Research On Intelligent Control Ventilation System For Urban Road Tunnel

The urban road tunnel longitudinal ventilation system has strong time-varying, non-linear and large delay characteristics, and it is difficult to get the precise mathematical model by using the conventional linear control theory. Therefore, searching for a highly efficient and intelligent ventilation control system to reduce operating expense of tunnel ventilation system has become one of the most critical issues to be handled in the construction of the road tunnels. In this thesis, an intelligent control technology for urban tunnel ventilation system is proposed.On the basis of aerodynamic theory, the aerodynamic model, pollution model and traffic flow model are established, and the necessary theoretical basis is founded for the following research on intelligent control model.Introducing the fuzzy control technology, we design the fuzzy rule base as per experts' or operators' knowledge and experience, and establish intelligent fuzzy control model. Then, with adjusting and optimizing the rule base of fuzzy control model , the fuzzy logic controller which bases on the real-time detection of CO/VI concentration and the standard setting of CO/VI(Carbon monoxide and Visibility) concentration difference could conduct the fuzzy reasoning and work out the number of fans to be switched on. Avoiding the mathematic models, the fuzzy control system can well adapt to the non-linear and distributed parameter characteristics of urban road tunnel ventilation system.Because of the time-varying characteristic of road tunnel, many problems have emerged when using fuzzy control system, e.g. the membership functions of the fuzzy variables cannot be changed and the fuzzy logical rules cannot be modified automatically when environmental variables such as traffic flow data, CO/VI concentration value are changed. For this reason, we introduce the neural network technology with powerful learning ability, and merge it with the fuzzy control technology within an equivalent structure on the basis of error feedback learning algorithm, following which, the tunnel ventilation system based on fuzzy neural network technology is studied and discussed in detail.The fuzzy neural network based ventilation control system can automatically adjust the membership functions and modify the fuzzy rule bases. In addition, it has strong self-learning ability. This technology could enhance the automation level of control system, save the time for adjusting and reduce the electric power consumption. It has a good control effect over the basic traffic flow(normal traffic flow, high density traffic flow, sparse traffic flow) in urban road tunnel. The CO/VI concentration is well controlled under the hygienic standard, which realizes the optimized control of fan operation. As compared with the conventional ventilation control system, this system could ensure the energy saving of fan operation up to 10%.The fuzzy neural network control system for the urban road tunnel longitudinal ventilation has great feasibility and practical value, and it has important significance for the current urban road tunnel ventilation control design.