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Register a new userDesign of State Feedback Controller to Control of the inverted pendulum
تصميم متحكم التغذية العكسية للتحكم بحركة النواس العكوس
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Authors
أحمد الشيحاوي( باحث )
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تم في هذا البحث تصميم متحكم تناسبي تكاملي تفاضلي كلاسيكي (PID controller) و تصميم متحكم تغذية عكسية (State Feedback Controller) للتحكم بحركة النواس العكوس و اجراء عملية المقارنة بين جميع الحالات و اختيار المتحكم الأنسب باستخدام برنامج MATLAB/SIMULINK.
In this research a proportional integral differential classic (PID controller) and state feedback controller was designed to control the in the inverted pendulum and a comparison between all the cases and choose the most suitable controller using MATLAB / SIMULINK program
References used
P. E. Wellstead, 2000 -Introduction to Physical System Modelling, ACADEMIC PRESS LTD, 24/28 Oval Road London NW1, 256p
GREGORY L. BAKER, JAMES A. BLACKBURN, 2005- The Pendulum A Case Study in Physics, Oxford University Press Inc., New York
José Luis Corona Miranda 2009, APPLICATION OF KALMAN FILTERING AND PID CONTROL FOR DIRECT INVERTED PENDULUM CONTROL, California State University, Chico
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This work presents the details of the construction of the temperature
control system in the center. We used the Atmega8 microcontroller
which has high performance speed and suitable memory.
As we enter the age of artificial intelligence, the need for intelligent home appliances has become very important for what this smart equipment can provide in the provision of electrical energy and water resources that are treasures should human pre
servation, in addition to the contribution of this equipment to protect the environment from pollution, where we face the challenges next:
High prices of electrical equipment.
The number of hours of electricity supply in many areas is low
because of the current conditions in our country.
- Water shortage.
- The rise in prices of materials used in daily life in general and
household detergents in particular
- Great waste of electricity.
- Pollution of the environment and groundwater with detergents used in the laundry process.
Moreover, the unjust economic blockade imposed on our country is pushing us to work to produce low-cost national housing equipment that competes with foreign products in order to alleviate the material burden on the citizens and promote the national economy.
In order to accomplish this smart washing machine, we have written a code for f type-2 fuzzy microcontroller, using the Python programming language. This controller has received four entries, which are: The first income (clothing color), obtained by taking a picture of the clothes that we need to wash by a camera with a resolution of 8 megapixels, analyzed using OpenCV library, and the second income (clothing type), determined by the local binary pattern algorithm, which is common digital image processing algorithm that widely used to identify shapes that follow specific pattern and structure, the third income (degree of dirt), and was identified by taking a picture of the clothes after soaking them with water for two minutes. The image was then analyzed by the OpenCV library and the fourth (washing weight) that getting From the Load Cell, which measures the physical weights. The readings were converted to digital values via the HX711 digital analogue converter and then sent to Arduino UNO to determine the weight. The weight values were eventually sent to the Raspberry PI for use in the controller. The system generates three exits: washing time (the length of time the laundry was washed), the temperature required for washing, and the amount of detergent required.
After selecting all the previous values, we transferred to control Wattar washing machine model 402, where the water valve was controlled to allow the water to pass into the powder box and from it to the washing basin. The water heater was controlled, which heated the water to the temperature determined by the Fuzzy algorithm, The temperature was monitored by the DS18B20 temperature sensor, which gives a signal to the Raspberry PI at the arrival of the temperature to the required value, and the washing machine engine is controlled for a third of the time specified in the Fuzzy algorithm and we controlled the pump Water to empty basin Washing from water, the process repeated for three consecutive times, we control using a software interface designed using TKinter library
We have been able to design a smart Fuzzy logic type-2 controller with the following advantages:
o save electricity consumption o Provide quantity of detergents o Shortenwashingtime
We have been able to control the following physical components within the washing machine:
o Control the water pump
o control Water valve
o controlMotor
o controlTemperaturesensor o controlLCDscreen
We have built a smart washing machine with the following characteristics:
o Have the ability to recognize the condition of clothes o Identify the type of clothing
o Identify the color of clothes
o Dothewashingwithoutusingapredefinedprogram.
The controller we designed gives good results to calculate the following:
o Washingtime
o Quantity of detergents o Temperature
All diagrams appear in the case of the incremental gradient with an increased degree of dirt and as values correspond to each type of clothing.
Keywords: smart washing machine, saving electricity, saving detergent, shortening washing time, color and clothing distinction, artificial intelligence, fuzzy logic type-2, Raspberry PI, control, Python programming language, HX711.
This paper shows how to design and implement control circuit in the movement of
pv board to reach to maximal possible output, by designing a system to integrate several
methods of of control with each other. During this work, we will design through
formation
a unified system combine control by light sensors, and control via data base on the other
hand. In addition to compare pv angle in both ways. The proposed circuit designed,
conduct a simulation, and implementation a miniature model simulates reality, and
discussed the result to to conflict the advantage and the goal of using the proposed system.
All that by using micro controller (PIC).
The nonlinear model of Unmanned Aerial Vehicle( UAV) has been
recognized. Airosim Matlab toolbox has been used to guarantee a
simulation model for the Aerosonde.In the first stage, a
linearization technique is used to calculate the mathematical
m
odel of the UAV at a specific operation point, then PID controller
is used to stabilize this linear model. At the final stage, an
augmented feedback neural network adaptive controller is
applied to stabilize the overall nonlinear system.
In our research,
we propose technique to become LQR controller able to drive
(Micro Aerial Vehicle by Change Center of Gravity(MAV COG))
robot on a specific trajectory. We add a matrix to adjust the
trajectory that we want to trace it. We use Mat
lab program to
execute our controller.
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