Research On Model Predictive Control Methods Based On Can-Bus Networked Control Systems

Based on the model predictive control theory, network-induced delays and data packet dropout are studied in this thesis. The main works are as follows:Firstly, the paper analyzes six fundamental issues that influence performance of NCS respectively: network scheduling delays, sampling period, jitter, data packet dropout, network scheduling and stability. Many research results are given and related handling approaches are remarked.Then, In order to overcome data packet dropout adverse influences on an NCS, the paper proposes a method dealing with these issues based on model predictive control (MPC), and compares it with the existing strategy. The simulation results show that the propose algorithm can improve control performance.And then a network control systems based on CAN bus is built, introduces hardware and software of the system. In the hardware circuit, the system adopts ARM7/LPC2292 micro-processing chips as the main controller and it is designed by making full use of LPC2292-chip periphery circuit. This part mainly introduces the hardware circuit and the five functional modules. In the software design part, emphatically introduces dynamic matrix control algorithm, generalized predictive control algorithm, controller area network algorithm procedure.At the last part, a network control systems based on the tank water-level control equipment modeling is built. And then dynamic matrix control generalized and predictive control algorithm are applied to the experimental system. The experiment validates the feasibility applying the MPC to the NCS, and provides a software frame and experiment platform for further study in the future. Because the study is not only on the MATLAB simulation but also takes account of the communication and the model is a real object model, the conclusions are more authenticity.