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One method for the nonholonomic system controller design is the time-state control form that utilizes a chained form conversion. The chained forms are powerful and useful for designing the nonholonomic control system. However, the time-state control form has some limitations in the controllable ranges due to the conversion. In this research, we propose a design method of a state feedback controller for a nonholonomic system using an NC without chained forms. The NC is trained by a genetic algorithm. In the controller design, the abilities of pattern recognition and generalization of the neural network are utilized. In the GA process, NCs are evaluated on the basis of control performance in which the squared errors that result from the control simulations starting from all the initial states are calculated. Based on the control performance, NCs are evolved through the GA processes. Results of simulations show that the NCs trained using a GA exhibit good control performance of some example objects of the nonholonomic systems. One of the control strategies of the NC resembles that of time-state control form. The proposed method has no limitations in the controllable ranges in the initial states.", "subitem_description_type": "Other"}, {"subitem_description": "\u975e\u516c\u958b\uff1aP.1\u4ee5\u964d\uff08\u5225\u5237\u8ad6\u6587\u306e\u305f\u3081\uff09", "subitem_description_type": "Other"}, {"subitem_description": "\u7814\u7a76\u5831\u544a\u66f8", "subitem_description_type": "Other"}]}, "item_1617186643794": {"attribute_name": "Publisher", "attribute_value_mlt": [{"subitem_1522300295150": "ja", "subitem_1522300316516": "\u91d1\u57ce\u5bdb"}]}, "item_1617186702042": {"attribute_name": "Language", "attribute_value_mlt": [{"subitem_1551255818386": "jpn"}]}, "item_1617186783814": {"attribute_name": "Identifier", "attribute_value_mlt": [{"subitem_identifier_type": "HDL", "subitem_identifier_uri": "http://hdl.handle.net/20.500.12000/11408"}]}, "item_1617186920753": {"attribute_name": "Source Identifier", "attribute_value_mlt": [{"subitem_1522646500366": "NCID", "subitem_1522646572813": "BA79368173"}]}, "item_1617258105262": {"attribute_name": "Resource Type", "attribute_value_mlt": [{"resourcetype": "research report", "resourceuri": "http://purl.org/coar/resource_type/c_18ws"}]}, "item_1617265215918": {"attribute_name": "Version Type", "attribute_value_mlt": [{"subitem_1522305645492": "VoR", "subitem_1600292170262": "http://purl.org/coar/version/c_970fb48d4fbd8a85"}]}, "item_1617605131499": {"attribute_name": "File", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "download_preview_message": "", "file_order": 0, "filename": "16500114.pdf", "future_date_message": "", "is_thumbnail": false, "mimetype": "", "size": 0, "url": {"objectType": "fulltext", "url": "https://u-ryukyu.repo.nii.ac.jp/record/2004734/files/16500114.pdf"}, "version_id": "a645fbe9-4222-4fca-a9ee-4b50e6b2b510"}]}, "item_title": "GA\u5b66\u7fd2\u6cd5\u3092\u7528\u3044\u305f\u30cb\u30e5\u30fc\u30ed\u5236\u5fa1\u5668\u306b\u3088\u308b\u975e\u30db\u30ed\u30ce\u30df\u30c3\u30af\u7cfb\u306e\u5236\u5fa1\u7cfb\u8a2d\u8a08\u6cd5", "item_type_id": "15", "owner": "1", "path": ["1642838403123", "1642838406845"], "permalink_uri": "http://hdl.handle.net/20.500.12000/11408", "pubdate": {"attribute_name": "PubDate", "attribute_value": "2009-07-23"}, "publish_date": "2009-07-23", "publish_status": "0", "recid": "2004734", "relation": {}, "relation_version_is_last": true, "title": ["GA\u5b66\u7fd2\u6cd5\u3092\u7528\u3044\u305f\u30cb\u30e5\u30fc\u30ed\u5236\u5fa1\u5668\u306b\u3088\u308b\u975e\u30db\u30ed\u30ce\u30df\u30c3\u30af\u7cfb\u306e\u5236\u5fa1\u7cfb\u8a2d\u8a08\u6cd5"], "weko_shared_id": -1}
GA学習法を用いたニューロ制御器による非ホロノミック系の制御系設計法
http://hdl.handle.net/20.500.12000/11408
http://hdl.handle.net/20.500.12000/11408