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• W2428253961 abstract "In order to improve the vehicle steering stability, and avoid the obstacles fast and accurately, the fuzzy neural networks has been developed, in detail introduced this algorithm control principle. Advance control algorithm usually needs much more prior knowledge and depends on the accuracy model of process. However, fuzzy logic control technology is applied to control the plants having fuzzy, uncertainty, high-order, heavy lag without accurate mathematics model. The neural network has the advantage of self-learning, memory ability, fault-tolerant and parallel processing etc. The back propagation neural network was taken as framework, combining an improved fuzzy control algorithm, to realize the fuzzy-neural control of the exploration vehicle's navigation. It can use the improved fuzzy theory and neural networks together to form an improved fuzzy neural networks control system. So it can auto pick-up the fuzzy rule and build the subordinate function, it's self-organizing and self-learning the control knowledge which is needed for steering process and precise obstacle avoidance. The result of simulation analyses indicate that the method proposed in the paper can achieve safe and stability in steering control of obstacle avoidance of exploration vehicle." @default.
• W2428253961 created "2016-06-24" @default.
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• W2428253961 date "2009-03-01" @default.
• W2428253961 modified "2023-09-24" @default.
• W2428253961 title "The algorithm of obstacle avoidance based on improved fuzzy neural networks fusion for exploration vehicle" @default.
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