scholarly journals Region-of-convergence estimation for learning-based adaptive controllers

Author(s):  
John F. Quindlen ◽  
Ufuk Topcu ◽  
Girish Chowdhary ◽  
Jonathan P. How
2015 ◽  
Vol 10 (3) ◽  
pp. 2825-2833
Author(s):  
Achala Nargund ◽  
R Madhusudhan ◽  
S B Sathyanarayana

In this paper, Homotopy analysis method is applied to the nonlinear coupleddifferential equations of classical Boussinesq system. We have applied Homotopy analysis method (HAM) for the application problems in [1, 2, 3, 4]. We have also plotted Domb-Sykes plot for the region of convergence. We have applied Pade for the HAM series to identify the singularity and reflect it in the graph. The HAM is a analytical technique which is used to solve non-linear problems to generate a convergent series. HAM gives complete freedom to choose the initial approximation of the solution, it is the auxiliary parameter h which gives us a convenient way to guarantee the convergence of homotopy series solution. It seems that moreartificial degrees of freedom implies larger possibility to gain better approximations by HAM.


Author(s):  
Walid Hatahet ◽  
Mostafa I. Marei ◽  
Mohamed Mokhtar

2021 ◽  
Vol 12 (1) ◽  
pp. 44
Author(s):  
Gururaj Banda ◽  
Sri Gowri Kolli

This article deals with an intelligent adaptive neural network (ANN) controller for a direct torque controlled (DTC) electric vehicle (EV) propulsion system. With the realization of artificial intelligence (AI) conferred adaptive controllers, the torque control of an electric car (eCAR) propulsion motor can be achieved by estimating the stator reference flux voltage used to synthesize the space vector pulse width modulation (SVPWM) for a DTC scheme. The proposed ANN tool optimizes the parameters of a proportional integral (PI) controller with real-time data and offers splendid dynamic stability. The response of an ANN controller is examined over standard drive cycles to validate the performance of an eCAR in terms of drive range and energy efficiency using MATLAB simulation software.


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