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The Research Of Iterative Learning Control Method For Speedway On-ramp

Posted on:2009-07-03Degree:MasterType:Thesis
Country:ChinaCandidate:Y W WangFull Text:PDF
GTID:2132360272483431Subject:Traffic Information Engineering & Control
Abstract/Summary:PDF Full Text Request
With the rapid society economic development, highway traffic has increased by geometric levels, traffic congestion and traffic accidents have caused frequently due to the increase in highway traffic, and even the traffic gridlock, the entrance on-ramp freeway traffic control is the most effective approach to improve the situation of highway traffic. According to the characteristics of freeway traffic flow, the paper mainly research on the method of iterative learning control and its application on highway entrance on-ramp control, the research work as follows:This paper has research on the method of the entrance on-ramp control based on iterative learning control (ILC). Research shows that ILC method is simple and effective and has more obvious advantages than any other methods of ramp model-based control. However, the method of study and gain control selected in the system still has to rely on some knowledge. Considering the problems of learning gain settings such as blindness in ILC method, this paper combined the model-free adaptive theory with the method of iterative learning control and put forward a improved model-free adaptive iterative learning control (MF-AILC) strategy.MF-AILC design strategy based on the ramp control algorithms, simulation analysis, the entire sampling period on the strategy to make the same density of traffic flow to the desired level of convergence and export ramp on the repeatability disturbance has certain suppression. On this basis, to optimize the immune algorithm based on the highway ramp and more iterative learning control methods. The largest highway to traffic, travel time and minimize the overall average waiting time for the three entrance to the objective function, immune algorithm used to coordinate multi-ramp iterative learning controller. The simulation results show that the method has good control and the effect is robust, based on immune optimization of iterative learning control on the highway ramp control is more effective to enhance the capacity of the main line and improve the highway running. The safety and efficiency is of great significance.
Keywords/Search Tags:Highway, ramp control, iterative learning, model-free adaptive, immune optimization
PDF Full Text Request
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