- Tytuł:
- Neural network based feedback linearization control of a servo-hydraulic vehicle suspension system
- Autorzy:
-
Pedro, J. O.
Dahunsi, O. A. - Powiązania:
- https://bibliotekanauki.pl/articles/907825.pdf
- Data publikacji:
- 2011
- Wydawca:
- Uniwersytet Zielonogórski. Oficyna Wydawnicza
- Tematy:
-
sieć neuronowa
sterowanie bezpośrednie
sterowanie ze sprzężeniem zwrotnym
regulacja PID
komfort jazdy
układ zawieszenia
neural networks
direct adaptive control
feedback linearization control
PID control
ride comfort
suspension system
servo-hydraulics - Opis:
- This paper presents the design of a neural network based feedback linearization (NNFBL) controller for a two degree-offreedom (DOF), quarter-car, servo-hydraulic vehicle suspension system. The main objective of the direct adaptive NNFBL controller is to improve the system's ride comfort and handling quality. A feedforward, multi-layer perceptron (MLP) neural network (NN) model that is well suited for control by discrete input-output linearization (NNIOL) is developed using input-output data sets obtained from mathematical model simulation. The NN model is trained using the Levenberg- Marquardt optimization algorithm. The proposed controller is compared with a constant-gain PID controller (based on the Ziegler-Nichols tuning method) during suspension travel setpoint tracking in the presence of deterministic road disturbance. Simulation results demonstrate the superior performance of the proposed direct adaptive NNFBL controller over the generic PID controller in rejecting the deterministic road disturbance. This superior performance is achieved at a much lower control cost within the stipulated constraints.
- Źródło:
-
International Journal of Applied Mathematics and Computer Science; 2011, 21, 1; 137-147
1641-876X
2083-8492 - Pojawia się w:
- International Journal of Applied Mathematics and Computer Science
- Dostawca treści:
- Biblioteka Nauki
Artykuł