Fuzzy Logic Algorithm of Projectile Electromechanical Actuator Control System

2021 ◽  
Author(s):  
Hongqiao Yin ◽  
Wenjun Yi ◽  
Cuicui Li ◽  
Kangjian Wang ◽  
Jun Guan
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Electromechanical Actuator ◽  
Fuzzy Logic Algorithm ◽  
Actuator Control

Electromechanical Actuator Control System Development Using Rapid Prototyping Method

2013 ◽  
Vol 397-400 ◽  
pp. 1258-1262
Author(s):  
Jia Bao Zhang
Keyword(s):  
Control System ◽  
Rapid Prototyping ◽  
System Development ◽  
Circuit Board ◽  
Electromechanical Actuator ◽  
Loop Control ◽  
Development Method ◽  
Development Platform ◽  
Loop Control System ◽  
Actuator Control

In order to rapidly develop the control system of the Electromechanical Actuator (EMA), the DSP development platform is established using rapid prototyping method based on the MATLAB software, and all the models is configured and researched. First, the DSP development platform structure in the environment of MATLAB is mainly presented. And the operation principle has been showed. Then, the EMA control circuit board schematic diagram is necessarily introduced, which one is for the developer to conveniently configure the system model. Finally, the developer reasonably configures the control system models used in the Simulink library and constitutes them to speed closed loop control system of the EMA. The EMA control system code will be compiled and debugged rapidly through this platform. The executed program will automatically download into the DSP processor. And the result of debugging would be sent to the CAN bus receiver. For generally speaking, the difficulty of EMA control system code development method is reduced and the development cycle is shortened using this rapid prototyping method. And this system development method is fast and effective.

scholarly journals Enhanced IoT-Based Climate Control for Oyster Mushroom Cultivation Using Fuzzy Logic Approach and NodeMCU Microcontroller

2021 ◽  
Vol 29 (4) ◽  
Author(s):  
Muhammad Azizi Mohd Ariffin ◽  
Muhammad Izzad Ramli ◽  
Zarina Zainol ◽  
Mohd Nazrul Mohd Amin ◽  
Marina Ismail ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Mushroom Cultivation ◽  
Urban Farming ◽  
Climate Control ◽  
Fuzzy Logic Algorithm ◽  
Temperature And Humidity ◽  
Food Shortages ◽  
Fuzzy Logic Approach ◽  
Input Variables

Urban farming has the potential to utilise unused space in the community to alleviate food shortages and increase the community’s income through local food production. When Internet of Things (IoT) technology is integrated with urban farming, it can further improve its efficiencies and yield. The work in this paper improved our previous work of using an IoT-based climate control system to regulate the cultivation environment of oyster mushrooms automatically. Even though the climate control system could produce two batches of mushroom yields, there were several limitations, such as less efficient climate control due to threshold-based corrective action, water wastage, and system instability. This paper aims to address these stated limitations by implementing a fuzzy logic algorithm and redesigned the climate control system. Two crisp input variables from DHT22 sensors representing temperature and humidity were fed into the Node MCU microcontroller’s fuzzy logic coded in C language. The temperature and humidity conditions were divided into five fuzzy trapezoidal membership functions resulting in 25 fuzzy rules to control the duration of running the water pump and ventilation fan. An internal, lightweight web server were managed all HTTP client requests. The enhanced system also included a safety measurement to avoid overheating the microcontroller and causing water wastage. Upon analysis of the data captured in two months, the result showed a decrease of 40% in water utilisation and an increase of mushrooms yield up to 226%. The enhanced climate control system also facilitated maintaining and controlling the temperature and humidity conducive for optimal mushroom cultivation.

