Parameters identification of Bouc–Wen hysteresis model for piezoelectric actuators using hybrid adaptive differential evolution and Jaya algorithm
The nonlinearities hysteresis of the piezoelectric-PZT actuator can greatly degrade in precise positioning applications. Therefore, modeling and identifying the hysteresis parameter of PZT actuator are still many challenges nowadays. In this paper, the hybrid adaptive differential evolution and Jaya...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Son, Nguyen Ngoc [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020transfer abstract |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Copper oxide nanomaterials synthesized from simple copper salts as active catalysts for electrocatalytic water oxidation - Liu, Xiang ELSEVIER, 2015, the international journal of real-time automation : a journal affiliated with IFAC, the International Federation of Automatic Control, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:87 ; year:2020 ; pages:0 |
| Links: |
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| DOI / URN: |
10.1016/j.engappai.2019.103317 |
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| 245 | 1 | 0 | |a Parameters identification of Bouc–Wen hysteresis model for piezoelectric actuators using hybrid adaptive differential evolution and Jaya algorithm |
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| 520 | |a The nonlinearities hysteresis of the piezoelectric-PZT actuator can greatly degrade in precise positioning applications. Therefore, modeling and identifying the hysteresis parameter of PZT actuator are still many challenges nowadays. In this paper, the hybrid adaptive differential evolution and Jaya algorithm (aDE-Jaya) is proposed to identify the Bouc–Wen hysteresis model of a piezoelectric actuator. In the aDE-Jaya algorithm, the improvement is focused on a hybrid mutant operator “DE/rand/1” and Jaya operator tried to balance between two contradictory aspects of their performance: exploration and exploitation and adaptive control parameters (mutant factor F, crossover rate CR, population size NP) to enhance the convergence efficiency. To prove the effectiveness and robustness of the proposed aDE-Jaya algorithm, it is tested on 8 benchmark functions and compared with other state-of-the-art optimizations. The comparison results show that aDE-Jaya has better performance in convergence rate and accuracy. After that, aDE-Jaya is applied to identify the Bouc–Wen hysteresis model based on experimental input–output data. The identified Bouc–Wen hysteresis resulted is used to design the feedforward controller to test accurate identification. As a consequent, the proposed aDE-Jaya algorithm can successfully identify the highly hysteretic nonlinearity of the piezoelectric actuator with perfect precision. | ||
| 520 | |a The nonlinearities hysteresis of the piezoelectric-PZT actuator can greatly degrade in precise positioning applications. Therefore, modeling and identifying the hysteresis parameter of PZT actuator are still many challenges nowadays. In this paper, the hybrid adaptive differential evolution and Jaya algorithm (aDE-Jaya) is proposed to identify the Bouc–Wen hysteresis model of a piezoelectric actuator. In the aDE-Jaya algorithm, the improvement is focused on a hybrid mutant operator “DE/rand/1” and Jaya operator tried to balance between two contradictory aspects of their performance: exploration and exploitation and adaptive control parameters (mutant factor F, crossover rate CR, population size NP) to enhance the convergence efficiency. To prove the effectiveness and robustness of the proposed aDE-Jaya algorithm, it is tested on 8 benchmark functions and compared with other state-of-the-art optimizations. The comparison results show that aDE-Jaya has better performance in convergence rate and accuracy. After that, aDE-Jaya is applied to identify the Bouc–Wen hysteresis model based on experimental input–output data. The identified Bouc–Wen hysteresis resulted is used to design the feedforward controller to test accurate identification. As a consequent, the proposed aDE-Jaya algorithm can successfully identify the highly hysteretic nonlinearity of the piezoelectric actuator with perfect precision. | ||
