Robust control synthesis using coefficient diagram method and µ-analysis: an aerospace example
Abstract This paper develops a structured controller synthesis method which satisfies robust stability and robust performance. In the proposed method (µ-CDM), coefficient diagram method (CDM) is employed to synthesize a structured controller and µ-analysis is used to evaluate the robustness of the c...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Abtahi, Seid Farhad [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2018 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer-Verlag GmbH Germany, part of Springer Nature 2018 |
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| Übergeordnetes Werk: |
Enthalten in: International journal of dynamics and control - Berlin : Springer, 2013, 7(2018), 2 vom: 23. Juli, Seite 595-606 |
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| Übergeordnetes Werk: |
volume:7 ; year:2018 ; number:2 ; day:23 ; month:07 ; pages:595-606 |
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| DOI / URN: |
10.1007/s40435-018-0462-7 |
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| Katalog-ID: |
SPR036474932 |
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| 100 | 1 | |a Abtahi, Seid Farhad |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Robust control synthesis using coefficient diagram method and µ-analysis: an aerospace example |
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| 520 | |a Abstract This paper develops a structured controller synthesis method which satisfies robust stability and robust performance. In the proposed method (µ-CDM), coefficient diagram method (CDM) is employed to synthesize a structured controller and µ-analysis is used to evaluate the robustness of the controller. A supervisory particle swarm optimization utilizes the CDM and µ-analysis in an iterative manner in order to reach an optimal robustness bound. To evaluate the performance of the proposed method, it has been used to synthesize a robust autopilot for an aerospace system. Numerical simulations confirm the feasibility of µ-CDM and show the acceptable closed-loop performance in presence of various model uncertainties. The performance of the proposed controller is compared with that of a conventional CDM controller and a D–K iterations controller. | ||
| 650 | 4 | |a Robust control |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a µ-Analysis |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Uncertain systems |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Coefficient diagram method |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Autopilot |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Azadi Yazdi, Ehsan |0 (orcid)0000-0001-6615-8327 |4 aut | |
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10.1007/s40435-018-0462-7 doi (DE-627)SPR036474932 (SPR)s40435-018-0462-7-e DE-627 ger DE-627 rakwb eng Abtahi, Seid Farhad verfasserin aut Robust control synthesis using coefficient diagram method and µ-analysis: an aerospace example 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract This paper develops a structured controller synthesis method which satisfies robust stability and robust performance. In the proposed method (µ-CDM), coefficient diagram method (CDM) is employed to synthesize a structured controller and µ-analysis is used to evaluate the robustness of the controller. A supervisory particle swarm optimization utilizes the CDM and µ-analysis in an iterative manner in order to reach an optimal robustness bound. To evaluate the performance of the proposed method, it has been used to synthesize a robust autopilot for an aerospace system. Numerical simulations confirm the feasibility of µ-CDM and show the acceptable closed-loop performance in presence of various model uncertainties. The performance of the proposed controller is compared with that of a conventional CDM controller and a D–K iterations controller. Robust control (dpeaa)DE-He213 µ-Analysis (dpeaa)DE-He213 Uncertain systems (dpeaa)DE-He213 Coefficient diagram method (dpeaa)DE-He213 Autopilot (dpeaa)DE-He213 Azadi Yazdi, Ehsan (orcid)0000-0001-6615-8327 aut Enthalten in International journal of dynamics and control Berlin : Springer, 2013 7(2018), 2 vom: 23. Juli, Seite 595-606 (DE-627)745617794 (DE-600)2714518-9 2195-2698 nnns volume:7 year:2018 number:2 day:23 month:07 pages:595-606 https://dx.doi.org/10.1007/s40435-018-0462-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 7 2018 2 23 07 595-606 |
| spelling |
10.1007/s40435-018-0462-7 doi (DE-627)SPR036474932 (SPR)s40435-018-0462-7-e DE-627 ger DE-627 rakwb eng Abtahi, Seid Farhad verfasserin aut Robust control synthesis using coefficient diagram method and µ-analysis: an aerospace example 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract This paper develops a structured controller synthesis method which satisfies robust stability and robust performance. In the proposed method (µ-CDM), coefficient diagram method (CDM) is employed to synthesize a structured controller and µ-analysis is used to evaluate the robustness of the controller. A supervisory particle swarm optimization utilizes the CDM and µ-analysis in an iterative manner in order to reach an optimal robustness bound. To evaluate the performance of the proposed method, it has been used to synthesize a robust autopilot for an aerospace system. Numerical simulations confirm the feasibility of µ-CDM and show the acceptable closed-loop performance in presence of various model uncertainties. The performance of the proposed controller is compared with that of a conventional CDM controller and a D–K iterations controller. Robust control (dpeaa)DE-He213 µ-Analysis (dpeaa)DE-He213 Uncertain systems (dpeaa)DE-He213 Coefficient diagram method (dpeaa)DE-He213 Autopilot (dpeaa)DE-He213 Azadi Yazdi, Ehsan (orcid)0000-0001-6615-8327 aut Enthalten in International journal of dynamics and control Berlin : Springer, 2013 7(2018), 2 vom: 23. Juli, Seite 595-606 (DE-627)745617794 (DE-600)2714518-9 2195-2698 nnns volume:7 year:2018 number:2 day:23 month:07 pages:595-606 https://dx.doi.org/10.1007/s40435-018-0462-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 7 2018 2 23 07 595-606 |
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10.1007/s40435-018-0462-7 doi (DE-627)SPR036474932 (SPR)s40435-018-0462-7-e DE-627 ger DE-627 rakwb eng Abtahi, Seid Farhad verfasserin aut Robust control synthesis using coefficient diagram method and µ-analysis: an aerospace example 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract This paper develops a structured controller synthesis method which satisfies robust stability and robust performance. In the proposed method (µ-CDM), coefficient diagram method (CDM) is employed to synthesize a structured controller and µ-analysis is used to evaluate the robustness of the controller. A supervisory particle swarm optimization utilizes the CDM and µ-analysis in an iterative manner in order to reach an optimal robustness bound. To evaluate the performance of the proposed method, it has been used to synthesize a robust autopilot for an aerospace system. Numerical simulations confirm the feasibility of µ-CDM and show the acceptable closed-loop performance in presence of various model uncertainties. The performance of the proposed controller is compared with that of a conventional CDM controller and a D–K iterations controller. Robust control (dpeaa)DE-He213 µ-Analysis (dpeaa)DE-He213 Uncertain systems (dpeaa)DE-He213 Coefficient diagram method (dpeaa)DE-He213 Autopilot (dpeaa)DE-He213 Azadi Yazdi, Ehsan (orcid)0000-0001-6615-8327 aut Enthalten in International journal of dynamics and control Berlin : Springer, 2013 7(2018), 2 vom: 23. Juli, Seite 595-606 (DE-627)745617794 (DE-600)2714518-9 2195-2698 nnns volume:7 year:2018 number:2 day:23 month:07 pages:595-606 https://dx.doi.org/10.1007/s40435-018-0462-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 7 2018 2 23 07 595-606 |
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10.1007/s40435-018-0462-7 doi (DE-627)SPR036474932 (SPR)s40435-018-0462-7-e DE-627 ger DE-627 rakwb eng Abtahi, Seid Farhad verfasserin aut Robust control synthesis using coefficient diagram method and µ-analysis: an aerospace example 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract This paper develops a structured controller synthesis method which satisfies robust stability and robust performance. In the proposed method (µ-CDM), coefficient diagram method (CDM) is employed to synthesize a structured controller and µ-analysis is used to evaluate the robustness of the controller. A supervisory particle swarm optimization utilizes the CDM and µ-analysis in an iterative manner in order to reach an optimal robustness bound. To evaluate the performance of the proposed method, it has been used to synthesize a robust autopilot for an aerospace system. Numerical simulations confirm the feasibility of µ-CDM and show the acceptable closed-loop performance in presence of various model uncertainties. The performance of the proposed controller is compared with that of a conventional CDM controller and a D–K iterations controller. Robust control (dpeaa)DE-He213 µ-Analysis (dpeaa)DE-He213 Uncertain systems (dpeaa)DE-He213 Coefficient diagram method (dpeaa)DE-He213 Autopilot (dpeaa)DE-He213 Azadi Yazdi, Ehsan (orcid)0000-0001-6615-8327 aut Enthalten in International journal of dynamics and control Berlin : Springer, 2013 7(2018), 2 vom: 23. Juli, Seite 595-606 (DE-627)745617794 (DE-600)2714518-9 2195-2698 nnns volume:7 year:2018 number:2 day:23 month:07 pages:595-606 https://dx.doi.org/10.1007/s40435-018-0462-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 7 2018 2 23 07 595-606 |
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10.1007/s40435-018-0462-7 doi (DE-627)SPR036474932 (SPR)s40435-018-0462-7-e DE-627 ger DE-627 rakwb eng Abtahi, Seid Farhad verfasserin aut Robust control synthesis using coefficient diagram method and µ-analysis: an aerospace example 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract This paper develops a structured controller synthesis method which satisfies robust stability and robust performance. In the proposed method (µ-CDM), coefficient diagram method (CDM) is employed to synthesize a structured controller and µ-analysis is used to evaluate the robustness of the controller. A supervisory particle swarm optimization utilizes the CDM and µ-analysis in an iterative manner in order to reach an optimal robustness bound. To evaluate the performance of the proposed method, it has been used to synthesize a robust autopilot for an aerospace system. Numerical simulations confirm the feasibility of µ-CDM and show the acceptable closed-loop performance in presence of various model uncertainties. The performance of the proposed controller is compared with that of a conventional CDM controller and a D–K iterations controller. Robust control (dpeaa)DE-He213 µ-Analysis (dpeaa)DE-He213 Uncertain systems (dpeaa)DE-He213 Coefficient diagram method (dpeaa)DE-He213 Autopilot (dpeaa)DE-He213 Azadi Yazdi, Ehsan (orcid)0000-0001-6615-8327 aut Enthalten in International journal of dynamics and control Berlin : Springer, 2013 7(2018), 2 vom: 23. Juli, Seite 595-606 (DE-627)745617794 (DE-600)2714518-9 2195-2698 nnns volume:7 year:2018 number:2 day:23 month:07 pages:595-606 https://dx.doi.org/10.1007/s40435-018-0462-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 7 2018 2 23 07 595-606 |
