A Semi-Analytic Method for Solving a Class of Non-Linear Optimal Control Problems
Publish place: International Journal of Industrial Electronics, Control and Optimization، Vol: 3، Issue: 4
Publish Year: 1399
نوع سند: مقاله ژورنالی
زبان: English
View: 100
This Paper With 8 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_IECO-3-4_002
تاریخ نمایه سازی: 20 تیر 1401
Abstract:
This paper, proposes an approximate analytical method to solvea class of optimal control problems. This method is an enhancementof the variational iteration method (VIM) which is called modified variational iteration method (MVIM) and eliminates all additional calculations in VIM, thus requires less time to do the calculations. In thisapproach, first, the optimal control problem is converted into a non-linear two-point boundary value problem via the Pontryagins maximum principle, and then we applied the MVIM method to solve this boundary value problem. This suggested method is suitable for a large class of non-linear optimal control problems that for the non-linear part of the problem, we used the Taylor series expansion. In the end, three examples are provided to demonstrate the simplicity and efficiency of the method. The numerical results of the proposed method versus other methods are presented in tables. All calculations were carried out using Mathematica software.
Keywords:
Modified variational iteration method (MVIM) , Differential equations , Optimal control problems , Numerical solution
Authors
Maryam Alipour
Department of Mathematics, Faculty of Mathematics, University of Sistan and Baluchestan, Zahedan, Iran
Pooneh Omidiniya
Department of Mathematics, Statistics and Computer Science, University of Sistan and Baluchestan, Zahedan, Iran.
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :