{"id":17832,"date":"2024-05-18T08:05:00","date_gmt":"2024-05-18T08:05:00","guid":{"rendered":"https:\/\/www.kmutt.ac.th\/sfa\/?post_type=sfa-article&#038;p=17832"},"modified":"2024-11-04T08:10:26","modified_gmt":"2024-11-04T08:10:26","slug":"a-revised-liu-story-conjugate-gradient-algorithm-for-solving-arm-robotic-manipulator-model","status":"publish","type":"sfa-article","link":"https:\/\/www.kmutt.ac.th\/sfa\/sfa-article\/a-revised-liu-story-conjugate-gradient-algorithm-for-solving-arm-robotic-manipulator-model\/","title":{"rendered":"A revised Liu-Story conjugate gradient algorithm for solving arm robotic manipulator model"},"content":{"rendered":"\n<p>\u0e19\u0e31\u0e01\u0e27\u0e34\u0e08\u0e31\u0e22\u0e28\u0e39\u0e19\u0e22\u0e4c\u0e04\u0e27\u0e32\u0e21\u0e40\u0e1b\u0e47\u0e19\u0e40\u0e25\u0e34\u0e28\u0e14\u0e49\u0e32\u0e19\u0e17\u0e24\u0e29\u0e0e\u0e35\u0e41\u0e25\u0e30\u0e27\u0e34\u0e17\u0e22\u0e32\u0e28\u0e32\u0e2a\u0e15\u0e23\u0e4c\u0e01\u0e32\u0e23\u0e04\u0e33\u0e19\u0e27\u0e13 (TaCS-CoE) \u0e44\u0e14\u0e49\u0e2a\u0e23\u0e49\u0e32\u0e07\u0e2d\u0e31\u0e25\u0e01\u0e2d\u0e23\u0e34\u0e17\u0e36\u0e21\u0e27\u0e34\u0e18\u0e35\u0e01\u0e32\u0e23 Conjugate Gradient (CG) \u0e0b\u0e36\u0e48\u0e07\u0e44\u0e14\u0e49\u0e23\u0e31\u0e1a\u0e01\u0e32\u0e23\u0e22\u0e01\u0e22\u0e48\u0e2d\u0e07\u0e2d\u0e22\u0e48\u0e32\u0e07\u0e2a\u0e39\u0e07\u0e43\u0e19\u0e01\u0e32\u0e23\u0e2b\u0e32\u0e04\u0e48\u0e32\u0e40\u0e2b\u0e21\u0e32\u0e30\u0e2a\u0e21\u0e17\u0e35\u0e48\u0e14\u0e35\u0e17\u0e35\u0e48\u0e2a\u0e38\u0e14 \u0e40\u0e19\u0e37\u0e48\u0e2d\u0e07\u0e08\u0e32\u0e01\u0e21\u0e35\u0e04\u0e38\u0e13\u0e2a\u0e21\u0e1a\u0e31\u0e15\u0e34\u0e17\u0e32\u0e07\u0e17\u0e24\u0e29\u0e0e\u0e35\u0e17\u0e35\u0e48\u0e19\u0e48\u0e32\u0e1e\u0e2d\u0e43\u0e08\u0e41\u0e25\u0e30\u0e04\u0e27\u0e32\u0e21\u0e2a\u0e32\u0e21\u0e32\u0e23\u0e16\u0e17\u0e35\u0e48\u0e21\u0e35\u0e1b\u0e23\u0e30\u0e2a\u0e34\u0e17\u0e18\u0e34\u0e20\u0e32\u0e1e\u0e43\u0e19\u0e01\u0e32\u0e23\u0e41\u0e01\u0e49\u0e1b\u0e31\u0e0d\u0e2b\u0e32\u0e17\u0e35\u0e48\u0e2b\u0e25\u0e32\u0e01\u0e2b\u0e25\u0e32\u0e22\u0e43\u0e19\u0e42\u0e25\u0e01\u0e41\u0e2b\u0e48\u0e07\u0e04\u0e27\u0e32\u0e21\u0e40\u0e1b\u0e47\u0e19\u0e08\u0e23\u0e34\u0e07 \u0e0b\u0e36\u0e48\u0e07\u0e23\u0e27\u0e21\u0e16\u0e36\u0e07\u0e01\u0e32\u0e23\u0e04\u0e27\u0e1a\u0e04\u0e38\u0e21\u0e01\u0e32\u0e23\u0e40\u0e04\u0e25\u0e37\u0e48\u0e2d\u0e19\u0e44\u0e2b\u0e27\u0e02\u0e2d\u0e07\u0e2b\u0e38\u0e48\u0e19\u0e22\u0e19\u0e15\u0e4c \u0e01\u0e32\u0e23\u0e40\u0e25\u0e37\u0e2d\u0e01\u0e1e\u0e2d\u0e23\u0e4c\u0e15\u0e42\u0e1f\u0e25\u0e34\u0e42\u0e2d \u0e01\u0e32\u0e23\u0e01\u0e39\u0e49\u0e04\u0e37\u0e19\u0e2a\u0e31\u0e0d\u0e0d\u0e32\u0e13 \u0e41\u0e25\u0e30\u0e01\u0e32\u0e23\u0e01\u0e39\u0e49\u0e04\u0e37\u0e19\u0e23\u0e39\u0e1b\u0e20\u0e32\u0e1e\u0e43\u0e19\u0e01\u0e32\u0e23\u0e27\u0e34\u0e08\u0e31\u0e22\u0e02\u0e2d\u0e07\u0e40\u0e23\u0e32 \u0e40\u0e23\u0e32\u0e44\u0e14\u0e49\u0e41\u0e19\u0e30\u0e19\u0e33\u0e2d\u0e31\u0e25\u0e01\u0e2d\u0e23\u0e34\u0e17\u0e36\u0e21 CG \u0e43\u0e2b\u0e21\u0e48\u0e2a\u0e2d\u0e07\u0e2d\u0e31\u0e25\u0e01\u0e2d\u0e23\u0e34\u0e17\u0e36\u0e21\u0e0a\u0e37\u0e48\u0e2d NSLS \u0e41\u0e25\u0e30 NSCD \u0e0b\u0e36\u0e48\u0e07\u0e44\u0e14\u0e49\u0e23\u0e31\u0e1a\u0e01\u0e32\u0e23\u0e1e\u0e34\u0e2a\u0e39\u0e08\u0e19\u0e4c\u0e41\u0e25\u0e49\u0e27\u0e27\u0e48\u0e32\u0e21\u0e35\u0e1b\u0e23\u0e30\u0e2a\u0e34\u0e17\u0e18\u0e34\u0e20\u0e32\u0e1e \u0e41\u0e02\u0e47\u0e07\u0e41\u0e01\u0e23\u0e48\u0e07 \u0e41\u0e25\u0e30\u0e15\u0e23\u0e07\u0e44\u0e1b\u0e15\u0e23\u0e07\u0e21\u0e32\u0e43\u0e19\u0e01\u0e32\u0e23\u0e19\u0e33\u0e44\u0e1b\u0e43\u0e0a\u0e49<\/p>\n\n\n\n<p>\u2705\u25b6\ufe0fResearchers at the Center of Excellence for Theory and Computational Science (TaCS-CoE) have created a highly acclaimed Conjugate Gradient (CG) algorithm for finding the best optimal solution. Conjugate Gradient (CG) methods are renowned for their efficiency and low memory requirements when solving optimization problems. However, certain formulations of CG methods that switch between two or more CG parameters often overlook specific values that could have been integrated. Moreover, the demonstration of the sufficient descent property in these methods usually relies on a strategy that assumes the possible exclusion of certain function values. To alleviate this assumption, this article introduces a structured Liu\u2013Storey spectral CG method. This method extends the formulation of the spectral Fletcher conjugate descent method, enabling it to maintain fast convergence and inherit a good restart property. Therefore, the method ensures sufficient descent property holds without additional requirements and converges globally via some standard assumptions. Additionally, the method proves useful in solving robotic and image reconstruction models. Finally, it demonstrates robustness when compared to some standard algorithms.<\/p>\n\n\n\n<p>\ud835\uddd9\ud835\udde8\ud835\udde7\ud835\udde8\ud835\udde5\ud835\uddd8 \ud835\uddd9\ud835\udde2\ud835\udde5\ud835\uddea\ud835\uddd4\ud835\udde5\ud835\uddd7 \u276f\u276f<br>Exploring KMUTT Research That Shapes Tomorrow<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"576\" height=\"1024\" src=\"https:\/\/www.kmutt.ac.th\/sfa\/wp-content\/uploads\/sites\/8\/2024\/11\/Nasiru-Poom_A-revised-Liu-etc-576x1024.jpg\" alt=\"\" class=\"wp-image-17833\" srcset=\"https:\/\/www.kmutt.ac.th\/sfa\/wp-content\/uploads\/sites\/8\/2024\/11\/Nasiru-Poom_A-revised-Liu-etc-576x1024.jpg 576w, https:\/\/www.kmutt.ac.th\/sfa\/wp-content\/uploads\/sites\/8\/2024\/11\/Nasiru-Poom_A-revised-Liu-etc-169x300.jpg 169w, https:\/\/www.kmutt.ac.th\/sfa\/wp-content\/uploads\/sites\/8\/2024\/11\/Nasiru-Poom_A-revised-Liu-etc-768x1365.jpg 768w, https:\/\/www.kmutt.ac.th\/sfa\/wp-content\/uploads\/sites\/8\/2024\/11\/Nasiru-Poom_A-revised-Liu-etc-864x1536.jpg 864w, https:\/\/www.kmutt.ac.th\/sfa\/wp-content\/uploads\/sites\/8\/2024\/11\/Nasiru-Poom_A-revised-Liu-etc.jpg 1152w\" sizes=\"(max-width: 576px) 100vw, 576px\" \/><\/figure>\n","protected":false},"featured_media":17836,"template":"","categories":[6],"sfa_article":[49],"pp_force_visibility":null,"pp_subpost_visibility":null,"pp_inherited_force_visibility":null,"pp_inherited_subpost_visibility":null,"acf":[],"_links":{"self":[{"href":"https:\/\/www.kmutt.ac.th\/sfa\/wp-json\/wp\/v2\/sfa-article\/17832"}],"collection":[{"href":"https:\/\/www.kmutt.ac.th\/sfa\/wp-json\/wp\/v2\/sfa-article"}],"about":[{"href":"https:\/\/www.kmutt.ac.th\/sfa\/wp-json\/wp\/v2\/types\/sfa-article"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.kmutt.ac.th\/sfa\/wp-json\/wp\/v2\/media\/17836"}],"wp:attachment":[{"href":"https:\/\/www.kmutt.ac.th\/sfa\/wp-json\/wp\/v2\/media?parent=17832"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.kmutt.ac.th\/sfa\/wp-json\/wp\/v2\/categories?post=17832"},{"taxonomy":"sfa_article","embeddable":true,"href":"https:\/\/www.kmutt.ac.th\/sfa\/wp-json\/wp\/v2\/sfa_article?post=17832"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}