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AGV steering model based on visual and control

Author: AiQing
Tutor: ZhanYueDong
School: Kunming University of Science and Technology
Course: Control Theory and Control Engineering
Keywords: AGV Kinesthetic schemata Simulated intelligent control Fuzzy Control Neural Network Control
CLC: TP273.5
Type: Master's thesis
Year: 2009
Downloads: 92
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Abstract

With the development of factory automation and computer integrated manufacturing systems, flexible manufacturing systems and the wide application of the automated warehouse, automatic guided vehicles (Automatic Guided Vehicle, ie AGV) as a means of connection and adjust the discrete logistics system has become automated transportation and handling the necessary tools, its scope of application and technical level has been rapid development. In the areas of research in the AGV path tracking steering control technology is a key technology in the AGV study. Thus, how to design a tracking error is small, fast dynamic response, can adapt to a variety of complex environments, and has better robustness steering control system is very important. On the basis of the main work of this paper first access to a large number of domestic and foreign research data, summarized at home and abroad the AGV and their turning movement control technology development history and the status quo. Second, understanding of the main structure and working principle of the automatic guided vehicles (V-AGV) based on the visual-oriented construct the steering control based on the the kinesthetic schema humanoid intelligent model, including straight, right angle, S-type, to avoid impaired steering model. Steering control strategy on the basis of the analysis of AGV design a multi-modal intelligent controller based on the theory of the schema, feature recognition results, select the appropriate control algorithms, including simulated intelligent control, fuzzy control, and so on. Fourth, have their own characteristics and applications for intelligent control methods, integrated fuzzy neural network control method. Play a neural network parallel computing, distributed information storage, fault tolerance, and fuzzy systems suitable to express of those fuzzy or qualitative knowledge, reasoning similar to the comprehensive advantages of the mindset. Fifth, the traditional method of control systems and complete theory, the need for more accurate mathematical models for system analysis and design, the intelligent control methods can be less dependent on model, but its still a lack of systematic and complete theory rely more on experience and trial and error, it is obvious to a combination of the two can give full play to their respective advantages. The simulation and experimental results show that, the design steering model and multi-modal control algorithm enables the system quickly and smoothly track-oriented path, the effect is significantly superior to conventional controller, V-AGV system reflects broad market prospect.

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