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10.1016/j.engappai.2019.103317 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000831.pica (DE-627)ELV048578142 (ELSEVIER)S0952-1976(19)30270-2 DE-627 ger DE-627 rakwb eng 540 VZ 610 VZ 44.00 bkl Son, Nguyen Ngoc verfasserin aut Parameters identification of Bouc–Wen hysteresis model for piezoelectric actuators using hybrid adaptive differential evolution and Jaya algorithm 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The nonlinearities hysteresis of the piezoelectric-PZT actuator can greatly degrade in precise positioning applications. Therefore, modeling and identifying the hysteresis parameter of PZT actuator are still many challenges nowadays. In this paper, the hybrid adaptive differential evolution and Jaya algorithm (aDE-Jaya) is proposed to identify the Bouc–Wen hysteresis model of a piezoelectric actuator. In the aDE-Jaya algorithm, the improvement is focused on a hybrid mutant operator “DE/rand/1” and Jaya operator tried to balance between two contradictory aspects of their performance: exploration and exploitation and adaptive control parameters (mutant factor F, crossover rate CR, population size NP) to enhance the convergence efficiency. To prove the effectiveness and robustness of the proposed aDE-Jaya algorithm, it is tested on 8 benchmark functions and compared with other state-of-the-art optimizations. The comparison results show that aDE-Jaya has better performance in convergence rate and accuracy. After that, aDE-Jaya is applied to identify the Bouc–Wen hysteresis model based on experimental input–output data. The identified Bouc–Wen hysteresis resulted is used to design the feedforward controller to test accurate identification. As a consequent, the proposed aDE-Jaya algorithm can successfully identify the highly hysteretic nonlinearity of the piezoelectric actuator with perfect precision. The nonlinearities hysteresis of the piezoelectric-PZT actuator can greatly degrade in precise positioning applications. Therefore, modeling and identifying the hysteresis parameter of PZT actuator are still many challenges nowadays. In this paper, the hybrid adaptive differential evolution and Jaya algorithm (aDE-Jaya) is proposed to identify the Bouc–Wen hysteresis model of a piezoelectric actuator. In the aDE-Jaya algorithm, the improvement is focused on a hybrid mutant operator “DE/rand/1” and Jaya operator tried to balance between two contradictory aspects of their performance: exploration and exploitation and adaptive control parameters (mutant factor F, crossover rate CR, population size NP) to enhance the convergence efficiency. To prove the effectiveness and robustness of the proposed aDE-Jaya algorithm, it is tested on 8 benchmark functions and compared with other state-of-the-art optimizations. The comparison results show that aDE-Jaya has better performance in convergence rate and accuracy. After that, aDE-Jaya is applied to identify the Bouc–Wen hysteresis model based on experimental input–output data. The identified Bouc–Wen hysteresis resulted is used to design the feedforward controller to test accurate identification. As a consequent, the proposed aDE-Jaya algorithm can successfully identify the highly hysteretic nonlinearity of the piezoelectric actuator with perfect precision. Jaya algorithm Elsevier Nonlinear hysteresis Elsevier Parameters identification Elsevier Differential evolution Elsevier Piezoelectric actuator Elsevier Van Kien, Cao oth Anh, Ho Pham Huy oth Enthalten in Elsevier Science Liu, Xiang ELSEVIER Copper oxide nanomaterials synthesized from simple copper salts as active catalysts for electrocatalytic water oxidation 2015 the international journal of real-time automation : a journal affiliated with IFAC, the International Federation of Automatic Control Amsterdam [u.a.] (DE-627)ELV013402978 volume:87 year:2020 pages:0 https://doi.org/10.1016/j.engappai.2019.103317 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.00 Medizin: Allgemeines VZ AR 87 2020 0 |
| spelling |
