TY - JOUR
ID - 3153
TI - A Neural Network Method Based on Mittag-Leffler Function for Solving a Class of Fractional Optimal Control Problems
JO - AUT Journal of Modeling and Simulation
JA - MISCJ
LA - en
SN - 2588-2953
AU - Ghasemi, S.
AU - Nazemi, A.R.
AD - Faculty of Mathematical Sciences, Shahrood University of Technology, Shahrood, Iran
Y1 - 2018
PY - 2018
VL - 50
IS - 2
SP - 211
EP - 218
KW - Ponteryagin minimum principle
KW - fractional optimal control problem
KW - artificial neural network
KW - equality and inequality constraint
KW - optimization
DO - 10.22060/miscj.2018.14448.5106
N2 - In this paper, a computational intelligence method is used for solution of fractional optimal control problems (FOCPs) with equality and inequality constraints. According to the Ponteryagin minimum principle (PMP) for FOCP with fractional derivative in the Riemann- Liouville sense and by constructing a suitable error function, we define an unconstrained minimization problem. In the optimization problem, we use trial solutions for the states, Lagrange multipliers and control functions where these trial solutions are constructed by a feed-forward neural network model. We then minimize the error function using a numerical optimization scheme where weight parameters and biases associated with all neurons are unknown. Examples are included to demonstrate the validity and capability of the proposed method. The strength of the proposed method is its equal applicability for the integer-order case as well as fractional order case. Another advantage of the presented approach is to provide results on entire finite continuous domain unlike some other numerical methods which provide solutions only on discrete grid of point.
UR - https://miscj.aut.ac.ir/article_3153.html
L1 - https://miscj.aut.ac.ir/article_3153_75d18d1f2ccea162cd23632681745a5e.pdf
ER -