Name
Abstract | ||
|---|---|---|
The fuzzy system can be a good solution when a mathematical model of the system is either unavailable or too complex. Truck
backer-upper control problem is one example of a standard highly nonlinear control problem. Bearing this in mind the control
scheme that considers obstacles near the truck is much more complex than other conventional approaches. In this paper a fuzzy
truck control system for obstacle avoidance, using newly designed 33 fuzzy inference rules for steering control and 13 rules
for speed control, is proposed. Through simulations of various real world situations, we observed that the proposed fuzzy
controller could drive the truck to the goal smoothly while avoiding the obstacles, and showed a reasonably good trajectory.
This flexible and applicable fuzzy control logic can be adapted to provide easy interaction with the driver for state-of-the-art
intelligent cruise control systems. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/s00521-008-0209-z | Neural Computing and Applications |
Keywords | DocType | Volume |
fuzzy truckfuzzy control � obstacle avoidancetruck backer-upper | Journal | 18 |
Issue | ISSN | Citations |
7 | 1433-3058 | 5 |
PageRank | References | Authors |
0.50 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Do-hyeon Kim | 1 | 5 | 0.50 |
| kwangbaek kim | 2 | 110 | 43.94 |
| Eui-Young Cha | 3 | 49 | 11.24 |