10.1016/j.engappai.2019.103317 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000831.pica (DE-627)ELV048578142 (ELSEVIER)S0952-1976(19)30270-2 DE-627 ger DE-627 rakwb eng 540 VZ 610 VZ 44.00 bkl Son, Nguyen Ngoc verfasserin aut Parameters identification of Bouc–Wen hysteresis model for piezoelectric actuators using hybrid adaptive differential evolution and Jaya algorithm 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The nonlinearities hysteresis of the piezoelectric-PZT actuator can greatly degrade in precise positioning applications. Therefore, modeling and identifying the hysteresis parameter of PZT actuator are still many challenges nowadays. In this paper, the hybrid adaptive differential evolution and Jaya algorithm (aDE-Jaya) is proposed to identify the Bouc–Wen hysteresis model of a piezoelectric actuator. In the aDE-Jaya algorithm, the improvement is focused on a hybrid mutant operator “DE/rand/1” and Jaya operator tried to balance between two contradictory aspects of their performance: exploration and exploitation and adaptive control parameters (mutant factor F, crossover rate CR, population size NP) to enhance the convergence efficiency. To prove the effectiveness and robustness of the proposed aDE-Jaya algorithm, it is tested on 8 benchmark functions and compared with other state-of-the-art optimizations. The comparison results show that aDE-Jaya has better performance in convergence rate and accuracy. After that, aDE-Jaya is applied to identify the Bouc–Wen hysteresis model based on experimental input–output data. The identified Bouc–Wen hysteresis resulted is used to design the feedforward controller to test accurate identification. As a consequent, the proposed aDE-Jaya algorithm can successfully identify the highly hysteretic nonlinearity of the piezoelectric actuator with perfect precision. The nonlinearities hysteresis of the piezoelectric-PZT actuator can greatly degrade in precise positioning applications. Therefore, modeling and identifying the hysteresis parameter of PZT actuator are still many challenges nowadays. In this paper, the hybrid adaptive differential evolution and Jaya algorithm (aDE-Jaya) is proposed to identify the Bouc–Wen hysteresis model of a piezoelectric actuator. In the aDE-Jaya algorithm, the improvement is focused on a hybrid mutant operator “DE/rand/1” and Jaya operator tried to balance between two contradictory aspects of their performance: exploration and exploitation and adaptive control parameters (mutant factor F, crossover rate CR, population size NP) to enhance the convergence efficiency. To prove the effectiveness and robustness of the proposed aDE-Jaya algorithm, it is tested on 8 benchmark functions and compared with other state-of-the-art optimizations. The comparison results show that aDE-Jaya has better performance in convergence rate and accuracy. After that, aDE-Jaya is applied to identify the Bouc–Wen hysteresis model based on experimental input–output data. The identified Bouc–Wen hysteresis resulted is used to design the feedforward controller to test accurate identification. As a consequent, the proposed aDE-Jaya algorithm can successfully identify the highly hysteretic nonlinearity of the piezoelectric actuator with perfect precision. Jaya algorithm Elsevier Nonlinear hysteresis Elsevier Parameters identification Elsevier Differential evolution Elsevier Piezoelectric actuator Elsevier Van Kien, Cao oth Anh, Ho Pham Huy oth Enthalten in Elsevier Science Liu, Xiang ELSEVIER Copper oxide nanomaterials synthesized from simple copper salts as active catalysts for electrocatalytic water oxidation 2015 the international journal of real-time automation : a journal affiliated with IFAC, the International Federation of Automatic Control Amsterdam [u.a.] (DE-627)ELV013402978 volume:87 year:2020 pages:0 https://doi.org/10.1016/j.engappai.2019.103317 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.00 Medizin: Allgemeines VZ AR 87 2020 0 |
| allfields_unstemmed |
