Abstract
Abstract Aiming at the issues of random delay and delay uncertainty in both the before channel and feedback channel for network control system, the root causes of random delay influence closed-loop control system by case is analysis, and the predictive control method based on neural network to solve the feasibility of existence network random delay in control system closed-loop control has provided. Simulation results show that the method can reflect and predict the delay characteristics of between measurement data represents the network path, and can effectively substitute for the actual network in the design of closed-loop control system based on Internet to research; the method used fast and accurate can be used for online learning network model and forecast the network delay value, provides a new way to remote closed-loop control based on Internet.
Highlights
Network control system based on Internet broke through the many limitations on control system based on field bus and become the new development direction of the network control system, stable, fast, and accurate still the ultimate goal of network control systems pursued [1]
In order to study the impact of network latency on the remote closed-loop control system, set up remote motor control system platform based on Internet, a brushless DC motor as charged object, developed DSP as core and motor drive modules with serial communication functions which directly connected the server serial port in order to facilitate the research on motor network control technology and control network functions embedded in the information networks, for the development of the control network search a more portable way, that is though the method of control functions embedded in the information network to build control information network
The delay of the control network is time-varying and controlled objects are often immediately confounding factors, it is can not use an inconvenience model to predict the state of system and can not use a specific delay time to do the fixed step predictive control, neural network has the advantages of online learning the state of the system, predictive control based on neural network has strong robustness to be adaptive to the change of system status and network delay aspects,it is a way to solve the network latency closed-loop control
Summary
Network control system based on Internet broke through the many limitations on control system based on field bus and become the new development direction of the network control system, stable, fast, and accurate still the ultimate goal of network control systems pursued [1]. When any one parameter value in the packet exceeds its threshold, the dynamic information was only package and send to the client, data transmission in such networks is greatly reduced These two aspects, due to reduce the data volume, network congestion reduced and delay and packet loss are greatly improved. The experimental results show that, when according to the principle of Smith compensator design dynamic compensation and appropriate delay prediction algorithm can make the Stability original system before not join the network latency links to restore stability after joining the network, so that the remote control of the mechanical movement using the Internet possible. This paper applied the neural network model predictive control to the network closed-loop system to reduce the impact of random delay to the system, and verified validity of the method by simulation, the method is an effective way to solve the network latency closed-loop control
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