Abstract

By introducing a new dynamical linearization technology, this paper presents a model-free adaptive control approach for density control of freeway traffic flow via ramp metering, which is consisted with a control input learning law and a parameter updating law. The design and analysis only depends on the I/O data of the freeway traffic system. Furthermore, the control input learning law is extended to a higher-order form by incorporating more control information of previous sampling instants for improving the control performance. Both convergence analysis and simulation results illustrate the validity of the presented methods.

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