A Robust Neural Network Controller for a TITO Interactive Nonlinear System

2006 ◽  
Author(s):  
Ji Li ◽  
Bong Jun ◽  
Pan Lee
Keyword(s):  
Neural Network ◽  
Nonlinear System ◽  
Neural Network Controller ◽  
Network Controller

Application of Multivariable Non-Linear Decoupling Control Based on Neural Network

2012 ◽  
Vol 214 ◽  
pp. 786-791
Author(s):  
Jian Bo Zhang ◽  
Dong Hai Fan ◽  
Ren Zhi Hu
Keyword(s):  
Neural Network ◽  
Nonlinear System ◽  
Distributed Control ◽  
Decoupling Control ◽  
Distributed Control System ◽  
Neural Network Controller ◽  
Mimo Nonlinear System ◽  
The Neural Network ◽  
Network Controller ◽  
The Mathematical Model

Aimed at Neural Network can approach any nonlinear system with arbitrary accuracy, the frame of distributed NN decoupling system are proposed to decouple the MIMO nonlinear system. In this paper, we designed and finished the Distributed Control System based on ABB’s Freelance 800F, and collected experimental data to model the thermostatic heater, then we have carried out the mathematical model by means of MATLAB dynamic simulation. In sequence, we trained the neural network controller in MATLAB. When the decoupling is completed, we used controller to control the MIMO nonlinear system in DCS. Experiment result shows that it is conscientiously feasible and deserves to be widely applied in the process of controlling industry.

scholarly journals Tuning Artificial Neural Network Controller Using Particle Swarm Optimization Technique for Nonlinear System

2021 ◽  
Author(s):  
Sabrine Slama ◽  
Ayachi Errachdi ◽  
Mohamed Benrejeb
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Particle Swarm Optimization ◽  
Nonlinear System ◽  
Optimization Technique ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Neural Network Controller ◽  
Network Controller ◽  
Artificial Neural

This chapter proposes an optimization technique of Artificial Neural Network (ANN) controller, of single-input single-output time-varying discrete nonlinear system. A bio-inspired optimization technique, Particle Swarm Optimization (PSO), is proposed to be applied in ANN to avoid any possibilities from local extreme condition. Further, a PSO based neural network controller is also developed to be integrated with the designed system to control a nonlinear systems. The simulation results of an example of nonlinear system demonstrate the effectiveness of the proposed approach using Particle Swarm Optimization approach in terms of reduced oscillations compared to classical neural network optimization method. MATLAB was used as simulation tool.

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.

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