Tree physiology optimization on SISO and MIMO PID control tuning
The tuning of proportional�integral�derivative (PID) controller is essential for any control application in order to ensure the best performance by step change or disturbance. This paper presents the tuning of PID controller for single-input single-output (SISO) and multiple-input multiple-outpu...
| Main Authors: | Halim, A.H., Ismail, I. |
|---|---|
| Format: | Article |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.21481 / |
| Published: |
Springer London
2018
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utp-eprints.214812019-01-10T05:39:49Z Tree physiology optimization on SISO and MIMO PID control tuning Halim, A.H. Ismail, I. The tuning of proportional�integral�derivative (PID) controller is essential for any control application in order to ensure the best performance by step change or disturbance. This paper presents the tuning of PID controller for single-input single-output (SISO) and multiple-input multiple-output (MIMO) control systems using tree physiology optimization (TPO). TPO is a metaheuristic algorithm inspired from a plant growth system derived based on the idea of plant architecture and Thornley model (TM). The basic principle of TM simplifies the plant growth into shoots and roots part. The plant shoots grow towards sunlight with the help of nutrients supplied by the root system in order to undergo photosynthesis process, a process of converting light photon into carbon. The carbon gain from the shoots extension will be supplied to the root system in order for the root to grow and search for water plus nutrients. As a result, the nutrients are supplied upwards towards shoot system for further extension. This concept runs iteratively in order to ensure optimum plant growth. The iterative search of shoot towards better light supported by the root counterparts leads to an optimization idea of TPO algorithm. TPO also has a unique exploration strategy due to its multiple branches and shoots that can be defined by user. This concept may improve the search mechanism with a better trade-off between diversification and intensification search. A simulation of SISO control system and an industrial application of MIMO control are applied to demonstrate the effectiveness of the proposed algorithm and compared with other optimization methods such as particle swarm optimization, Ziegler�Nichols, Tyreus�Luyben and Chien�Hrones�Reswick methods. The results clearly exhibit the capability of TPO algorithm towards finding the optimum PID parameters for SISO and MIMO process with faster settling time and better performance with respect to other methods. © 2018 The Natural Computing Applications Forum Springer London 2018 Article PeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049127945&doi=10.1007%2fs00521-018-3588-9&partnerID=40&md5=e0f51d3369bfb84db7f0394928d74019 Halim, A.H. and Ismail, I. (2018) Tree physiology optimization on SISO and MIMO PID control tuning. Neural Computing and Applications . pp. 1-11. http://eprints.utp.edu.my/21481/ |
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Universiti Teknologi Petronas |
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| description |
The tuning of proportional�integral�derivative (PID) controller is essential for any control application in order to ensure the best performance by step change or disturbance. This paper presents the tuning of PID controller for single-input single-output (SISO) and multiple-input multiple-output (MIMO) control systems using tree physiology optimization (TPO). TPO is a metaheuristic algorithm inspired from a plant growth system derived based on the idea of plant architecture and Thornley model (TM). The basic principle of TM simplifies the plant growth into shoots and roots part. The plant shoots grow towards sunlight with the help of nutrients supplied by the root system in order to undergo photosynthesis process, a process of converting light photon into carbon. The carbon gain from the shoots extension will be supplied to the root system in order for the root to grow and search for water plus nutrients. As a result, the nutrients are supplied upwards towards shoot system for further extension. This concept runs iteratively in order to ensure optimum plant growth. The iterative search of shoot towards better light supported by the root counterparts leads to an optimization idea of TPO algorithm. TPO also has a unique exploration strategy due to its multiple branches and shoots that can be defined by user. This concept may improve the search mechanism with a better trade-off between diversification and intensification search. A simulation of SISO control system and an industrial application of MIMO control are applied to demonstrate the effectiveness of the proposed algorithm and compared with other optimization methods such as particle swarm optimization, Ziegler�Nichols, Tyreus�Luyben and Chien�Hrones�Reswick methods. The results clearly exhibit the capability of TPO algorithm towards finding the optimum PID parameters for SISO and MIMO process with faster settling time and better performance with respect to other methods. © 2018 The Natural Computing Applications Forum |
| format |
Article |
| author |
Halim, A.H. Ismail, I. |
| spellingShingle |
Halim, A.H. Ismail, I. Tree physiology optimization on SISO and MIMO PID control tuning |
| author_sort |
Halim, A.H. |
| title |
Tree physiology optimization on SISO and MIMO PID control tuning |
| title_short |
Tree physiology optimization on SISO and MIMO PID control tuning |
| title_full |
Tree physiology optimization on SISO and MIMO PID control tuning |
| title_fullStr |
Tree physiology optimization on SISO and MIMO PID control tuning |
| title_full_unstemmed |
Tree physiology optimization on SISO and MIMO PID control tuning |
| title_sort |
tree physiology optimization on siso and mimo pid control tuning |
| publisher |
Springer London |
| publishDate |
2018 |
| url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049127945&doi=10.1007%2fs00521-018-3588-9&partnerID=40&md5=e0f51d3369bfb84db7f0394928d74019 http://eprints.utp.edu.my/21481/ |
| _version_ |
1741196466824675328 |
| score |
11.62408 |