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Erschienen in:
01.10.2009 | Original Article
Fuzzy truck control scheme for obstacle avoidance
Erschienen in: Neural Computing and Applications | Ausgabe 7/2009
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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.