Asymptotic Tracking Control of Freeway Traffic Density via Ramp Metering

2012 ◽  
Vol 253-255 ◽  
pp. 1686-1690
Author(s):  
Xiao Hong Fan ◽  
Yong Feng Ju
Keyword(s):  
Tracking Control ◽  
Flow System ◽  
Ramp Metering ◽  
Traffic Density ◽  
Unknown Parameters ◽  
External Disturbances ◽  
Freeway Traffic ◽  
Control Gain ◽  
Asymptotic Tracking ◽  
Ramp Signal

The method of the robust integral of the sign of the error was used to design the ramp signal for traffic flow system of freeway with uncertaines . Uncertain terms are allowed to be modelled or unmodelled.The unmodelled terms in the model were estimated by there bounded differential . Compared with other ramp metering method, this controller is designed without approximately linearizing the complicated nonlinear model and requiring the upper bound of unmodelled terms known .The control gain is reduced .The method is verified to be robust subject to both external disturbances and unmodelled dynamics ,and to be adaptive to unknown parameters . The numerical example shows good tracking performance .

Asymptotic tracking control scheme for mechanical systems with external disturbances and friction

2010 ◽  
Vol 73 (7-9) ◽  
pp. 1293-1302 ◽  
Author(s):  
Lili Cui ◽  
Huaguang Zhang ◽  
Bing Chen ◽  
Qingling Zhang
Keyword(s):  
Tracking Control ◽  
Mechanical Systems ◽  
External Disturbances ◽  
Control Scheme ◽  
Asymptotic Tracking

Linear Matrix Inequality Robust Tracking Control Conditions for Nonlinear Disturbed Interconnected Systems

2017 ◽  
Vol 139 (6) ◽  
Author(s):  
Ali Sghaier Tlili
Keyword(s):  
Tracking Control ◽  
Design Method ◽  
Performance Criterion ◽  
Interconnected Systems ◽  
Linear Matrix ◽  
Robust Tracking Control ◽  
External Disturbances ◽  
Control Approach ◽  
Control Gain ◽  
And Control

The objective of this paper is to develop a robust decentralized observer-based feedback model reference tracking control approach for a class of nonlinear disturbed interconnected systems. The proposed H∞ control and observation design method is formulated within an optimization problem involving linear matrix inequalities (LMIs), efficiently solved by a one-step LMI procedure, to compute the decentralized observation and control gain matrices of each subsystem, and to attenuate the external disturbances affecting the subsystems by minimizing a H∞ performance criterion. A numerical simulation is highlighted on a power system with three-interconnected machines to demonstrate the effectiveness of the developed control approach despite the interconnections between different generators, nonlinearities in the system, and external disturbances.

An Iterative Learning Approach for Freeway Traffic Density Control

2011 ◽  
Vol 317-319 ◽  
pp. 1394-1397 ◽  
Author(s):  
Xin Rong Liang ◽  
Xiao Yan Wu ◽  
Jian Ye Li
Keyword(s):  
Traffic Flow ◽  
Flow Model ◽  
Control Variable ◽  
Iterative Learning ◽  
Ramp Metering ◽  
Traffic Density ◽  
Nonlinear Feedback ◽  
Freeway Traffic ◽  
Traffic Flow Model ◽  
Density Control

In this work, we apply iterative learning method to address the traffic density control problem in a macroscopic level freeway environment with ramp metering. The second-order traffic flow model is firstly formulated. Then traffic density is selected as the control variable in place of traffic occupancy. Based on the traffic flow model and in conjunction with nonlinear feedback theory, an iterative learning based traffic density controller is designed. Finally, the iterative learning based feedback controller is simulated in Matlab software. Simulation results show that this method has good dynamic and steady-state performance, and can achieve an almost perfect tracking performance.

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