For a freeway traffic system with strict repeatable pattern, iterative learning control (ILC) has been successfully applied to local ramp metering for a macroscopic freeway environment by formulating the original ramp metering problem as an output tracking, disturbance rejection, and error compensation problem. In this paper, we address the freeway traffic ramp-metering system under a nonstrict repeatable pattern. ILC-based ramp metering and ILC add-on to ALINEA strategies are modified to deal with the presence of iteration-dependent parameters, iteration-dependent desired trajectory, and input constraints. Theoretical analysis and extensive simulations are used to verify the effectiveness of the proposed approaches.
Modified Iterative-Learning-Control-Based Ramp Metering Strategies for Freeway Traffic Control With Iteration-Dependent Factors
IEEE Transactions on Intelligent Transportation Systems ; 13 , 2 ; 606-618
2012-06-01
384590 byte
Article (Journal)
Electronic Resource
English
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