We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Adaptive sliding neural network-based vibration control of a nonlinear quarter car active suspension system with unknown dynamics.
- Authors
Ghahremani, Azadeh; Khaloozadeh, Hamid; Ghahremani, Peyman
- Abstract
This study investigates adaptive sliding neural network (NN) control for quarter active suspension system with dynamic uncertainties and road disturbances. A Multilayer Perceptron (MLP) neural network is adopted to estimate the unknown dynamics of the system. In addition, sliding mode controller is introduced to compensate the function of estimation error for improving the performance of the system. Furthermore, the uniformly and bounded of closed-loop signals is guaranteed by Lyapunov analysis; the adaptation laws for training of MLP are derived from stability analysis. The simulation results demonstrate that the proposed controller can effectively provide a good ride and makes great trade-off between passenger comfort and handling despite the dynamic uncertainties.
- Subjects
NEURAL computers; NONLINEAR systems; SUSPENSIONS (Chemistry); MULTILAYER perceptrons; CLOSED loop systems; LYAPUNOV functions
- Publication
Vibroengineering Procedia, 2018, Vol 17, p67
- ISSN
2345-0533
- Publication type
Article
- DOI
10.21595/vp.2018.19871