scholarly journals Control System of a Robotic Irrigation Machine Based on the Mamdani Fuzzy Algorithm

2021 ◽  
Vol 2096 (1) ◽  
pp. 012014
Author(s):  
I Kafiev ◽  
P Romanov ◽  
I Romanova
Keyword(s):  
Mathematical Model ◽  
Soil Moisture ◽  
Control System ◽  
Fuzzy Control ◽  
Fuzzy Inference ◽  
Control Valve ◽  
Flow Control Valve ◽  
Inference System ◽  
Agricultural Robots ◽  
Matlab Package

Abstract The article analyzes the tasks that can be solved by agricultural robots. The purpose of the study was the robotization of the "Fregat" type crop irrigation machine by the fuzzy control of irrigation technological processes, which allows to control the irrigation rate. It is proposed to use in a robotic irrigation machine the analog valve-setter of the speed of the last cart, powered by electricity. It is recommended to include a diagnostic subsystem in the fuzzy control system of the flow control valve, which includes sensors for measuring the soil moisture and the slope of the irrigation machine in various areas of the field. The mathematical model of fuzzy control of the irrigation machine is developed based on the software control of the water supply depending on the terrain of the field, the speed of irrigation machine and soil moisture to reduce water consumption and improve the efficiency and quality of irrigation. The Mamdani algorithm, which is implemented in the MATLAB package, is proposed as a fuzzy inference system. The formalization of the description of the indicators of the irrigation machine is carried out by specifying linguistic variables. The proposed mathematical model can be used in the design of control systems for other robotic agricultural machines.

Design of Rotary-Type Flow Control Valve for Control of Water-Driven Spindle

2010 ◽  
Author(s):  
Yohichi Nakao ◽  
Hajime Niimiya ◽  
Takuya Obayashi
Keyword(s):  
Mathematical Model ◽  
Control System ◽  
Flow Control ◽  
Mathematical Models ◽  
Rotational Speed ◽  
Control Valve ◽  
Diamond Turning ◽  
Flow Control Valve ◽  
Type Flow ◽  
Rotary Type

Water-driven spindle was developed for producing small and precise parts by the diamond turning processes. Rotational speed of the spindle can be controlled by the flowrate supplied to the spindle. The paper describes a newly developed rotary-type flow control valve that is designed for controlling rotational speed of the water-driven spindle. In particular, the paper focuses on the establishment of the mathematical model capable of representing the characteristics of the open loop control system composed of the pump, flow control valve and spindle. Mathematical models are then derived so that a feedback control system can be designed using the models. Performances of the flow control valve and the spindle are examined through simulation as well as experiments. It is then verified that the derived mathematical models are capable of representing the performance of the system. In addition, the required positioning accuracy of valve rotation for achieving desired control of the rotational speed of the spindle is considered based on the derived linearized mathematical model.

An Wavelet Based Handoff Algorithm for Cognitive Wireless Network

2012 ◽  
Vol 433-440 ◽  
pp. 5087-5091
Author(s):  
Meng Jia Li ◽  
Jing Yao Wang ◽  
Mei Song ◽  
Xiao Jun Wang ◽  
Ning Ning Liu
Keyword(s):  
Control System ◽  
Wavelet Analysis ◽  
Fuzzy Control ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Second Use

This paper proposed a novel handoff algorithm for cognitive network based on wavelet analysis and fuzzy control system. It makes the system cognitive and adaptive to the changes of the environment by two steps: first, make wavelet analysis to the received signal to get the basic signal which is without noise. Second, use adaptive neuro-fuzzy inference system (ANFIS) to make diligent handoff decision. The simulation shows that it improves the performance of the whole system when the channel is in low signal-to-noise ratio.

Research on Elevator Group Control Uncertainty

2014 ◽  
Vol 602-605 ◽  
pp. 874-877
Author(s):  
Dong Mei Yan ◽  
Li Liu
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Control Theory ◽  
Simulation Model ◽  
Control Systems ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Inference System ◽  
Group Control ◽  
Elevator Group Control

Uncertainties elevator group control systems are analyzed first in this paper according to the fuzzy control theory and characteristics of the elevator group control system. Then, simulation model of elevator group control system is built using fuzzy inference system with Matlab. Operation of elevator group control system based on fuzzy control system is shown by simulation.

