A novel control strategy for balancing traffic flow in urban traffic network based on iterative learning control

2018 ◽  
Vol 508 ◽  
pp. 519-531 ◽  
Author(s):  
Fei Yan ◽  
Gaowei Yan ◽  
Mifeng Ren ◽  
Jianyan Tian ◽  
Zhongke Shi
Keyword(s):  
Traffic Flow ◽  
Control Strategy ◽  
Iterative Learning Control ◽  
Learning Control ◽  
Iterative Learning ◽  
Urban Traffic ◽  
Traffic Network ◽  
Urban Traffic Network

scholarly journals Iterative Learning Control of a Nonlinear Aeroelastic System despite Gust Load

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Xing-zhi Xu ◽  
Ya-kui Gao ◽  
Wei-guo Zhang
Keyword(s):  
Control Strategy ◽  
Iterative Learning Control ◽  
Tracking Error ◽  
Learning Control ◽  
Iterative Learning ◽  
Control Surface ◽  
Stream Velocity ◽  
Control Input ◽  
Parameter Uncertainties ◽  
Composite Energy

The development of a control strategy appropriate for the suppression of aeroelastic vibration of a two-dimensional nonlinear wing section based on iterative learning control (ILC) theory is described. Structural stiffness in pitch degree of freedom is represented by nonlinear polynomials. The uncontrolled aeroelastic model exhibits limit cycle oscillations beyond a critical value of the free-stream velocity. Using a single trailing-edge control surface as the control input, a ILC law under alignment condition is developed to ensure convergence of state tracking error. A novel Barrier Lyapunov Function (BLF) is incorporated in the proposed Barrier Composite Energy Function (BCEF) approach. Numerical simulation results clearly demonstrate the effectiveness of the control strategy toward suppressing aeroelastic vibration in the presence of parameter uncertainties and triangular, sinusoidal, and graded gust loads.

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