Modeling a Control System for Actuator of Mechanisms of a Robotic System Based on a Neural Network Controller

2021 ◽  
Author(s):  
Kseniya A. Porokhnenko ◽  
Mikhail P. Belov
Keyword(s):  
Neural Network ◽  
Control System ◽  
Robotic System ◽  
Neural Network Controller ◽  
Network Controller

Research on Intelligent Variable Frequency of Air-Conditioner Control System Based on Fuzzy Control

2011 ◽  
Vol 110-116 ◽  
pp. 4076-4084
Author(s):  
Hai Cun Du
Keyword(s):  
Neural Network ◽  
Control System ◽  
Fuzzy Control ◽  
Fuzzy Neural Network ◽  
Air Conditioner ◽  
Neural Network Controller ◽  
The Neural Network ◽  
Network Controller ◽  
Fuzzy Neural ◽  
Fuzzy Control Strategy

In this paper, we determine the fuzzy control strategy of inverter air conditioner, the fuzzy control model structure, the neural network and fuzzy control technology, structural design of the fuzzy neural network controller as well as the neural network predictor FNNC NNP. Simulation results show that the fuzzy neural network controller can control the accuracy greatly improved the compressor, and the control system has strong adaptability to achieve a truly intelligent; model of the controller design and implementation of technology are mainly from the practical point of view, which is practical and feasible.

Teaching Neural Network Control System Design Using a Low-Cost Rapid Control Prototyping Platform

2013 ◽  
Author(s):  
Francisco Franquiz ◽  
Alecia Hurst ◽  
Yan Tang
Keyword(s):  
Neural Network ◽  
Control System ◽  
Low Cost ◽  
Network Control ◽  
Control System Design ◽  
Neural Network Control ◽  
Neural Network Controller ◽  
Network Controller ◽  
Rapid Control ◽  
Rapid Control Prototyping

This paper presents the use of a low-cost rapid control prototyping platform, HILINK, in teaching a graduate course on neural network control system design for mechanical engineering students. The HILINK platform offers a seamless interface between physical plants and Simulink for implementation of hardware-in-the-loop real-time control systems. With HILINK, student can quickly build a neural network controller for applications using Neural Network Toolbox in Simulink. As a result, students can use one single environment for both computer simulation and hardware implementation to understand theories and tackle practical issues in a limited time frame. The paper presents the experimental setup and implementation process of the NARMA-L2 controller for DC motor speed control, and demonstrates the convenience and effectiveness of using HILINK in developing a neural network controller.

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