Research Of The Predictive Algorithms For Networked Control Systems

Networked control systems are feedback control systems connected through a real-time network, in which the information is exchanged using a network among control system component (sensors, controller, actuators, etc). Due to the use of network, it could increase the complicacy of analyses and designs on control systems, and cause some problems. The obvious problems are the network-induced delay effect on the system, and the data packet dropout phenomena owing to the uncertainty of the network transmission. Network delays and data packet dropout phenomena degrade the NCS control performance and destabilize the system. Considered the problems in NCSs, research of the predictive control algorithms for networked control systems is done in this thesis.Firstly, the paper introduces the background and the present control methods of NCS; analyzes the issues that influence performance of NCS respectively:sampling period, driving mode of node, and clock synchronization. Some basic problems including network induced delay, dropping network packets, jitter and network scheduling are discussed. Stability Analysis of networked control systems with delay and packets dropping respectively, and considering the two factors at the same time are proposed.Aimed at the network delay and packets dropping, network control methods based on dynamic matrix control (DMC) and generalized predictive controls (GPC) are proposed respectively. Based on the model of networked control system with random delays, the DMC for network delays and compensation strategy for networked control system based on DMC are presented; Network control methods based on GPC including the GPC with Buffer queue strategy, and predictive control for NCS based on pole assignment approach and time-delay error compensating.The proposed methods have several advantages inherited from predictive control. Good performance of the methods is showed in simulations.