The Design of Neuro-Fuzzy Control System Based on Data Fusion

2014 ◽  
Vol 678 ◽  
pp. 406-409
Author(s):  
Xiao Rong Fu
Keyword(s):  
Nonlinear Systems ◽  
Data Fusion ◽  
Intelligent Control ◽  
Fuzzy Controller ◽  
Control Technique ◽  
Fusion Method ◽  
Neuro Fuzzy ◽  
Simulation Results ◽  
Using Data ◽  
Self Learning

An adaptive neuro-fuzzy controller of nonlinear systems is presented based on data fusion method. It reduces the input dimension of the controller using data fusion technique and simplifies the fuzzy controller’s design. The fuzzy controller was designed with self-learning of neural networks. The simulation results show that the performance of the system is superior to that using conventional fuzzy controller. It is rewarding for the research on combination of data fusion method and intelligent control technique of nonlinear systems.

scholarly journals Development of Novel Average Neuro Fuzzy Hybrid Control Technique for Robot Navigation in Unknown Environments

2020 ◽  
Vol 1 (1) ◽  
Keyword(s):  
Mobile Robot ◽  
Robot Control ◽  
Fuzzy Controller ◽  
Hybrid Control ◽  
Robot Navigation ◽  
Control Technique ◽  
Complex Environments ◽  
Cluttered Environment ◽  
Neuro Fuzzy ◽  
Simulation Results

The current research focuses on development and analysis of novel Average Neuro-Fuzzy Controller for path planning and navigation of mobile robot in highly cluttered environment. During the investigation various researches related to robot, control and navigation have been analysed. For mapping the environments several distance sensors mounted on the robot are used. The sensors readings about the environments have been segmented into various sectors (front, left, right and back sectors). Using the sensors reading robots negotiate with the obstacles present in the environments during navigation from start to goal point. Experimental and simulation results obtained during the current research from various exercises are in agreement and are within 3%. Comparisons between results show the effectiveness of the proposed technique for robot navigation in complex environments. This technique can be used to address various engineering optimisation problems.

scholarly journals Fuzzy Logic for Intelligent Control System Using Soft Computing Applications

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2617
Author(s):  
Catalin Dumitrescu ◽  
Petrica Ciotirnae ◽  
Constantin Vizitiu
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Soft Computing ◽  
Intelligent Control ◽  
Fuzzy Controller ◽  
Control Technique ◽  
Distributed Intelligence ◽  
High Level ◽  
The Impact ◽  
Fuzzy Subsets

When considering the concept of distributed intelligent control, three types of components can be defined: (i) fuzzy sensors which provide a representation of measurements as fuzzy subsets, (ii) fuzzy actuators which can operate in the real world based on the fuzzy subsets they receive, and, (iii) the fuzzy components of the inference. As a result, these elements generate new fuzzy subsets from the fuzzy elements that were previously used. The purpose of this article is to define the elements of an interoperable technology Fuzzy Applied Cell Control-soft computing language for the development of fuzzy components with distributed intelligence implemented on the DSP target. The cells in the network are configured using the operations of symbolic fusion, symbolic inference and fuzzy–real symbolic transformation, which are based on the concepts of fuzzy meaning and fuzzy description. The two applications presented in the article, Agent-based modeling and fuzzy logic for simulating pedestrian crowds in panic decision-making situations and Fuzzy controller for mobile robot, are both timely. The increasing occurrence of panic moments during mass events prompted the investigation of the impact of panic on crowd dynamics and the simulation of pedestrian flows in panic situations. Based on the research presented in the article, we propose a Fuzzy controller-based system for determining pedestrian flows and calculating the shortest evacuation distance in panic situations. Fuzzy logic, one of the representation techniques in artificial intelligence, is a well-known method in soft computing that allows the treatment of strong constraints caused by the inaccuracy of the data obtained from the robot’s sensors. Based on this motivation, the second application proposed in the article creates an intelligent control technique based on Fuzzy Logic Control (FLC), a feature of intelligent control systems that can be used as an alternative to traditional control techniques for mobile robots. This method allows you to simulate the experience of a human expert. The benefits of using a network of fuzzy components are not limited to those provided distributed systems. Fuzzy cells are simple to configure while also providing high-level functions such as mergers and decision-making processes.

scholarly journals Automation of microclimate in greenhouses

2020 ◽  
Vol 210 ◽  
pp. 05004
Author(s):  
Marina Ganzhur ◽  
Alexey Ganzhur ◽  
Andrey Kobylko ◽  
Denis Fathi
Keyword(s):  
Intelligent Control ◽  
Experimental Validation ◽  
Fuzzy Controller ◽  
Asynchronous Motor ◽  
Measurement Data ◽  
Indoor Climate ◽  
Intelligent Control System ◽  
Dynamic Simulation Model ◽  
Simulation Results ◽  
Favorable Conditions

An agricultural greenhouse is a complex system with many input features. Taking these features into consideration creates favorable conditions for the production of plants. The parameters are temperature and internal humidity, which have a significant impact on the yield. The aim of this study was to propose a dynamic simulation model in the MATLAB/Simulink environment for experimental validation. In addition, a fuzzy controller for the indoor climate of the greenhouse with an asynchronous motor for ventilation, heating, humidification, etc. has been designed. The model includes an intelligent control system for these drives in order to ensure optimal indoor climate. The dynamic model was validated by comparing simulation results with experimental measurement data. These results showed the effectiveness of the control strategy in regulating the greenhouse indoor climate.