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Abtahi, Seid Farhad |
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Abtahi, Seid Farhad misc Robust control misc µ-Analysis misc Uncertain systems misc Coefficient diagram method misc Autopilot Robust control synthesis using coefficient diagram method and µ-analysis: an aerospace example |
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Robust control synthesis using coefficient diagram method and µ-analysis: an aerospace example Robust control (dpeaa)DE-He213 µ-Analysis (dpeaa)DE-He213 Uncertain systems (dpeaa)DE-He213 Coefficient diagram method (dpeaa)DE-He213 Autopilot (dpeaa)DE-He213 |
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Robust control synthesis using coefficient diagram method and µ-analysis: an aerospace example |
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Robust control synthesis using coefficient diagram method and µ-analysis: an aerospace example |
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Abtahi, Seid Farhad |
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International journal of dynamics and control |
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Abtahi, Seid Farhad Azadi Yazdi, Ehsan |
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Abtahi, Seid Farhad |
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robust control synthesis using coefficient diagram method and µ-analysis: an aerospace example |
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Robust control synthesis using coefficient diagram method and µ-analysis: an aerospace example |
| abstract |
Abstract This paper develops a structured controller synthesis method which satisfies robust stability and robust performance. In the proposed method (µ-CDM), coefficient diagram method (CDM) is employed to synthesize a structured controller and µ-analysis is used to evaluate the robustness of the controller. A supervisory particle swarm optimization utilizes the CDM and µ-analysis in an iterative manner in order to reach an optimal robustness bound. To evaluate the performance of the proposed method, it has been used to synthesize a robust autopilot for an aerospace system. Numerical simulations confirm the feasibility of µ-CDM and show the acceptable closed-loop performance in presence of various model uncertainties. The performance of the proposed controller is compared with that of a conventional CDM controller and a D–K iterations controller. © Springer-Verlag GmbH Germany, part of Springer Nature 2018 |
| abstractGer |
Abstract This paper develops a structured controller synthesis method which satisfies robust stability and robust performance. In the proposed method (µ-CDM), coefficient diagram method (CDM) is employed to synthesize a structured controller and µ-analysis is used to evaluate the robustness of the controller. A supervisory particle swarm optimization utilizes the CDM and µ-analysis in an iterative manner in order to reach an optimal robustness bound. To evaluate the performance of the proposed method, it has been used to synthesize a robust autopilot for an aerospace system. Numerical simulations confirm the feasibility of µ-CDM and show the acceptable closed-loop performance in presence of various model uncertainties. The performance of the proposed controller is compared with that of a conventional CDM controller and a D–K iterations controller. © Springer-Verlag GmbH Germany, part of Springer Nature 2018 |
| abstract_unstemmed |
Abstract This paper develops a structured controller synthesis method which satisfies robust stability and robust performance. In the proposed method (µ-CDM), coefficient diagram method (CDM) is employed to synthesize a structured controller and µ-analysis is used to evaluate the robustness of the controller. A supervisory particle swarm optimization utilizes the CDM and µ-analysis in an iterative manner in order to reach an optimal robustness bound. To evaluate the performance of the proposed method, it has been used to synthesize a robust autopilot for an aerospace system. Numerical simulations confirm the feasibility of µ-CDM and show the acceptable closed-loop performance in presence of various model uncertainties. The performance of the proposed controller is compared with that of a conventional CDM controller and a D–K iterations controller. © Springer-Verlag GmbH Germany, part of Springer Nature 2018 |
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Robust control synthesis using coefficient diagram method and µ-analysis: an aerospace example |
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https://dx.doi.org/10.1007/s40435-018-0462-7 |
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Azadi Yazdi, Ehsan |
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| doi_str |
10.1007/s40435-018-0462-7 |
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2024-07-03T17:50:44.055Z |
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In the proposed method (µ-CDM), coefficient diagram method (CDM) is employed to synthesize a structured controller and µ-analysis is used to evaluate the robustness of the controller. A supervisory particle swarm optimization utilizes the CDM and µ-analysis in an iterative manner in order to reach an optimal robustness bound. To evaluate the performance of the proposed method, it has been used to synthesize a robust autopilot for an aerospace system. Numerical simulations confirm the feasibility of µ-CDM and show the acceptable closed-loop performance in presence of various model uncertainties. 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