Fixed-time Control Method Research Articles

Design and Optimization of Urban Signal Fuzzy Controller Based on IQPSO

In order to overcome the shortcomings of traffic signal fixed-time control method, a fuzzy control algorithm for urban traffic signal is proposed. The signal phase switching order is adjustable. The improved quantum particle swarm optimization(QPSO) is also introduced to optimize fuzzy control rules of traffic signal controller. Take four-phase traffic signal commonly used in current practice for example. Compared with traffic signal fixed-time control and single fuzzy control method, the control method put forward in this paper can reduce the vehicles’ average delay time in junction. The simulation results show that the proposed algorithm is proved to be an effective and practicable method for urban traffic self-adaptive control.

Rate control-based strategy to enhance biological nitrogen removal during anoxic/oxic sludge digestion

Anoxic/oxic (A/O) sludge digestion is a waste-activated sludge (WAS) treatment practice that simultaneously reduces volatile suspended solids reduction and removes nutrients from digested sludge. This study aims to optimize the performance of A/O sludge digestion by achieving the optimum alkalinity and nitrogen balance through rate control. Rate control involves oxic/anoxic cycling based on the activity of WAS (i.e. ammonification, nitrification, oxygen utilization, and denitrification rates) and controlling the processes of amonification, nitrification, oxygen ultilization, and denitrification in WAS. This strategy is different from pH, oxidation–reduction potential, dissolved oxygen controls, or fixed time control methods. Laboratory-scale batch aerobic digestion and A/O digestion tests were performed to verify the feasibility of the approach. The optimum operational cycles for the aeration and mixing were determined as 3.5 and 2.5 h, respectively (6 h full cycle). The sludge reduction in A/O digestion was greater than that in the aerobic digestion (51.83 vs. 48.13%) at a sludge retention time of 23 d. The total nitrogen reduction in A/O digestion was significantly higher than that in the aerobic digestion (65.20 vs. 12.27%). The performance of the proposed rate-control strategy for A/O digestion is superior to those of other experimental control schemes. In addition, this technique produces a sludge dewatering liquor with low nitrogen and phosphorus concentrations.

Service-oriented dynamic data driven application systems to urban traffic management in resource-bounded environment

With advance in distributed system technology, data has become ubiquitous and its dynamics has increased. Therefore, in this paper we proposed a new framework to integrate dynamic data driven application systems (DDDAS) with service-oriented architecture (SOA) and web services technology to tackle dynamic data issue in a real-time and resource-bounded environment. Nowadays, traffic management in Intelligent Transportation Systems (ITS) has been widely developed in major cities' urban areas around the world to provide more efficient way for solving traffic congestion problem. However, the problems in dynamic traffic management systems such as system flexibility, data standard common interface, transmission of required information, prediction performance, and real-time measurement data are all important issues but not totally supported. An efficient and effective service-oriented dynamic data-driven framework algorithm is designed in this paper to support prediction strategies for traffic management. The simulation results of vehicle navigation show that our algorithm outperforms the Dijkstra algorithm by improving 24.43% in average vehicle travelling time. On the other hand, the results of traffic signal control also show that our algorithm improves the performance in vehicles average number of stops by 43.7%, and 70.62% in average delay time that is compared with the fixed time control method.

Urban Oversaturated Traffic Network Control Based on Stability Preference Multi-Objective Compatible Optimization Control

To solve the traffic congestion control problem on oversaturated network, the control problem is formulated as a conflicted multi-objective control problem., a new stability preference multi-objective compatible optimization control(SPMOCC) algorithm is proposed to solve the conflicted multi-objective control problem. In the proposed SPMOCC algorithm, NSGA-II algorithm is adjusted by proposing non-even Pareto front spread preserving strategy to obtain some special area on the Pareto front; a stability preference selection strategy is proposed to obtain stable controller. The proposed SPMOCC is used to solve the oversaturated traffic network control problem in a core area of 11 junctions under the simulation environment. It is proved that the proposed compatible optimization control algorithm can handle the oversaturated traffic network control problem effectively than the fixed time control method.

Urban Oversaturated Traffic Network Control Based on Preference Multi-Objective Compatible Optimization Control

To solve the traffic congestion control problem on oversaturated network, the total delay is classified into two parts: the feeding delay and the non-feeding delay, and the control problem is formulated as a conflicted multi-objective control problem. The simultaneous control of multiple objectives is different from single objective control in that there is no unique solution to multi-objective control problems(MOPs). Multi-objective control usually involves many conflicting and incompatible objectives, therefore, a set of optimal trade-off solutions known as the Pareto-optimal solutions is required. Based on this background, a modified compatible control algorithm(MOCC) hunting for suboptimal and feasible region as the control aim rather than precise optimal point is proposed in this paper to solve the conflicted oversaturated traffic network control problem. Since it is impossible to avoid the inaccurate system model and input disturbance, the controller of the proposed multi-objective compatible control strategy is designed based on feedback control structure. Besides, considering the difference between control problem and optimization problem, user's preference are incorporated into multi-objective compatible control algorithm to guide the search direction. The proposed preference based compatible optimization control algorithm(PMOCC) is used to solve the oversaturated traffic network control problem in a core area of eleven junctions under the simulation environment. It is proved that the proposed compatible optimization control algorithm can handle the oversaturated traffic network control problem effectively than the fixed time control method.