scholarly journals AUTOMATION OF MICROCLIMATE WITH THE USE OF MODERN EQUIPMENT IN GREENHOUSES AND GREENHOUSES

2020 ◽  
Author(s):  
M.A. Ganzhur ◽  
◽  
A.P Ganzhur ◽  
D.L. Romanov
Keyword(s):  
Intelligent Control ◽  
Experimental Validation ◽  
Fuzzy Controller ◽  
Asynchronous Motor ◽  
Plant Production ◽  
Indoor Climate ◽  
Intelligent Control System ◽  
Dynamic Simulation Model ◽  
Simulation Results ◽  
Favorable Conditions

An agricultural greenhouse is a complex and system with many input characteristics. Accounting for which creates favorable conditions for plant production. The parameters are temperature and internal humidity, which have a significant impact on the yield. The aim of this study was to propose a dynamic simulation model in MATLAB / Simulink for experimental validation. In addition, the fuzzy controller has been designed to control the indoor climate of the greenhouse with an asynchronous motor for ventilation, heating, humidification, etc. The model has implemented an intelligent control system for these drives to ensure an optimal indoor climate. The dynamic model was validated by comparing simulation results with experimental measurements. These results showed the effectiveness of the control strategy in regulating the indoor climate of the greenhouse.

scholarly journals Design of a fuzzy controller for open architecture quadrotor

2020 ◽  
pp. 16-25
Author(s):  
Saida Charre-Ibarra ◽  
Thonatiuh Valdovinos-Jimenez ◽  
Janeth Alcalá-Rodríguez ◽  
Jorge Gudiño-Lau
Keyword(s):  
Data Acquisition ◽  
Intelligent Control ◽  
Fuzzy Controller ◽  
Data Acquisition System ◽  
Power Line ◽  
Open Architecture ◽  
Control Technique ◽  
Work Processes ◽  
Labview Software ◽  
The Stability

The use of quadrotor helicopters has now increased, especially in civilian applications such as maintenance tasks related to power line or large construction status control, surveillance, crop control in agriculture, work processes in the logistics sector, among others. One of the main problems with some of the conventional designs is the lack of stability. This paper presents the design of a controller using an intelligent control technique to achieve the stability of a quadrotor, to experiment an open architecture quadcopter helicopter was developed, the controller was programmed using LabVIEW software and the data acquisition system is based on the NI PCI 6251 card.

Intelligent Temperature Control of Ceramic Kiln Based on Data Fusion Technology

2011 ◽  
Vol 128-129 ◽  
pp. 177-180
Author(s):  
Yong Hong Zhu ◽  
Jun Wan
Keyword(s):  
Control System ◽  
Data Fusion ◽  
Temperature Control ◽  
Intelligent Control ◽  
Sensor Data ◽  
Temperature Control System ◽  
Fusion Method ◽  
Fusion Technology ◽  
Multi Sensor Data Fusion ◽  
Kiln Temperature

At first, according to the feature of ceramic kiln, this paper studies a fundamental data fusion method which is applied to ceramic kiln temperature control system. This method is used to solve the parameter estimation problem in measurement noise environment. Then, it proposes a kind of intelligent control structure of ceramic kiln temperature control system based on multi-sensor data fusion technology. At last, this data fusion method is applied to intelligent temperature control system of ceramic kiln. The result shows that the method proposed is effective and feasible.

Nonlinear Control of Multiple Equilibrium Systems and Unknown Sinusoidal Disturbance by Using Backstepping Technique and Neural-Fuzzy Controller

2007 ◽  
Author(s):  
Nona Abolfathi Nobari ◽  
Danial Alizadeh
Keyword(s):  
Nonlinear Systems ◽  
Fuzzy Controller ◽  
Initial Conditions ◽  
Equilibrium Points ◽  
Multiple Equilibrium ◽  
Phase Portraits ◽  
Backstepping Method ◽  
Neuro Fuzzy ◽  
Unknown Amplitude ◽  
Sinusoidal Disturbance

Controlling nonlinear systems have always been a challenging problem. Complexity is mostly the result of nonlinear systems behavior dependence on initial conditions and input. Linearization techniques are such kinds of nonlinear systems analysis tools, which can give suitable results in neighborhood of equilibrium points. In addition, phase portraits are very efficient for visualizing the behavior of system in equilibrium points’ neighborhood. In this paper, designing a controller for a low order dynamic system with multiple equilibrium points in presence of a sinusoidal disturbance with unknown amplitude and unknown bounded frequency is investigated. The proposed controller is based on a combination of the backstepping method, Lyapunov based techniques and neuro-fuzzy strategies. At first, the mathematical dynamic model is presented and all equilibrium points are found. Lyapunov-based techniques and backstepping method are combined in order to control the system under influence of sinusoidal disturbance with unknown amplitude but fixed frequency. Finally, a neuro-fuzzy controller is designed and added to main controller to tolerate the frequency variation of the disturbance. Simulation results are presented to demonstrate the performance of the controller in omission of a sinusoidal disturbance with random variable frequency and amplitude.

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