSO-PID algorithm together with the Variable Weight Grey-Taguchi DOE method as a good tuning method in the hydraulic positioning system. 2014 Thesis NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/11514/1/Optimization%20of%20PID%20parameters%20for%20hydraulic%20positioning%20system%20utilizing%20variable%20weight%20Grey-Taguchi%20and%20particle%20swarm%20optimization%20%28Table%20of%20content%29.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/11514/2/Optimization%20of%20PID%20parameters%20for%20hydraulic%20positioning%20system%20utilizing%20variable%20weight%20Grey-Taguchi%20and%20particle%20swarm%20optimization%20%28Abstract%29.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/11514/3/Optimization%20of%20PID%20parameters%20for%20hydraulic%20positioning%20system%20utilizing%20variable%20weight%20Grey-Taguchi%20and%20particle%20swarm%20optimization%20%28References%29.pdf Nur Iffah , Mohamed Azmi (2014) Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization. Masters thesis, Universiti Malaysia Pahang. http://iportal.ump.edu.my/lib/item?id=chamo:91346&theme=UMP2 |
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Digital Repository |
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Local University |
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Universiti Malaysia Pahang |
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UMP Institutional Repository |
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Online Access |
| language |
English English English |
| topic |
TJ Mechanical engineering and machinery |
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TJ Mechanical engineering and machinery Nur Iffah , Mohamed Azmi Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization |
| description |
Controller that uses PID parameters requires a good tuning method in order to improve the control system performance. Especially on hydraulic positioning system that is highly nonlinear and difficult to be controlled whereby PID parameters needs to be tuned to obtain optimum performance criteria. Tuning PID control method is divided into two namely the classical methods and the methods of artificial intelligence. Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. Previously, researchers had integrated PSO algorithms in the PID parameter tuning process. This research aims to improve the PSO-PID tuning algorithms by integrating the tuning process with the Variable Weight Grey-Taguchi Design of Experiment (DOE) method. This is done by conducting the DOE on the two PSO optimizing parameters: the limit of change in particle velocity and the weight distribution factor. Computer simulations and physical experiments were conducted by using the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE and the classical Ziegler-Nichols methods. They are implemented on the hydraulic positioning system. Simulation results show that the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE has reduced the rise time by 48.13% and settling time by 48.57% compared to the Ziegler-Nichols method. Physical experiment results also show that the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE tuning responds better than Ziegler-Nichols tuning. In conclusion, this research has improved the PSO-PID parameter by applying the PSO-PID algorithm together with the Variable Weight Grey-Taguchi DOE method as a good tuning method in the hydraulic positioning system. |
| format |
Thesis |
| author |
Nur Iffah , Mohamed Azmi |
| author_facet |
Nur Iffah , Mohamed Azmi |
| author_sort |
Nur Iffah , Mohamed Azmi |
| title |
Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization |
| title_short |
Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization |
| title_full |
Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization |
| title_fullStr |
Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization |
| title_full_unstemmed |
Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization |
| title_sort |
optimization of pid parameters for hydraulic positioning system utilizing variable weight grey-taguchi and particle swarm optimization |
| publishDate |
2014 |
| url |
http://umpir.ump.edu.my/id/eprint/11514/ http://umpir.ump.edu.my/id/eprint/11514/ http://umpir.ump.edu.my/id/eprint/11514/1/Optimization%20of%20PID%20parameters%20for%20hydraulic%20positioning%20system%20utilizing%20variable%20weight%20Grey-Taguchi%20and%20particle%20swarm%20optimization%20%28Table%20of%20content%29.pdf http://umpir.ump.edu.my/id/eprint/11514/2/Optimization%20of%20PID%20parameters%20for%20hydraulic%20positioning%20system%20utilizing%20variable%20weight%20Grey-Taguchi%20and%20particle%20swarm%20optimization%20%28Abstract%29.pdf http://umpir.ump.edu.my/id/eprint/11514/3/Optimization%20of%20PID%20parameters%20for%20hydraulic%20positioning%20system%20utilizing%20variable%20weight%20Grey-Taguchi%20and%20particle%20swarm%20optimization%20%28References%29.pdf |
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2023-09-18T22:12:21Z |
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2023-09-18T22:12:21Z |
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1777415111243202560 |