Adaptive path following control for tracked vehicles based on genetic algorithm

作者：Zhang Baojun; Zhu Hualin; Luo Jun^*; Xie Shaorong; Li Hengyu

来源：ICIC Express Letters, Part B: Applications , 2013, 4(3): 815-823.

• Adaptive control algorithms
• Complex environments
• Control structure
• Curve fitting methods
• Following control
• Obstacle crossings
• Path following control
• Stable locomotion

Tracked vehicles have the advantage of mighty obstacle crossing ability and stable locomotion on uneven terrain. As a result, such mechanisms are widely used for locomotion in complex environments. Among the research of tracked vehicles, path tracking takes a very important role in the vehicle research. However, most previous research over following controls just limits to some simple paths, such as circle and straight line. In this paper, a control scheme involving complicated curve following is proposed in order to adapt to more intricate environment. Within the control structure, a novel method named curve fitting method (CFM) is issued to match the targeted route. A multi-parameter adaptive control algorithm (MPACA) is further constructed based on genetic algorithm. This intends to automatically adjust the parameters according to the changing route, which is used for the definition of vehicle's speed. Simulations conducted on genetic algorithm, tested on a sophisticated route, demonstrate the performance both of CFM and MPACA.

• 出版日期2013