Open AccessReal‐time implementation of Chebyshev neural adaptive controller for boost converter
Author(s) -
Govindharaj Arunprasad,
Mariappan Anitha
Publication year - 2020
Publication title -
international transactions on electrical energy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.428
H-Index - 42
ISSN - 2050-7038
DOI - 10.1002/2050-7038.12394
Subject(s) - control theory (sociology) , backstepping , controller (irrigation) , pid controller , artificial neural network , lyapunov function , duty cycle , computer science , mathematics , adaptive control , voltage , control engineering , engineering , nonlinear system , temperature control , control (management) , electrical engineering , artificial intelligence , agronomy , biology , physics , machine learning , quantum mechanics
Summary An indirect approach is employed to track the desired output voltage of the boost converter by controlling the inductor current in the proposed adaptive backstepping Chebyshev neural network controller, because of the non‐minimum phase nature of the converter. The computational complexity of the neural network is avoided by the use of Chebyshev polynomials as the basis function. The online weight update of the Chebyshev neural network is designed for the closed‐loop system based on the Lyapunov stability analysis to obtain an asymptotically stable system. In the proposed work, the required duty cycle is obtained by a novel method of solving the quadratic equation of the control function instead of the first derivative of the duty cycle to get the desired output voltage from the Lyapunov control function. Detailed analyses of simulations are carried out for a wide range of variations in the set point and load, and the results are compared with that of backstepping and PID controllers. The proposed controller exhibits superior performance than other controllers for the uncertainties caused by disturbances. To ensure its suitability in real time, a prototype is designed for the proposed controller, and the obtained results are compared with that of backstepping and PID controllers. Investigation of experimental results confirms the adaptability of the proposed control scheme as it exhibits accurate and fast response irrespective of disturbances acting upon it.