10.1016/j.engappai.2019.103317 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000831.pica (DE-627)ELV048578142 (ELSEVIER)S0952-1976(19)30270-2 DE-627 ger DE-627 rakwb eng 540 VZ 610 VZ 44.00 bkl Son, Nguyen Ngoc verfasserin aut Parameters identification of Bouc–Wen hysteresis model for piezoelectric actuators using hybrid adaptive differential evolution and Jaya algorithm 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The nonlinearities hysteresis of the piezoelectric-PZT actuator can greatly degrade in precise positioning applications. Therefore, modeling and identifying the hysteresis parameter of PZT actuator are still many challenges nowadays. In this paper, the hybrid adaptive differential evolution and Jaya algorithm (aDE-Jaya) is proposed to identify the Bouc–Wen hysteresis model of a piezoelectric actuator. In the aDE-Jaya algorithm, the improvement is focused on a hybrid mutant operator “DE/rand/1” and Jaya operator tried to balance between two contradictory aspects of their performance: exploration and exploitation and adaptive control parameters (mutant factor F, crossover rate CR, population size NP) to enhance the convergence efficiency. To prove the effectiveness and robustness of the proposed aDE-Jaya algorithm, it is tested on 8 benchmark functions and compared with other state-of-the-art optimizations. The comparison results show that aDE-Jaya has better performance in convergence rate and accuracy. After that, aDE-Jaya is applied to identify the Bouc–Wen hysteresis model based on experimental input–output data. The identified Bouc–Wen hysteresis resulted is used to design the feedforward controller to test accurate identification. As a consequent, the proposed aDE-Jaya algorithm can successfully identify the highly hysteretic nonlinearity of the piezoelectric actuator with perfect precision. The nonlinearities hysteresis of the piezoelectric-PZT actuator can greatly degrade in precise positioning applications. Therefore, modeling and identifying the hysteresis parameter of PZT actuator are still many challenges nowadays. In this paper, the hybrid adaptive differential evolution and Jaya algorithm (aDE-Jaya) is proposed to identify the Bouc–Wen hysteresis model of a piezoelectric actuator. In the aDE-Jaya algorithm, the improvement is focused on a hybrid mutant operator “DE/rand/1” and Jaya operator tried to balance between two contradictory aspects of their performance: exploration and exploitation and adaptive control parameters (mutant factor F, crossover rate CR, population size NP) to enhance the convergence efficiency. To prove the effectiveness and robustness of the proposed aDE-Jaya algorithm, it is tested on 8 benchmark functions and compared with other state-of-the-art optimizations. The comparison results show that aDE-Jaya has better performance in convergence rate and accuracy. After that, aDE-Jaya is applied to identify the Bouc–Wen hysteresis model based on experimental input–output data. The identified Bouc–Wen hysteresis resulted is used to design the feedforward controller to test accurate identification. As a consequent, the proposed aDE-Jaya algorithm can successfully identify the highly hysteretic nonlinearity of the piezoelectric actuator with perfect precision. Jaya algorithm Elsevier Nonlinear hysteresis Elsevier Parameters identification Elsevier Differential evolution Elsevier Piezoelectric actuator Elsevier Van Kien, Cao oth Anh, Ho Pham Huy oth Enthalten in Elsevier Science Liu, Xiang ELSEVIER Copper oxide nanomaterials synthesized from simple copper salts as active catalysts for electrocatalytic water oxidation 2015 the international journal of real-time automation : a journal affiliated with IFAC, the International Federation of Automatic Control Amsterdam [u.a.] (DE-627)ELV013402978 volume:87 year:2020 pages:0 https://doi.org/10.1016/j.engappai.2019.103317 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.00 Medizin: Allgemeines VZ AR 87 2020 0 |
| allfieldsGer |
10.1016/j.engappai.2019.103317 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000831.pica (DE-627)ELV048578142 (ELSEVIER)S0952-1976(19)30270-2 DE-627 ger DE-627 rakwb eng 540 VZ 610 VZ 44.00 bkl Son, Nguyen Ngoc verfasserin aut Parameters identification of Bouc–Wen hysteresis model for piezoelectric actuators using hybrid adaptive differential evolution and Jaya algorithm 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The nonlinearities hysteresis of the piezoelectric-PZT actuator can greatly degrade in precise positioning applications. Therefore, modeling and identifying the hysteresis parameter of PZT actuator are still many challenges nowadays. In this paper, the hybrid adaptive differential evolution and Jaya algorithm (aDE-Jaya) is proposed to identify the Bouc–Wen hysteresis model of a piezoelectric actuator. In the aDE-Jaya algorithm, the improvement is focused on a hybrid mutant operator “DE/rand/1” and Jaya operator tried to balance between two contradictory aspects of their performance: exploration and exploitation and adaptive control parameters (mutant factor F, crossover rate CR, population size NP) to enhance the convergence efficiency. To prove the effectiveness and robustness of the proposed aDE-Jaya algorithm, it is tested on 8 benchmark functions and compared with other state-of-the-art optimizations. The comparison results show that aDE-Jaya has better performance in convergence rate and accuracy. After that, aDE-Jaya is applied to identify the Bouc–Wen hysteresis model based on experimental input–output data. The identified Bouc–Wen hysteresis resulted is used to design the feedforward controller to test accurate identification. As a consequent, the proposed aDE-Jaya algorithm can successfully identify the highly hysteretic nonlinearity of the piezoelectric actuator with perfect precision. The nonlinearities hysteresis of the piezoelectric-PZT actuator can greatly degrade in precise positioning applications. Therefore, modeling and identifying the hysteresis parameter of PZT actuator are still many challenges nowadays. In this paper, the hybrid adaptive differential evolution and Jaya algorithm (aDE-Jaya) is proposed to identify the Bouc–Wen hysteresis model of a piezoelectric actuator. In the aDE-Jaya algorithm, the improvement is focused on a hybrid mutant operator “DE/rand/1” and Jaya operator tried to balance between two contradictory aspects of their performance: exploration and exploitation and adaptive control parameters (mutant factor F, crossover rate CR, population size NP) to enhance the convergence efficiency. To prove the effectiveness and robustness of the proposed aDE-Jaya algorithm, it is tested on 8 benchmark functions and compared with other state-of-the-art optimizations. The comparison results show that aDE-Jaya has better performance in convergence rate and accuracy. After that, aDE-Jaya is applied to identify the Bouc–Wen hysteresis model based on experimental input–output data. The identified Bouc–Wen hysteresis resulted is used to design the feedforward controller to test accurate identification. As a consequent, the proposed aDE-Jaya algorithm can successfully identify the highly hysteretic nonlinearity of the piezoelectric actuator with perfect precision. Jaya algorithm Elsevier Nonlinear hysteresis Elsevier Parameters identification Elsevier Differential evolution Elsevier Piezoelectric actuator Elsevier Van Kien, Cao oth Anh, Ho Pham Huy oth Enthalten in Elsevier Science Liu, Xiang ELSEVIER Copper oxide nanomaterials synthesized from simple copper salts as active catalysts for electrocatalytic water oxidation 2015 the international journal of real-time automation : a journal affiliated with IFAC, the International Federation of Automatic Control Amsterdam [u.a.] (DE-627)ELV013402978 volume:87 year:2020 pages:0 https://doi.org/10.1016/j.engappai.2019.103317 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.00 Medizin: Allgemeines VZ AR 87 2020 0 |
| allfieldsSound |
10.1016/j.engappai.2019.103317 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000831.pica (DE-627)ELV048578142 (ELSEVIER)S0952-1976(19)30270-2 DE-627 ger DE-627 rakwb eng 540 VZ 610 VZ 44.00 bkl Son, Nguyen Ngoc verfasserin aut Parameters identification of Bouc–Wen hysteresis model for piezoelectric actuators using hybrid adaptive differential evolution and Jaya algorithm 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The nonlinearities hysteresis of the piezoelectric-PZT actuator can greatly degrade in precise positioning applications. Therefore, modeling and identifying the hysteresis parameter of PZT actuator are still many challenges nowadays. In this paper, the hybrid adaptive differential evolution and Jaya algorithm (aDE-Jaya) is proposed to identify the Bouc–Wen hysteresis model of a piezoelectric actuator. In the aDE-Jaya algorithm, the improvement is focused on a hybrid mutant operator “DE/rand/1” and Jaya operator tried to balance between two contradictory aspects of their performance: exploration and exploitation and adaptive control parameters (mutant factor F, crossover rate CR, population size NP) to enhance the convergence efficiency. To prove the effectiveness and robustness of the proposed aDE-Jaya algorithm, it is