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.

scholarly journals Development of a GA-Fuzzy-Immune PID Controller with Incomplete Derivation for Robot Dexterous Hand

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Xin-hua Liu ◽  
Xiao-hu Chen ◽  
Xian-hua Zheng ◽  
Sheng-peng Li ◽  
Zhong-bin Wang
Keyword(s):  
Mathematical Model ◽  
Control System ◽  
Pid Controller ◽  
Fuzzy Inference ◽  
Controller Design ◽  
Index Finger ◽  
Parameters Optimization ◽  
Immune Mechanism ◽  
Dexterous Hand ◽  
Incomplete Derivation

In order to improve the performance of robot dexterous hand, a controller based on GA-fuzzy-immune PID was designed. The control system of a robot dexterous hand and mathematical model of an index finger were presented. Moreover, immune mechanism was applied to the controller design and an improved approach through integration of GA and fuzzy inference was proposed to realize parameters’ optimization. Finally, a simulation example was provided and the designed controller was proved ideal.

Modeling and Optimal Control of a Variable-Speed Centrifugal Pump With a Pipeline

2016 ◽  
Author(s):  
Cristian F. Jaimes Saavedra ◽  
Sebastian Roa Prada ◽  
Jessica G. Maradey Lázaro
Keyword(s):  
Mathematical Model ◽  
Control System ◽  
Flow Control ◽  
Flow Rate ◽  
Power Efficiency ◽  
Control Valve ◽  
Operating Point ◽  
Variable Frequency ◽  
Centrifugal Pumps ◽  
Variable Frequency Drive

Pumping processes often require different operating conditions for the same pipeline. The conditions downstream in the pipeline can change in such a way that the pressure at the discharge of the pump may vary, which automatically introduces changes in the flow supplied by the pump into the pipeline due to the head vs flow characteristic curve of the pump. Even under varying pipeline pressure conditions, it may be necessary to keep the flow discharge of the pump constant. The two most commonly used control strategies for flow control with centrifugal pumps are by means of a fixed-speed pump and a control valve at the outlet of the pump, or by means of a variable frequency drive which avoids the need for the control valve. It has been demonstrated that the approach with the fixed-speed pump and the control valve provides poor power efficiency results, so a variable frequency drive is normally the solution of choice in industry applications. The use of a variable frequency drive allows reaching the flow required by the system without changing the physical characteristic of the pump or pipeline, i.e., it is not necessary to shut the system down to replace the impeller of the pump. However, affinity laws of centrifugal pumps dictate that a change in the rotational speed of the impeller shifts the characteristic curves of the pump, not only the flow vs head curve, but also the efficiency curves, among others. Besides, searching for a different operating point by changing the speed of the pump does not necessarily guarantees optimal operating power efficiency. This paper proposes an optimization approach where a compromise is made between flow control and power efficiency by minimizing the error in the flow rate while at the same time maximizing the power efficiency. To accomplish this goal, this paper presents the modeling of the pump and pipeline, and the design of a linear quadratic regulator control for the fluid flow passing through a given pipeline. The fluid under consideration is water. The mathematical model of the overall system is derived by considering the model of an AC motor, the pump and the hydraulic circuit. Then, with the help of the software MATLAB, the controller was designed and implemented with the linearized mathematical model. The actuator of the control system is the variable frequency drive that changes the speed of the impeller to adjust the flow rate to the required operating point under different loading conditions. The results show the behavior of the compensated system with the optimal controller. In practice, the control system must take into account the constraints of the control effort, which means, the frequency of the pump must be kept within safe values to achieve proper functioning of the pumping system.

A New Fuzzy Inference Method for Symbolic Stability Analysis of Multigranular Intelligent Control System

2000 ◽  
Vol 12 (6) ◽  
pp. 664-674
Author(s):  
Hidehiro Yamamoto ◽  
◽  
Takeshi Furuhashi
Keyword(s):  
Control System ◽  
Stability Analysis ◽  
Fuzzy Control ◽  
Control Systems ◽  
Fuzzy Inference ◽  
Continuous System ◽  
Asymptotically Stable ◽  
Membership Functions ◽  
Symbolic System ◽  
Inference Method

Fuzzy inference has a multigranular architecture consisting of symbols and continuous values, and has worked well to incorporate experts' know-how into fuzzy controls. Stability analysis of fuzzy control systems is one of the main topics of fuzzy control. A recently proposed stability analysis method on the symbolic level opened the door to the design of stable fuzzy controller using symbols. However the validity of the stability analysis in the symbolic system is not guaranteed in the continuous system. To guarantee this validity, a nonseparate condition has been introduced. If the fuzzy control system is asymptotically stable in the symbolic system and the system satisfies the nonseparate condition, the continuous system is also asymptotically stable. However this condition is too conservative. The new condition called a relaxed nonseparate condition has been proposed and the class of control systems with guaranteed discretization has been expanded. However the relaxed condition has been applicable only to controf systems having symmetric membership functions. This paper presents a new fuzzy inference method that makes the relaxed condition applicable to fuzzy control systems with asymmetric membership functions. Simulations are done to demonstrate the effectiveness of the new fuzzy inference method. The proof of the expansion of the relaxed nonseparate condition is also given.

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