Traffic flow dynamics is an important issue for implementing effective pollutant discharge control of tunnels. Longitudinal ventilation using jet fans is the most popular system for pollutant discharge control of tunnels. Nowadays, jet fans equipped with the frequency conversion technology in the tunnel can shorten the control cycle and even conduct manipulation of step-less jet speeds. The longitudinal ventilation system has considerable inertia and non-linear characteristics, which are partly resulted from traffic flow dynamics such as traffic state transition. Therefore in this study an adaptive control method based on the artificial neural-network theory is proposed to be tailored to the traffic state transition. The model is based on aerodynamic equations and takes vehicle speed and density as main system disturbances, whose value can be determined by fundamental diagram when having incomplete field traffic data. The proposed controller can also cope with the parameters and uncertainties of the time-varying model. The authors simulation results show that the adaptive control method can track the desirable system output effectively whenever the traffic condition changes gently or dramatically. The results also show that their method performs better than the common-used proportional integral derivative controller in terms of system adaptability following the traffic state transition.
Adaptive fine pollutant discharge control for motor vehicles tunnels under traffic state transition
IET Intelligent Transport Systems ; 9 , 8 ; 783-791
2015-10-01
9 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
motorcycles , jet fans , PID controller , step-less jet speed manipulation , neurocontrollers , aerodynamic equations , frequency conversion technology , tunnels , jets , nonlinear characteristics , ventilation , field traffic data , motor vehicle tunnels , traffic state transition , adaptive control , vehicle dynamics , aerodynamics , fans , vehicle speed , vehicle density , traffic flow dynamics , adaptive fine pollutant discharge control method , longitudinal ventilation system , road traffic control , artificial neural-network theory , air pollution control , control cycle , system disturbances , time-varying model , inertia characteristics
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