Intelligent control strategy for a heavy vehicle compaction system DYNAPAC CC6200 Online publication date: Fri, 18-Nov-2022
by Hocine Chebi
International Journal of Heavy Vehicle Systems (IJHVS), Vol. 29, No. 3, 2022
Abstract: This paper proposes a GA-LOS-PI controller-based four-level control system that accurately evaluates pavement compaction effect of DYNAPAC CC6200 autonomous articulated vehicle (AAV). In the evaluation layer, various performance indicators are evaluated, including stability, rapidity and accuracy when trajectory tracking, and the ratio of required compaction to actual compaction once and twice and compaction repeatability index when pavement compacting. In the decision and control layer, incremental PI controller is used as the main control strategy, line of sight (LOS) guidance is introduced to eliminate system control lag, and genetic algorithm (GA) is used for searching the best proportional. The comparative simulation results of no controller, the traditional incremental PI controller, LOS-PI controller with human driving experience initial control parameters (HDEICP), GA-LOS-PI controller with random initial control parameters (RICP) and GA-LOS-PI controller with HDEICP manifest evidently that the proposed GA-LOS-PI controller with HDEICP has almost no steady-state error.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Heavy Vehicle Systems (IJHVS):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook