Performance Evaluation of PID controller parameters optimization for two wheel mobile robot based on bat algorithm and particle swarm optimization
Tuning Proportional Integral Differential (PID) controller to the best value of gains is essential to develop a reliable controller for wheel mobile ro-bot (WMR). WMR is a nonlinear system that falls into category of underactuat-ed system where the inputs number is less than output number. The selec...
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ump-229092018-12-24T03:25:20Z http://umpir.ump.edu.my/id/eprint/22909/ Performance Evaluation of PID controller parameters optimization for two wheel mobile robot based on bat algorithm and particle swarm optimization Nur Aisyah Syafinaz, Suarin Pebrianti, Dwi Nurnajmin Qasrina, Ann Luhur, Bayuaji Muhammad, Syafrullah Indra, Riyanto TK Electrical engineering. Electronics Nuclear engineering Tuning Proportional Integral Differential (PID) controller to the best value of gains is essential to develop a reliable controller for wheel mobile ro-bot (WMR). WMR is a nonlinear system that falls into category of underactuat-ed system where the inputs number is less than output number. The selection of PID gains for such system is highly difficult. Optimization of PID controller us-ing Bat Algorithm (BA) is presented in this paper. BA as a nature inspired algo-rithm is used to search the optimum PID gains for two wheel mobile robot i.e. an off-the-shelf mobile robot called mBot so that the system will have good per-formance in term of steady state error and time response. Kinematic model of mBot robot is used to develop a simulation model to simulate the system. The result of tuning and optimizing PID gains using BA is compared with Particle Swarm Optimization (PSO). The tuning result by using BA outperformed PSO methods with faster processing time and best values of gain Kp and Kd to be applied in the WMR. The PID gain values obtained from BA and PSO are then applied on the WMR model. The result of time response and steady state error from BA shows better (?) performance compared to PSO. Settling time, rise time, % OS, and steady state error 2018 Conference or Workshop Item NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/22909/1/53.%20Performance%20Evaluation%20of%20PID%20controller%20parameters%20optimization.pdf pdf en http://umpir.ump.edu.my/id/eprint/22909/2/53.1%20Performance%20Evaluation%20of%20PID%20controller%20parameters%20optimization.pdf Nur Aisyah Syafinaz, Suarin and Pebrianti, Dwi and Nurnajmin Qasrina, Ann and Luhur, Bayuaji and Muhammad, Syafrullah and Indra, Riyanto (2018) Performance Evaluation of PID controller parameters optimization for two wheel mobile robot based on bat algorithm and particle swarm optimization. In: 10th National Technical Seminar on Underwater System Technology 2018 (NUSYS'18), 26 - 27 September 2018 , Universiti Malaysia Pahang, Pekan. pp. 1-11.. (Unpublished) |
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TK Electrical engineering. Electronics Nuclear engineering |
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TK Electrical engineering. Electronics Nuclear engineering Nur Aisyah Syafinaz, Suarin Pebrianti, Dwi Nurnajmin Qasrina, Ann Luhur, Bayuaji Muhammad, Syafrullah Indra, Riyanto Performance Evaluation of PID controller parameters optimization for two wheel mobile robot based on bat algorithm and particle swarm optimization |
description |
Tuning Proportional Integral Differential (PID) controller to the best value of gains is essential to develop a reliable controller for wheel mobile ro-bot (WMR). WMR is a nonlinear system that falls into category of underactuat-ed system where the inputs number is less than output number. The selection of PID gains for such system is highly difficult. Optimization of PID controller us-ing Bat Algorithm (BA) is presented in this paper. BA as a nature inspired algo-rithm is used to search the optimum PID gains for two wheel mobile robot i.e. an off-the-shelf mobile robot called mBot so that the system will have good per-formance in term of steady state error and time response. Kinematic model of mBot robot is used to develop a simulation model to simulate the system. The result of tuning and optimizing PID gains using BA is compared with Particle Swarm Optimization (PSO). The tuning result by using BA outperformed PSO methods with faster processing time and best values of gain Kp and Kd to be applied in the WMR. The PID gain values obtained from BA and PSO are then applied on the WMR model. The result of time response and steady state error from BA shows better (?) performance compared to PSO. Settling time, rise time, % OS, and steady state error |
format |
Conference or Workshop Item |
author |
Nur Aisyah Syafinaz, Suarin Pebrianti, Dwi Nurnajmin Qasrina, Ann Luhur, Bayuaji Muhammad, Syafrullah Indra, Riyanto |
author_facet |
Nur Aisyah Syafinaz, Suarin Pebrianti, Dwi Nurnajmin Qasrina, Ann Luhur, Bayuaji Muhammad, Syafrullah Indra, Riyanto |
author_sort |
Nur Aisyah Syafinaz, Suarin |
title |
Performance Evaluation of PID controller parameters optimization for two wheel mobile robot based on bat algorithm and particle swarm optimization |
title_short |
Performance Evaluation of PID controller parameters optimization for two wheel mobile robot based on bat algorithm and particle swarm optimization |
title_full |
Performance Evaluation of PID controller parameters optimization for two wheel mobile robot based on bat algorithm and particle swarm optimization |
title_fullStr |
Performance Evaluation of PID controller parameters optimization for two wheel mobile robot based on bat algorithm and particle swarm optimization |
title_full_unstemmed |
Performance Evaluation of PID controller parameters optimization for two wheel mobile robot based on bat algorithm and particle swarm optimization |
title_sort |
performance evaluation of pid controller parameters optimization for two wheel mobile robot based on bat algorithm and particle swarm optimization |
publishDate |
2018 |
url |
http://umpir.ump.edu.my/id/eprint/22909/ http://umpir.ump.edu.my/id/eprint/22909/1/53.%20Performance%20Evaluation%20of%20PID%20controller%20parameters%20optimization.pdf http://umpir.ump.edu.my/id/eprint/22909/2/53.1%20Performance%20Evaluation%20of%20PID%20controller%20parameters%20optimization.pdf |
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2023-09-18T22:34:05Z |
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2023-09-18T22:34:05Z |
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