Research On Delay Compensation And Scheduling Of Networked Control Systems With Long Delay

The network control system refers to a real-time closed-loop feedback system composed of sensors,controllers,actuators and controlled objects in the control unit connected by the communication network.Compared to traditional digital control systems,the network control system can connect systems distributed in different spatial locations,with the advantages of less wiring,easy expansion and maintenance,and easy remote operation.At the same time,however,the involvement of communication networks will lead to many new problems and considerations,such as the choice of network induced delay compensation and multi-loop scheduling optimization strategy.This academic dissertation research the delay prediction and compensation of networked control systems and network scheduling strategies.Aiming at the problem of network control system delay prediction,the composition and generation mechanism of network induced delay are analyzed.Based on the actual measurement acquisition delay,the characteristics of network induced delay sequence are analyzed,and phase space reconstruction technology is used.Reconstruct the delay sequence data sample space.At the same time,considering the sparse characteristics of the abnormal delay value,the traditional extreme learning machine is improved,and a delay prediction model of the robust extreme learning machine is adopted to improve the prediction accuracy and accuracy of the network control system.A generalized predictive control algorithm is used for the delay compensation of networked control systems with delays greater than one sampling period.At the same time,a recursive fast solution method is adopted for solving the problems of large workload and long busy time when solving the Diophantine equation in the traditional generalized predictive control process.Combined with the advantages of proportional-integral control,the traditional generalized predictive control algorithm is improved to form an improved generalized predictive control with proportional integral structure.The simulation results show that the improved generalized predictive control algorithm with proportional integral can effectively improve the delay compensation effect and improve the dynamic characteristics of the system.Aiming at the scheduling problem of resource-constrained network control system,based on the network two-parameter priority,combined with the variable sampling period dynamic scheduling algorithm.First,the scheduler determines the two-parameter weight according to the network demand degree of the current time loop and the network urgency double parameter,and the quadratic square root mapping function established by the absolute value of the error,thereby realizing the determination of the multi-task scheduling priority.At the same time,the scheduler comprehensively analyzes the performance of each control loop,dynamically adjusts the sampling period of each control loop,and completes the scheduling adjustment under the premise of ensuring the stability of the control system.The simulation shows that the scheduling algorithm improves the service quality of the network control system to some extent.