Design and Simulation of Smart Control System for Internet Traffic Distribution on Servers by Using Fuzzy Logic System

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Raid Daoud ◽  
Yaareb Al-Khashab
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Input Parameter ◽  
Traffic Density ◽  
The Internet ◽  
Linguistic Variables ◽  
Internet Service ◽  
Traffic Distribution ◽  
Smart Control ◽  
High Level

The internet service is provided by a given number of servers located in the main node of internet service provider (ISP). In some cases; the overload problem was occurred because a demand on a given website goes to very high level. In this paper, a fuzzy logic control (FLC) has proposed to distribute the load into the internet servers by a smart and flexible manner. Three effected parameters are tacked into account as input for FLC: link capacity which has three linguistic variables with Gaussian membership function (MF): (small, medium and big), traffic density with linguistic variables (low, normal and high) and channel latency with linguistic variables (empty, half and full); with one output which is the share server status (single, simple and share). The proposed work has been simulated by using MATLAB 2016a, by building a structure in the Fuzzy toolbox. The results were fixed by two manners: the graphical curves and the numerical tables, the surface response was smoothly changed and translates the well-fixed control system. The numerical results of the control system satisfy the idea of the smart rout for the incoming traffics from the users to internet servers. So, the response of the proposed system for the share of server ratio is 0.122, when the input parameter in the smallest levels; and the ratio is 0.879 when the input parameters are in highest level. The smart work and flexible use for the FLC is the main success solution for most of today systems control.

Sistem Kontrol Optimal Fuzzy-Particle Swarm Optimization

2018 ◽  
Vol 9 (1) ◽  
pp. 1-5
Author(s):  
Fachrudin Hunaini ◽  
Imam Robandi ◽  
Nyoman Sutantra
Keyword(s):  
Fuzzy Logic ◽  
Particle Swarm Optimization ◽  
Control System ◽  
Membership Function ◽  
Fuzzy Logic Control ◽  
Particle Swarm ◽  
Optimization Method ◽  
Swarm Optimization ◽  
Motion Error ◽  
Logic Control

Fuzzy Logic Control (FLC) is a reliable control system for controlling nonlinear systems, but to obtain optimal fuzzy logic control results, optimal Membership Function parameters are needed. Therefore in this paper Particle Swarm Optimization (PSO) is used as a fast and accurate optimization method to determine Membership Function parameters. The optimal control system simulation is carried out on the automatic steering system of the vehicle model and the results obtained are the vehicle's lateral motion error can be minimized so that the movement of the vehicle can always be maintained on the expected trajectory

The Condition for Absolute Stability of an Electroelastic Actuator Control System for Nanomechatronics

2020 ◽  
Vol 10 (10) ◽  
pp. 52-58
Author(s):  
Sergey M. AFONIN ◽  
Keyword(s):  
Control System ◽  
Adaptive Optics ◽  
Absolute Stability ◽  
Deformation Characteristic ◽  
Straight Line Segment ◽  
Control Mechanisms ◽  
Relative Width ◽  
Random Inputs ◽  
Deformation Control ◽  
Actuator Control

An electroelastic actuator for nanomechatronics is used in nanotechnology, adaptive optics, microsurgery, microelectronics, and biomedicine to actuate or control mechanisms, systems based on the electroelastic effect, and to convert electrical signals into mechanical displacements and forces. In nanomechatronic systems, a piezoactuator is used in scanning microscopy, laser systems, in astronomy for precision alignment, for compensation of temperature, gravitational deformations and atmospheric turbulence, focusing, and stabilizing the image. In this study, a condition for absolute stability of an electroelastic actuator control system for nanomechatronics under deterministic and random inputs is obtained. A number of equilibrium positions in an electroelastic actuator mechatronic control system are found, the totality of which is represented by a straight line segment. The electroelastic actuator’s deformation control system dead band relative width is determined for the actuator’s symmetric and asymmetric hysteresis characteristics. Under deterministic inputs and with fulfilling the condition for the derivative of the nonlinear hysteresis actuator deformation characteristic, the set of equilibrium positions of the electroelastic actuator control system for nanomechatronics is absolutely stable. Under random inputs, the system absolute stability with respect to the mathematical expectations of the electroelastic actuator mechatronic control system equilibrium positions has been determined subject to fulfilling the condition on the derivative of the actuator hysteresis characteristic.

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