scholarly journals Perancangan Balancing Robot Beroda Dua Dengan Metode Pengendali PID Berbasis Arduino Nano

2020 ◽  
Vol 2 (2) ◽  
pp. 39-43
Author(s):  
Marfanri Lamatenggo ◽  
Ifan Wiranto ◽  
Wrastawa Ridwan
Keyword(s):  
Control System ◽  
Pid Control ◽  
Pid Controller ◽  
Inverted Pendulum ◽  
Control Method ◽  
Proportional Integral ◽  
The Earth ◽  
Balancing Robot ◽  
Robot Body

Balancing robot adalah  robot beroda dua dengan badan robot diasumsikan sebagai pendulum terbalik. Sistem ini tidak stabil karena ketika kereta beroda diberi gangguan dari luar maka pendulum akan jatuh. Untuk mempertahankan agar tidak jatuh maka posisi pendulum harus dipertahankan seimbang. Oleh karena dibutuhkan suatu sistem kendali yang berfungsi untuk mempertahankan posisi pemdulum. Permasalahan yang ada disini adalah bagaimana membuat robot tetap stabil tegak lurus dengan permukaan bumi. Pada penelitian ini ditawarkan metode kendali PID (Proporsional, Integral dan Derivatif) berbasis Arduino Nano. Dalam pembuatan Balancing robot menggunakan sensor GY-521 MPU-6050 Module untuk mendeteksi kemiringan robot, dengan penggerak robotnya menggunakan motor DC 6V 620 RPM  gearbox 25ga370. Hasil yang didapat dari penelitian ini adalah Balancing robot dapat menyeimbangkan diri pada ACC Ydan ACC Z. Pengendali PID ditanamkan pada mikrokontroler Arduino nano dengan nilai Kp =  60, Ki = 2.0 dan Kd = 130. Kata Kunci— Balancing robot, kendali PID, Arduino nano.Balancing robot is a two-wheels robot with a robot body assumed to be an inverted pendulum. This system is unstable because when the robot is disturbed from outside the pendulum will fall. To keep from falling, the position of the pendulum must be keep in balance. Therefore we need a control system that functions to keep the position of the pemdulum. The problem here is how to make the robot remain stable perpendicular to the surface of the earth. In this study, the PID (Proportional, Integral and Derivative) PID control method based on  Arduino Nano. To build the balancing robot, it uses a GY-521 MPU-6050 module sensor to detect the tilt of the robot, with the robot drive using a DC 6V 620 RPM gearbox 25ga370 motor. The results obtained from this research is the balancing robot can balance itself on Axis Y 220 and Axis Z -40. The PID controller is implanted in Arduino nano with values Kp = 60, Ki = 2.0 and Kd = 130.Keywords — Balancing robot, PID controller, Arduino nano.

PID Control Based Missile Sub-Channel Simulation

2012 ◽  
Vol 433-440 ◽  
pp. 7011-7016 ◽  
Author(s):  
Chao Bo Chen ◽  
Bing Liu ◽  
Ning He ◽  
Song Gao ◽  
Quan Pan
Keyword(s):  
Control System ◽  
Real Time ◽  
Flight Control ◽  
Pid Control ◽  
Pid Controller ◽  
Channel Model ◽  
Control Method ◽  
Flight Control System ◽  
Aerodynamic Control ◽  
The Stability

The accuracy and real-time of modern missile flight control system of traditional aerodynamic can not be satisfied. In this paper a new method is presented to improve the accuracy and real-time of missiles under this condition. First of all, a missile sub-channel model of the dynamic equations and steering gear is established, then based on the established model, using PID controller to control steering gear and three channels of missile pitch, yaw, roll respectively which is called missile sub-channel PID control method, and finally making use of MATLAB/Simulink to complete the simulation. Simulation results show that compared with traditional aerodynamic control system, this method can reduce the response time of aerodynamic missile and enhance the stability of the control system obviously.

