A new adaptive deep neural network controller based on sparse auto‐encoder for the antilock bracking system systems subject to high constraints

• Published in: Asian journal of control Vol. 23; no. 5; pp. 2145 - 2156
• Main Author: Ait Abbas, Hamou
• Format: Journal Article
• Language: English
• Published: Hoboken Wiley Subscription Services, Inc 01.09.2021
• Subjects: Adaptive algorithms; Adaptive control; adaptive DNN observer & controller; Antilock braking systems; Artificial neural networks; Coders; Compensators; Control algorithms; Control systems design; Control theory; Controllers; Deep learning; deep learning hybrid strategy; deep neural network; Error signals; Feasibility; Feedback control; Machine learning; Neural networks; Output feedback; Parameter uncertainty; parametric uncertainty; robustness test; Tracking errors; unmodeled dynamics

We contribute in the current paper to extend the universal function approximation property of deep learning hybrid strategy to design both : (a) adaptive deep neural network observer to estimate derivatives of the tracking error dynamics (b) and robust deep neural network (DNN) output feedback contr...