Research on Road Simulator with Iterative Learning Control

2009-01-2908

10/06/2009

Event
SAE 2009 Commercial Vehicle Engineering Congress & Exhibition
Authors Abstract
Content
Road simulation experiment in laboratory is a most important method to enhance the design quality of vehicle products. Presently, two main control techniques for road simulation—remote parameter control (RPC) and minimum variance adaptive control—are both defective: the former becomes an open-loop control after generating the drive signals, however the latter is essentially a kind of gradual control. To realize the closed-loop control and increase the control quality, this article brings forward a PID open-closed loop control method. Firstly taking the original road simulator as a group to identify, a nonlinear autoregressive moving average (NARMA) model was built with the dynamic neural network. Subsequently, this plant model was used to build the open-closed loop control system mentioned above. In the closed-loop a discrete PID controller was introduced to stabilize the system, while a P-type iterative learning control (ILC) was adopted to increase the control quality. Simulation results show that by using open-closed loop ILC, system convergence rate is fast, so this method can be applied to physical system.
Meta TagsDetails
DOI
https://doi.org/10.4271/2009-01-2908
Pages
6
Citation
Wang, B., Guo, X., Xu, Z., Tan, G. et al., "Research on Road Simulator with Iterative Learning Control," SAE Technical Paper 2009-01-2908, 2009, https://doi.org/10.4271/2009-01-2908.
Additional Details
Publisher
Published
Oct 6, 2009
Product Code
2009-01-2908
Content Type
Technical Paper
Language
English