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Improved Neural Network and the Pontryagin's minimum Principle for Solve Fuzzy Optimal Control Problems | ||
International Journal of Industrial Mathematics | ||
دوره 12، شماره 3، مرداد 2020، صفحه 303-314 اصل مقاله (471.62 K) | ||
نوع مقاله: Research Paper | ||
نویسندگان | ||
S. Askari 1؛ S. Abbasbandy 2 | ||
1Department of Mathematics, Science and Research Branch, Islamic Azad University, Hamedan, Iran | ||
2Department of Applied Mathematics, Faculty of Science, Imam Khomeini International University, Qazvin, Iran. | ||
چکیده | ||
In this paper, a novel and practical approach are proposed to solve the fuzzy optimal control (FOC) using an improved multi-layer perceptron (IMLP) network along with the Pontryagin minimum principle (PMP). Here, it is worthwhile to mention that in the fuzzy Hamilton function, instead of functions of control and trajectory and the Lagrange multipliers, the approximate solutions are replaced based on the IMLP neural network, which is a Three-layer type. | ||
کلیدواژهها | ||
FOC problem؛ Pontryagin minimum principle؛ IMLP networks؛ BFGs method. | ||
آمار تعداد مشاهده مقاله: 201 تعداد دریافت فایل اصل مقاله: 238 |