scholarly journals The formation of control actions in the automatic climate control system in the production of electronics based on the inclusion of a fuzzy controller in the recurrence algorithm

2020 ◽  
Vol 1515 ◽  
pp. 052033
Author(s):  
N A Aleshkin ◽  
A P Aleshkin ◽  
A A Petrushevskaya
Keyword(s):  
Control System ◽  
Fuzzy Controller ◽  
Climate Control ◽  
Control Actions ◽  
Recurrence Algorithm

Simplified architecture of a type-2 fuzzy controller using four embedded type-1 fuzzy controllers and its application to a greenhouse climate control system

2009 ◽  
Vol 223 (5) ◽  
pp. 619-631 ◽  
Author(s):  
I A Hameed
Keyword(s):  
Control System ◽  
Control Systems ◽  
Degrees Of Freedom ◽  
Fuzzy Controller ◽  
Climate Control ◽  
Fuzzy Logic Systems ◽  
Greenhouse Climate ◽  
Greenhouse Climate Control

Uncertainty is an inherent part of control systems used in real-world applications. The use of new methods for handling incomplete information and to cope with large amounts of uncertainties is of fundamental importance. The traditional type-1 fuzzy sets (T1FSs) used in conventional fuzzy logic systems (FLSs) cannot fully handle the uncertainties present in control systems. The type-2 FSs (T2FSs) used in T2FLSs can handle such uncertainties in a better way because they provide more parameters and more degrees of freedom. In spite of the features of the T2FS, it has not received the attention it deserves because of its implementation complexity. In this paper, a simple architecture of the T2FLS using four embedded T1FLSs is introduced. The performance of the proposed T2FLS is assessed by applying it to a multi-input multi-output (MIMO) greenhouse climate control system. Simulation results showed that the simplified architecture is able to cope with the complexity of the plant and has the ability to handle measurement and modelling uncertainties. The performance of the proposed T2FLS is comparable with the computationally costly T2FLS and outperforms its traditional T1FLS counterpart.

scholarly journals Synthesis of a fuzzy controller for identification and quantification of disturbances by trends

2021 ◽  
Vol 2094 (4) ◽  
pp. 042084
Author(s):  
E A Muravyova ◽  
R F Imaev
Keyword(s):  
Mathematical Model ◽  
Control System ◽  
Heat Exchanger ◽  
Automatic Control ◽  
Control Systems ◽  
Fuzzy Controller ◽  
Practical Importance ◽  
Heating Cycle ◽  
System State ◽  
Control Actions

Abstract This article describes the main stages of constructing a fuzzy controller that identifies disturbances in the automatic control system by trends on the example of the brine cycle, namely, heating the purified one going to electrolysis. This method can be implemented in perturbation control systems for the formation of control actions, as well as for diagnostic purposes. The aim of the study is to synthesize a fuzzy controller for identifying and quantifying perturbations by trends. The article proposes a method for estimating perturbations by trends. A mathematical model of processes implemented in the Mathcad environment is constructed. A conceptual model of a fuzzy controller for determining the perturbation is implemented. As a result of the research conducted on the basis of the proposed method, two fuzzy controllers were synthesized that quantify disturbances in the water heating cycle, namely: the deviation of the temperature of the purified brine entering the heat exchanger, as well as the deviation of the water temperature in the tank from the norm. The developed project is of practical importance, since the information about disturbances obtained as an output value from the fuzzy controller can be used in the diagnosis and assessment of the system state at any time, which, in turn, can be used for smoother control when applying a correction signal to the controller that controls the dampers and pumps, as well as to prevent accidents.

SYNTHESIS AND OPTIMIZATION OF FUZZY CONTROLLER FOR CONTROL SYSTEM OF FLOATING DOCK DRAFT

2016 ◽  
Vol 23 (99) ◽  
pp. 113-120
Author(s):  
Yuri P. Kondratenko ◽  
◽  
Alexey V. Korobko ◽  
Alexey V. Kozlov ◽  
Andrej N Topalov ◽  
...  
Keyword(s):  
Control System ◽  
Fuzzy Controller

Path Tracking Controller Design of Automatic Guided Vehicle Based on Four-Wheeled Omnidirectional Motion Model

2020 ◽  
Vol 17 (2) ◽  
pp. 7996-8010
Author(s):  
X. Wu ◽  
Y. Yang
Keyword(s):  
Control System ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Threshold Value ◽  
Position Angle ◽  
Path Tracking ◽  
Global Coordinate System ◽  
Automatic Guided Vehicle ◽  
Input Variables ◽  
Industrial Pc

This paper presents a new design of omnidirectional automatic guided vehicle based on a hub motor, and proposes a joint controller for path tracking. The proposed controller includes two parts: a fuzzy controller and a multi-step predictive optimal controller. Firstly, based on various steering conditions, the kinematics model of the whole vehicle and the pose (position, angle) model in the global coordinate system are introduced. Secondly, based on the modeling, the joint controller is designed. Lateral deviation and course deviation are used as the input variables of the control system, and the threshold value is switched according to the value of the input variable to realise the correction of the large range of posture deviation. Finally, the joint controller is implemented by using the industrial PC and the self-developed control system based on the Freescale minimum system. Path tracking experiments were made under the straight and circular paths to test the ability of the joint controller for reducing the pose deviation. The experimental results show that the designed guided vehicle has excellent ability to path tracking, which meets the design goals.

