Comparison of Controllers Using Mean Squared Error (MSE) Criteria for Helical Tracking in the Presence of Input Disturbances.
<p>Comparison of Controllers Using Mean Squared Error (MSE) Criteria for Helical Tracking in the Presence of Input Disturbances.</p>
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2025
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| _version_ | 1852017163734351872 |
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| author | Nigatu Wanore Madebo (22146141) |
| author_facet | Nigatu Wanore Madebo (22146141) |
| author_role | author |
| dc.creator.none.fl_str_mv | Nigatu Wanore Madebo (22146141) |
| dc.date.none.fl_str_mv | 2025-08-29T17:44:32Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0331036.t008 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/dataset/Comparison_of_Controllers_Using_Mean_Squared_Error_MSE_Criteria_for_Helical_Tracking_in_the_Presence_of_Input_Disturbances_/30013650 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Neuroscience Biotechnology Developmental Biology Infectious Diseases Biological Sciences not elsewhere classified Information Systems not elsewhere classified proposed approach leverages mean squared error layer neural network integrates neural networks combining neural networks applying neural networks >&# 981 ;</ >&# 968 ;</ >&# 952 ;</ 10 hidden neurons dimensional control challenges states using proportional fuzzy logic enhances div >< p derivative errors () adjust pid gains fuzzy logic pid controller input errors control strategy work demonstrates time adaptability remaining states paper presents ensure real |
| dc.title.none.fl_str_mv | Comparison of Controllers Using Mean Squared Error (MSE) Criteria for Helical Tracking in the Presence of Input Disturbances. |
| dc.type.none.fl_str_mv | Dataset info:eu-repo/semantics/publishedVersion dataset |
| description | <p>Comparison of Controllers Using Mean Squared Error (MSE) Criteria for Helical Tracking in the Presence of Input Disturbances.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_d46b7fd2a114fa4b3da4e9d6876d21be |
| identifier_str_mv | 10.1371/journal.pone.0331036.t008 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/30013650 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Comparison of Controllers Using Mean Squared Error (MSE) Criteria for Helical Tracking in the Presence of Input Disturbances.Nigatu Wanore Madebo (22146141)NeuroscienceBiotechnologyDevelopmental BiologyInfectious DiseasesBiological Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedproposed approach leveragesmean squared errorlayer neural networkintegrates neural networkscombining neural networksapplying neural networks>&# 981 ;</>&# 968 ;</>&# 952 ;</10 hidden neuronsdimensional control challengesstates using proportionalfuzzy logic enhancesdiv >< pderivative errors ()adjust pid gainsfuzzy logicpid controllerinput errorscontrol strategywork demonstratestime adaptabilityremaining statespaper presentsensure real<p>Comparison of Controllers Using Mean Squared Error (MSE) Criteria for Helical Tracking in the Presence of Input Disturbances.</p>2025-08-29T17:44:32ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pone.0331036.t008https://figshare.com/articles/dataset/Comparison_of_Controllers_Using_Mean_Squared_Error_MSE_Criteria_for_Helical_Tracking_in_the_Presence_of_Input_Disturbances_/30013650CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/300136502025-08-29T17:44:32Z |
| spellingShingle | Comparison of Controllers Using Mean Squared Error (MSE) Criteria for Helical Tracking in the Presence of Input Disturbances. Nigatu Wanore Madebo (22146141) Neuroscience Biotechnology Developmental Biology Infectious Diseases Biological Sciences not elsewhere classified Information Systems not elsewhere classified proposed approach leverages mean squared error layer neural network integrates neural networks combining neural networks applying neural networks >&# 981 ;</ >&# 968 ;</ >&# 952 ;</ 10 hidden neurons dimensional control challenges states using proportional fuzzy logic enhances div >< p derivative errors () adjust pid gains fuzzy logic pid controller input errors control strategy work demonstrates time adaptability remaining states paper presents ensure real |
| status_str | publishedVersion |
| title | Comparison of Controllers Using Mean Squared Error (MSE) Criteria for Helical Tracking in the Presence of Input Disturbances. |
| title_full | Comparison of Controllers Using Mean Squared Error (MSE) Criteria for Helical Tracking in the Presence of Input Disturbances. |
| title_fullStr | Comparison of Controllers Using Mean Squared Error (MSE) Criteria for Helical Tracking in the Presence of Input Disturbances. |
| title_full_unstemmed | Comparison of Controllers Using Mean Squared Error (MSE) Criteria for Helical Tracking in the Presence of Input Disturbances. |
| title_short | Comparison of Controllers Using Mean Squared Error (MSE) Criteria for Helical Tracking in the Presence of Input Disturbances. |
| title_sort | Comparison of Controllers Using Mean Squared Error (MSE) Criteria for Helical Tracking in the Presence of Input Disturbances. |
| topic | Neuroscience Biotechnology Developmental Biology Infectious Diseases Biological Sciences not elsewhere classified Information Systems not elsewhere classified proposed approach leverages mean squared error layer neural network integrates neural networks combining neural networks applying neural networks >&# 981 ;</ >&# 968 ;</ >&# 952 ;</ 10 hidden neurons dimensional control challenges states using proportional fuzzy logic enhances div >< p derivative errors () adjust pid gains fuzzy logic pid controller input errors control strategy work demonstrates time adaptability remaining states paper presents ensure real |