Fuzzy Immune PID Control for 6-DOF Parallel Platform

2011 ◽  
Vol 128-129 ◽  
pp. 890-893
Author(s):  
De Quan Zhu ◽  
Wen Hua Xie ◽  
Lei Sun
Keyword(s):  
Control System ◽  
Pid Control ◽  
Pid Controller ◽  
Control Method ◽  
Feedback Mechanism ◽  
Least Square ◽  
Control Precision ◽  
On Line ◽  
Parallel Platform ◽  
Six Degree Of Freedom

To improve the control precision of six degree-of-freedom parallel platform, a fuzzy immune PID control method was presented based on the immune feedback mechanism and fuzzy control theory, and the parameters of PID controller was optimized with hybrid algorithm. First, least square algorithm was used for off-line optimization to form immune feedback control system. Then, genetic algorithm was used for on-line optimization to get the optimal performance parameters of immune PID control system and the optimal fuzzy proportional parameters. Simulation results demonstrated that the control method designed gets tracking effect with high precision and speed.

scholarly journals Balancing Robot Menggunakan Metode Kendali Proporsional Integral Derivatif

2015 ◽  
Vol 5 (1) ◽  
pp. 89
Author(s):  
Rizka Bimarta ◽  
Agfianto Eko Putra ◽  
Andi Dharmawan
Keyword(s):  
Pid Control ◽  
Inverted Pendulum ◽  
Control Method ◽  
Angular Acceleration ◽  
Set Point ◽  
Tuning Method ◽  
Dc Motors ◽  
Complementary Filter ◽  
Proportional Integral Derivative Control ◽  
Balancing Robot

AbstrakPendulum terbalik memiliki pusat gravitasi yang berada diatas poros putar sehingga menyebabkan pendulum terbalik tidak seimbang. Suatu kendali khusus dibutuhkan agar pendulum seimbang dengan cara menggerakkan kereta beroda yang menjadi tumpuan dari pendulum. Penerapan pendulum terbalik dapat ditemui pada balancing robot. Tujuan dari penelitian ini adalah merancang bangun sebuah sistem pengendalian robot dengan dua roda menggunakan sistem kendali untuk membuat robot yang seimbang (balancing robot).            Sistem ini mempunyai masukan akselerometer yang digunakan untuk mengukur percepatan sudut (m/s2) dan giroskop untuk mengukur kecepatan sudut (rad/s). Luaran dari akselerometer dan giroskop digabungkan dengan metode complementary filter untuk mendapatkan nilai sudut. Sudut yang diperoleh kemudian dibandingkan dengan set point yang nilainya 0o. Nilai selisih dari set point dan sudut complementary filter diolah menggunakan metode kendali Proporsional Integral Derivatif. Proses kendali PID ini diprogram pada Arduino IDE yang hasilnya diumpankan ke motor DC untuk mengatur kecepatan putar motor DC. Untuk arah putar motor DC ditentukan apabila sudut complementary filter kurang dari nol, maka motor akan berputar mundur. Sedangkan jika sudut complementary filter lebih dari nol, maka motor akan berputar maju.            Nilai konstanta PID berdasarkan hasil tuning  dengan metode Ziegler-Nichols metode osilasi adalah Kp=1.5, Ki=0.75, Kd=1.85 dan nilai koefisien pada algoritma complementary filter adalah a=0.96. Kata kunci—inverted pendulum, balancing robot, kendali PID, IMU, complementary filter Abstract            Center of gravity’s inverted pendulum is located above its pivot point therefore inverted pendulum is unstable. Specific control is needed so that inverted pendulum stable which is by move the cart where the pendulum is mounted. Inverted pendulum application can be found in balancing robot. The purpose of this research is to design a system to control a two wheeled robot using the control system to balance it.The inputs are accelerometer to measure angular acceleration (m/s2) and gyroskop to measure angular velocity (rad/s). The output’s of accelerometer and gyroscope are fused by complementary filter algorithm method to get the actual angle. The actual angle is then compared to set point which is 0o. The differences between set point and actual angle are processed using Proportional Integral Derivative control method. The process of PID control is programmed using Arduino IDE which its result is fed to DC motors. The direction of DC motors are determined by two conditions, if actual angle less than zero then DC motors will spin backwards. Whereas if actual angle more than zero then DC motors will spin forward.             The PID control’s constans value based on Ziegler-Nichols Oscillation tuning method are Kp=1.5, Ki=0.75, Kd=1.875 and complementary filter’s coefficient is a=0.96. Keywords— inverted pendulum, balancing robot, PID control, IMU, complementary filter

