Parameter Identification of Motors by Cuckoo Search Using Steady-State Relations
The direct current (DC) motors are widely used; therefore, they are subject to multiple studies, different control techniques or analyses require a dynamic DC motor model. The parameters are needed to complete the model, which can be challenging to obtain. Therefore, multiple parametric estimation t...
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| creator | Rodriguez-Abreo, Omar Hernandez-Paredes, Jose Miguel Rangel, Alejandro Flores Fuentes-Silva, Carlos Velasquez, Francisco Antonio Castillo |
| description | The direct current (DC) motors are widely used; therefore, they are subject to multiple studies, different control techniques or analyses require a dynamic DC motor model. The parameters are needed to complete the model, which can be challenging to obtain. Therefore, multiple parametric estimation techniques have been developed. This paper presents a metaheuristic cuckoo search algorithm modified for motors as a parametric estimation tool. A cost function is based on the current and velocity error obtained when an input voltage step is applied to the motor. The main difference with similar works is that we used the steady-state equations to determine the parameters. The algorithm proposed is compared with the Steiglitz-McBride and the original cuckoo search algorithms to evaluate its performance objectively. Simulated and experimental results show that the algorithm proposed can calculate the parameters with better accuracy than the original cuckoo search and Steiglitz-McBride. The modifications made to the original algorithm of the cuckoo search allowed finding the values of the parameters motor with a root mean square error of less than 0.1% for signals obtained with simulation and less than 1% for real signals sampled at 0.001 s. |
| doi_str_mv | 10.1109/ACCESS.2021.3078578 |
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The parameters are needed to complete the model, which can be challenging to obtain. Therefore, multiple parametric estimation techniques have been developed. This paper presents a metaheuristic cuckoo search algorithm modified for motors as a parametric estimation tool. A cost function is based on the current and velocity error obtained when an input voltage step is applied to the motor. The main difference with similar works is that we used the steady-state equations to determine the parameters. The algorithm proposed is compared with the Steiglitz-McBride and the original cuckoo search algorithms to evaluate its performance objectively. Simulated and experimental results show that the algorithm proposed can calculate the parameters with better accuracy than the original cuckoo search and Steiglitz-McBride. The modifications made to the original algorithm of the cuckoo search allowed finding the values of the parameters motor with a root mean square error of less than 0.1% for signals obtained with simulation and less than 1% for real signals sampled at 0.001 s.</description><identifier>ISSN: 2169-3536</identifier><identifier>EISSN: 2169-3536</identifier><identifier>DOI: 10.1109/ACCESS.2021.3078578</identifier><identifier>CODEN: IAECCG</identifier><language>eng</language><publisher>PISCATAWAY: IEEE</publisher><subject>Algorithms ; Brushless DC motors ; Computer Science ; Computer Science, Information Systems ; Cost function ; Cuckoo search ; D C motors ; DC motor ; Electric motors ; Engineering ; Engineering, Electrical & Electronic ; Equations of state ; Heuristic algorithms ; Heuristic methods ; Induction motors ; Mathematical model ; Mathematical models ; metaheuristic ; Parameter estimation ; Parameter identification ; Permanent magnet motors ; Reluctance motors ; Science & Technology ; Search algorithms ; Steady state ; Steiglitz-McBride algorithm ; Technology ; Telecommunications ; Velocity errors</subject><ispartof>IEEE access, 2021, Vol.9, p.72017-72024</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>true</woscitedreferencessubscribed><woscitedreferencescount>12</woscitedreferencescount><woscitedreferencesoriginalsourcerecordid>wos000652516200001</woscitedreferencesoriginalsourcerecordid><citedby>FETCH-LOGICAL-c408t-49bf694753df58cc80076d0f6346dc39dfd34347af4e22adec1c528c0cff50053</citedby><cites>FETCH-LOGICAL-c408t-49bf694753df58cc80076d0f6346dc39dfd34347af4e22adec1c528c0cff50053</cites><orcidid>0000-0002-9476-4129 ; 0000-0002-8650-1185</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9427132$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>315,781,785,865,2103,2115,4025,27637,27927,27928,27929,39262,54937</link.rule.ids></links><search><creatorcontrib>Rodriguez-Abreo, Omar</creatorcontrib><creatorcontrib>Hernandez-Paredes, Jose Miguel</creatorcontrib><creatorcontrib>Rangel, Alejandro Flores</creatorcontrib><creatorcontrib>Fuentes-Silva, Carlos</creatorcontrib><creatorcontrib>Velasquez, Francisco Antonio Castillo</creatorcontrib><title>Parameter Identification of Motors by Cuckoo Search Using Steady-State Relations</title><title>IEEE access</title><addtitle>Access</addtitle><addtitle>IEEE ACCESS</addtitle><description>The direct current (DC) motors are widely used; therefore, they are subject to multiple studies, different control