Title :
Adaptive Optimal Iterative Learning Control for Local Ramp Metering
Author :
Jin, ShangTai ; Hou, Zhongsheng
Author_Institution :
Adv. Control Syst. Lab., Beijing Jiaotong Univ., Beijing
Abstract :
In this work, a novel adaptive optimal iterative learning control algorithm (AOILC) is applied to address the traffic density control via ramp metering in a macroscopic level freeway environment. The traffic density control problem is formulated into an output tracking problem and the initial traffic density is variable with iteration change. Rigorous analyses and intensive simulations show the effectiveness of the algorithm.
Keywords :
adaptive control; iterative methods; learning systems; optimal control; road traffic; tracking; traffic control; adaptive optimal iterative learning control; local ramp metering; macroscopic level freeway environment; output tracking problem; traffic density control; Adaptive control; Control design; Control system synthesis; Design optimization; Intelligent robots; Intelligent transportation systems; Nonlinear control systems; Optimal control; Programmable control; Traffic control; Iterative learning control; Local Ramp Metering;
Conference_Titel :
Power Electronics and Intelligent Transportation System, 2008. PEITS '08. Workshop on
Conference_Location :
Guangzhou
Print_ISBN :
978-0-7695-3342-1
DOI :
10.1109/PEITS.2008.80