Nonlinear Dynamics

, Volume 73, Issue 3, pp 1443–1454 | Cite as

Design of neural network-based control systems for active steering system

Original Paper


Nowadays, safety of road vehicles is an important issue due to the increasing road vehicle accidents. Passive safety system of the passenger vehicle is to minimize the damage to the driver and passenger of a road vehicle during an accident. Whereas an active steering system is to improve the response of the vehicle to the driver inputs even in adverse situations and thus avoid accidents. This paper presents a neural network-based robust control system design for the active steering system. Primarily, double-pinion steering system used modeling of the active steering system. Then four control structures are used to control prescribed random trajectories of the active steering system. These control structures are as classical PID Controller, Model-Based Neural Network Controller, Neural Network Predictive Controller and Robust Neural Network Predictive Control System. The results of the simulation showed that the proposed neural network-based robust control system had superior performance in adapting to large random disturbances.


Active steering system Artificial neural network Robust control Random road input signal 


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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Faculty of Engineering, Mechatronics Engineering DepartmentErciyes UniversityKayseriTurkey
  2. 2.Faculty of Information Technologies and EngineeringAhmet Yesevi UniversityTurkestan cityKazakhstan

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