Abstract:
The process of traffic signal control can be taken as a typical network control system (NCSs), which has extensive application in many fields for its easy maintenance and installation. However, there are still some problems on NCSs in practical analysis and design, such as network delay, packet loss, signal quantization, and multi-packet transmission, which may decrease the performance of the control system and further lead to system instability. This paper presents an adaptive event-triggered model predictive control (MPC) strategy to reduce the communication consumption. The resulting framework is used for the stabilization of uncertain NCSs subject to quantization. The system state and control signals are transmitted via wireless networks only when the triggering conditions are satisfied, in which the adaptive triggering mechanism has more flexible and better performance. The adaptive triggering condition decides how often to transmit the current sample data. Under this mechanism, a robust MPC is designed to ensure the stability of closed-loop NCSs with quantized effects and achieve the desired control performance, meanwhile, reduce the energy consumption and improve the network congestion. A solving algorithm on the proposed control method is also given. Finally, it is shown via a simulation example that the proposed event-triggered MPC method can ensure the robust stability of the controlled system, meanwhile, the event-triggered mechanism can save more communication resources.