scholarly journals An Adaptive Neuro-Fuzzy Control of Pneumatic Mechanical Ventilator

Actuators ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 51
Author(s):  
Jozef Živčák ◽  
Michal Kelemen ◽  
Ivan Virgala ◽  
Peter Marcinko ◽  
Peter Tuleja ◽  
...  
Keyword(s):  
Control System ◽  
Control Algorithm ◽  
Fuzzy Inference ◽  
Fuzzy Controller ◽  
Mechanical Design ◽  
Mechanical Ventilator ◽  
Mechanical Ventilators ◽  
Inference System ◽  
Control Approach ◽  
Neuro Fuzzy

COVID-19 was first identified in December 2019 in Wuhan, China. It mainly affects the respiratory system and can lead to the death of the patient. The motivation for this study was the current pandemic situation and general deficiency of emergency mechanical ventilators. The paper presents the development of a mechanical ventilator and its control algorithm. The main feature of the developed mechanical ventilator is AmbuBag compressed by a pneumatic actuator. The control algorithm is based on an adaptive neuro-fuzzy inference system (ANFIS), which integrates both neural networks and fuzzy logic principles. Mechanical design and hardware design are presented in the paper. Subsequently, there is a description of the process of data collecting and training of the fuzzy controller. The paper also presents a simulation model for verification of the designed control approach. The experimental results provide the verification of the designed control system. The novelty of the paper is, on the one hand, an implementation of the ANFIS controller for AmbuBag pressure control, with a description of training process. On other hand, the paper presents a novel design of a mechanical ventilator, with a detailed description of the hardware and control system. The last contribution of the paper lies in the mathematical and experimental description of AmbuBag for ventilation purposes.

Analysis and Synthesis of a Fuzzy Controller by the Phase Plane Method

2021 ◽  
Vol 22 (10) ◽  
pp. 507-517
Author(s):  
Y. A. Bykovtsev
Keyword(s):  
Control System ◽  
Automatic Control ◽  
Automatic Control System ◽  
Phase Plane ◽  
Fuzzy Controller ◽  
Piecewise Linear ◽  
Plane Method ◽  
Phase Trajectories ◽  
Analysis And Synthesis ◽  
Phase Plane Method

The article is devoted to solving the problem of analysis and synthesis of a control system with a fuzzy controller by the phase plane method. The nonlinear transformation, built according to the Sugeno fuzzy model, is approximated by a piecewise linear characteristic consisting of three sections: two piecewise linear and one piecewise constant. This approach allows us to restrict ourselves to three sheets of phase trajectories, each of which is constructed on the basis of a second-order differential equation. Taking this feature into account, the technique of "stitching" of three sheets of phase trajectories is considered and an analytical base is obtained that allows one to determine the conditions for "stitching" of phase trajectories for various variants of piecewise-linear approximation of the characteristics of a fuzzy controller. In view of the specificity of the approximated model of the fuzzy controller used, useful analytical relations are given, with the help of which it is possible to calculate the time of motion of the representing point for each section with the involvement of the numerical optimization apparatus. For a variant of the approximation of three sections, a technique for synthesizing a fuzzy controller is proposed, according to which the range of parameters and the range of input signals are determined, at which an aperiodic process and a given control time are provided. On the model of the automatic control system of the drive level of the mechatronic module, it is shown that the study of a fuzzy system by such an approximated characteristic of a fuzzy controller gives quite reliable results. The conducted studies of the influence of the degree of approximation on the quality of control show that the approximated characteristic of a fuzzy controller gives a slight deterioration in quality in comparison with the smooth characteristic of a fuzzy controller. Since the capabilities of the phase plane method are limited to the 2nd order of the linear part of the automatic control system, the influence of the third order on the dynamics of the system is considered using the example of a mechatronic module drive. It is shown that taking into account the electric time constant leads to overshoot within 5-10 %. Such overshoot can be eliminated due to the proposed recommendations for correcting the static characteristic of the fuzzy controller.

Design and Simulation of Temperature Control System in Intermittent Reaction Kettles Based on Intelligent Fuzzy Control

2013 ◽  
Vol 380-384 ◽  
pp. 294-297 ◽  
Author(s):  
Xin Wei Li
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Pid Control ◽  
Elevated Temperatures ◽  
Fuzzy Controller ◽  
Dynamic Performance ◽  
Temperature Curve ◽  
Time Variable ◽  
Temperature Control System ◽  
New Type

A temperature rising control system and temperature maintaining control system were designed in according to time-variable and hysteretic nature of temperature change and limitation when traditional PID control deals with nonlinear systems. A new type of intelligent fuzzy controller combination of traditional PID control and fuzzy control was designed and applied in temperature maintaining control system. The simulation results show that the holding phase at elevated temperatures and temperature, the temperature curve has a high steady-state accuracy and dynamic performance in the period of temperature rising and maintaining, and the system and controller cause a better result.

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