tested on 8 benchmark functions and compared with other state-of-the-art optimizations. The comparison results show that aDE-Jaya has better performance in convergence rate and accuracy. After that, aDE-Jaya is applied to identify the Bouc–Wen hysteresis model based on experimental input–output data. The identified Bouc–Wen hysteresis resulted is used to design the feedforward controller to test accurate identification. As a consequent, the proposed aDE-Jaya algorithm can successfully identify the highly hysteretic nonlinearity of the piezoelectric actuator with perfect precision. The nonlinearities hysteresis of the piezoelectric-PZT actuator can greatly degrade in precise positioning applications. Therefore, modeling and identifying the hysteresis parameter of PZT actuator are still many challenges nowadays. In this paper, the hybrid adaptive differential evolution and Jaya algorithm (aDE-Jaya) is proposed to identify the Bouc–Wen hysteresis model of a piezoelectric actuator. In the aDE-Jaya algorithm, the improvement is focused on a hybrid mutant operator “DE/rand/1” and Jaya operator tried to balance between two contradictory aspects of their performance: exploration and exploitation and adaptive control parameters (mutant factor F, crossover rate CR, population size NP) to enhance the convergence efficiency. To prove the effectiveness and robustness of the proposed aDE-Jaya algorithm, it is tested on 8 benchmark functions and compared with other state-of-the-art optimizations. The comparison results show that aDE-Jaya has better performance in convergence rate and accuracy. After that, aDE-Jaya is applied to identify the Bouc–Wen hysteresis model based on experimental input–output data. The identified Bouc–Wen hysteresis resulted is used to design the feedforward controller to test accurate identification. As a consequent, the proposed aDE-Jaya algorithm can successfully identify the highly hysteretic nonlinearity of the piezoelectric actuator with perfect precision. Jaya algorithm Elsevier Nonlinear hysteresis Elsevier Parameters identification Elsevier Differential evolution Elsevier Piezoelectric actuator Elsevier Van Kien, Cao oth Anh, Ho Pham Huy oth Enthalten in Elsevier Science Liu, Xiang ELSEVIER Copper oxide nanomaterials synthesized from simple copper salts as active catalysts for electrocatalytic water oxidation 2015 the international journal of real-time automation : a journal affiliated with IFAC, the International Federation of Automatic Control Amsterdam [u.a.] (DE-627)ELV013402978 volume:87 year:2020 pages:0 https://doi.org/10.1016/j.engappai.2019.103317 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.00 Medizin: Allgemeines VZ AR 87 2020 0 |
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Therefore, modeling and identifying the hysteresis parameter of PZT actuator are still many challenges nowadays. In this paper, the hybrid adaptive differential evolution and Jaya algorithm (aDE-Jaya) is proposed to identify the Bouc–Wen hysteresis model of a piezoelectric actuator. In the aDE-Jaya algorithm, the improvement is focused on a hybrid mutant operator “DE/rand/1” and Jaya operator tried to balance between two contradictory aspects of their performance: exploration and exploitation and adaptive control parameters (mutant factor F, crossover rate CR, population size NP) to enhance the convergence efficiency. To prove the effectiveness and robustness of the proposed aDE-Jaya algorithm, it is tested on 8 benchmark functions and compared with other state-of-the-art optimizations. The comparison results show that aDE-Jaya has better performance in convergence rate and accuracy. 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parameters identification of bouc–wen hysteresis model for piezoelectric actuators using hybrid adaptive differential evolution and jaya algorithm |
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Parameters identification of Bouc–Wen hysteresis model for piezoelectric actuators using hybrid adaptive differential evolution and Jaya algorithm |
| abstract |