techniques or analyses require a dynamic DC motor model. The parameters are needed to complete the model, which can be challenging to obtain. Therefore, multiple parametric estimation techniques have been developed. This paper presents a metaheuristic cuckoo search algorithm modified for motors as a parametric estimation tool. A cost function is based on the current and velocity error obtained when an input voltage step is applied to the motor. The main difference with similar works is that we used the steady-state equations to determine the parameters. The algorithm proposed is compared with the Steiglitz-McBride and the original cuckoo search algorithms to evaluate its performance objectively. Simulated and experimental results show that the algorithm proposed can calculate the parameters with better accuracy than the original cuckoo search and Steiglitz-McBride. The modifications made to the original algorithm of the cuckoo search allowed finding the values of the parameters motor with a root mean square error of less than 0.1% for signals obtained with simulation and less than 1% for real signals sampled at 0.001 s.</description><subject>Algorithms</subject><subject>Brushless DC motors</subject><subject>Computer Science</subject><subject>Computer Science, Information Systems</subject><subject>Cost function</subject><subject>Cuckoo search</subject><subject>D C motors</subject><subject>DC motor</subject><subject>Electric motors</subject><subject>Engineering</subject><subject>Engineering, Electrical & Electronic</subject><subject>Equations of state</subject><subject>Heuristic algorithms</subject><subject>Heuristic methods</subject><subject>Induction motors</subject><subject>Mathematical model</subject><subject>Mathematical models</subject><subject>metaheuristic</subject><subject>Parameter estimation</subject><subject>Parameter identification</subject><subject>Permanent magnet motors</subject><subject>Reluctance motors</subject><subject>Science & Technology</subject><subject>Search algorithms</subject><subject>Steady state</subject><subject>Steiglitz-McBride algorithm</subject><subject>Technology</subject><subject>Telecommunications</subject><subject>Velocity errors</subject><issn>2169-3536</issn><issn>2169-3536</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><sourceid>HGBXW</sourceid><sourceid>DOA</sourceid><recordid>eNqNkV1rFDEUhgdRsNT-gt4EvJRZ853JZRmqLlQsjr0O2eSkZt1OapKl7L83u1Oql-Ym4fA-5xzydN0lwStCsP54NY7X07SimJIVw2oQanjVnVEidc8Ek6__eb_tLkrZ4naGVhLqrLu9tdk-QIWM1h7mGkN0tsY0oxTQ11RTLmhzQOPe_UoJTWCz-4nuSpzv0VTB-kM_VVsBfYfdCSvvujfB7gpcPN_n3d2n6x_jl_7m2-f1eHXTO46H2nO9CVJzJZgPYnBuwFhJj4NkXHrHtA-eccaVDRwotR4ccYIODrsQBMaCnXfrpa9Pdmsec3yw-WCSjeZUSPne2Fyj24ERmBFvBQgCllshNMEKOGirFNd-Y1uv90uvx5x-76FUs037PLf1DW1DNReD1C3FlpTLqZQM4WUqweZowiwmzNGEeTbRqGGhnmCTQnERZgcvZDMhBRVE0qMUMsZ6-sUx7efa0A__j7b05ZKOAH9TmlNFGGV_AI0OpHY</recordid><startdate>2021</startdate><enddate>2021</enddate><creator>Rodriguez-Abreo, Omar</creator><creator>Hernandez-Paredes, Jose Miguel</creator><creator>Rangel, Alejandro Flores</creator><creator>Fuentes-Silva, Carlos</creator><creator>Velasquez, Francisco Antonio Castillo</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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The parameters are needed to complete the model, which can be challenging to obtain. Therefore, multiple parametric estimation techniques have been developed. This paper presents a metaheuristic cuckoo search algorithm modified for motors as a parametric estimation tool. A cost function is based on the current and velocity error obtained when an input voltage step is applied to the motor. The main difference with similar works is that we used the steady-state equations to determine the parameters. The algorithm proposed is compared with the Steiglitz-McBride and the original cuckoo search algorithms to evaluate its performance objectively. Simulated and experimental results show that the algorithm proposed can calculate the parameters with better accuracy than the original cuckoo search and Steiglitz-McBride. The modifications made to the original algorithm of the cuckoo search allowed finding the values of the parameters motor with a root mean square error of less than 0.1% for signals obtained with simulation and less than 1% for real signals sampled at 0.001 s.</abstract><cop>PISCATAWAY</cop><pub>IEEE</pub><doi>10.1109/ACCESS.2021.3078578</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-9476-4129</orcidid><orcidid>https://orcid.org/0000-0002-8650-1185</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Algorithms Brushless DC motors Computer Science Computer Science, Information Systems Cost function Cuckoo search D C motors DC motor Electric motors Engineering Engineering, Electrical & Electronic Equations of state Heuristic algorithms Heuristic methods Induction motors Mathematical model Mathematical models metaheuristic Parameter estimation Parameter identification Permanent magnet motors Reluctance motors Science & Technology Search algorithms Steady state Steiglitz-McBride algorithm Technology Telecommunications Velocity errors |
| title | Parameter Identification of Motors by Cuckoo Search Using Steady-State Relations |
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