The nonlinearities hysteresis of the piezoelectric-PZT actuator can greatly degrade in precise positioning applications. Therefore, modeling and identifying the hysteresis parameter of PZT actuator are still many challenges nowadays. In this paper, the hybrid adaptive differential evolution and Jaya algorithm (aDE-Jaya) is proposed to identify the Bouc–Wen hysteresis model of a piezoelectric actuator. In the aDE-Jaya algorithm, the improvement is focused on a hybrid mutant operator “DE/rand/1” and Jaya operator tried to balance between two contradictory aspects of their performance: exploration and exploitation and adaptive control parameters (mutant factor F, crossover rate CR, population size NP) to enhance the convergence efficiency. To prove the effectiveness and robustness of the proposed aDE-Jaya algorithm, it is tested on 8 benchmark functions and compared with other state-of-the-art optimizations. The comparison results show that aDE-Jaya has better performance in convergence rate and accuracy. After that, aDE-Jaya is applied to identify the Bouc–Wen hysteresis model based on experimental input–output data. The identified Bouc–Wen hysteresis resulted is used to design the feedforward controller to test accurate identification. As a consequent, the proposed aDE-Jaya algorithm can successfully identify the highly hysteretic nonlinearity of the piezoelectric actuator with perfect precision. |
| abstractGer |
The nonlinearities hysteresis of the piezoelectric-PZT actuator can greatly degrade in precise positioning applications. Therefore, modeling and identifying the hysteresis parameter of PZT actuator are still many challenges nowadays. In this paper, the hybrid adaptive differential evolution and Jaya algorithm (aDE-Jaya) is proposed to identify the Bouc–Wen hysteresis model of a piezoelectric actuator. In the aDE-Jaya algorithm, the improvement is focused on a hybrid mutant operator “DE/rand/1” and Jaya operator tried to balance between two contradictory aspects of their performance: exploration and exploitation and adaptive control parameters (mutant factor F, crossover rate CR, population size NP) to enhance the convergence efficiency. To prove the effectiveness and robustness of the proposed aDE-Jaya algorithm, it is tested on 8 benchmark functions and compared with other state-of-the-art optimizations. The comparison results show that aDE-Jaya has better performance in convergence rate and accuracy. After that, aDE-Jaya is applied to identify the Bouc–Wen hysteresis model based on experimental input–output data. The identified Bouc–Wen hysteresis resulted is used to design the feedforward controller to test accurate identification. As a consequent, the proposed aDE-Jaya algorithm can successfully identify the highly hysteretic nonlinearity of the piezoelectric actuator with perfect precision. |
| abstract_unstemmed |
The nonlinearities hysteresis of the piezoelectric-PZT actuator can greatly degrade in precise positioning applications. Therefore, modeling and identifying the hysteresis parameter of PZT actuator are still many challenges nowadays. In this paper, the hybrid adaptive differential evolution and Jaya algorithm (aDE-Jaya) is proposed to identify the Bouc–Wen hysteresis model of a piezoelectric actuator. In the aDE-Jaya algorithm, the improvement is focused on a hybrid mutant operator “DE/rand/1” and Jaya operator tried to balance between two contradictory aspects of their performance: exploration and exploitation and adaptive control parameters (mutant factor F, crossover rate CR, population size NP) to enhance the convergence efficiency. To prove the effectiveness and robustness of the proposed aDE-Jaya algorithm, it is tested on 8 benchmark functions and compared with other state-of-the-art optimizations. The comparison results show that aDE-Jaya has better performance in convergence rate and accuracy. After that, aDE-Jaya is applied to identify the Bouc–Wen hysteresis model based on experimental input–output data. The identified Bouc–Wen hysteresis resulted is used to design the feedforward controller to test accurate identification. As a consequent, the proposed aDE-Jaya algorithm can successfully identify the highly hysteretic nonlinearity of the piezoelectric actuator with perfect precision. |
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Parameters identification of Bouc–Wen hysteresis model for piezoelectric actuators using hybrid adaptive differential evolution and Jaya algorithm |
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