scholarly journals Design of the LADRC control system for gravimetric stabilisation platforms

2021 ◽  
Vol 2113 (1) ◽  
pp. 012018
Author(s):  
Enfan Lin ◽  
Jiangning Xu ◽  
Miao Wu ◽  
Hongyang He
Keyword(s):  
Adaptive Control ◽  
Control System ◽  
Pid Control ◽  
Pid Controller ◽  
Control Algorithm ◽  
Simulation Experiment ◽  
Control Method ◽  
Control System Design ◽  
Adaptive Control System ◽  
Platform System

Abstract Aiming at the problems of strong non-linearity of gravimeter stabilisation platform system, poor robustness of linear PID control algorithm and non-adaptive control system. This paper designs a LADRC-based gravimetric stabilisation platform control system design and method based on the research of PID controller and ADRC control method, and gives the anti-saturation and anti-noise design applicable to it, and the simulation experiment shows that the method is feasible.

Adaptive Fuzzy Immune PID Control for Multi-Joint Robots

2011 ◽  
Vol 58-60 ◽  
pp. 1914-1919
Author(s):  
De Quan Zhu ◽  
Cheng Mao Cao ◽  
Lei Sun ◽  
Mei Zhu
Keyword(s):  
Control System ◽  
Pid Control ◽  
Pid Controller ◽  
Control Method ◽  
Robot Manipulator ◽  
Feedback Mechanism ◽  
Least Square ◽  
Adaptive Fuzzy ◽  
Control Precision ◽  
On Line

To improve the control precision of multi-joint robots, a adaptive fuzzy immune PID control method for multi-joint robots was presented based on the immune feedback mechanism and fuzzy control theory, and the parameters of PID controller was optimized with hybrid algorithm. First, least square algorithm was used for off-line optimization to form immune feedback control system. Then, genetic algorithm was used for on-line optimization to get the optimal performance parameters of immune PID control system and the optimal fuzzy proportional parameters. Simulation results of a 2-joint robot manipulator demonstrated that the control method designed gets tracking effect with high precision and speed.

scholarly journals An Improved PID Controller for the Compliant Constant-Force Actuator Based on BP Neural Network and Smith Predictor

2021 ◽  
Vol 11 (6) ◽  
pp. 2685
Author(s):  
Guojin Pei ◽  
Ming Yu ◽  
Yaohui Xu ◽  
Cui Ma ◽  
Houhu Lai ◽  
...  
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Pid Control ◽  
Pid Controller ◽  
Experimental Validation ◽  
Control Method ◽  
Smith Predictor ◽  
Constant Force ◽  
Matlab Simulation ◽  
Adjustment Time

A compliant constant-force actuator based on the cylinder is an important tool for the contact operation of robots. Due to the nonlinearity and time delay of the pneumatic system, the traditional proportional–integral–derivative (PID) method for constant force control does not work so well. In this paper, an improved PID control method combining a backpropagation (BP) neural network and the Smith predictor is proposed. Through MATLAB simulation and experimental validation, the results show that the proposed method can shorten the maximum overshoot and the adjustment time compared with traditional the PID method.

Intelligent Information of TS Fuzzy PID Control System of BLDCM

2013 ◽  
Vol 846-847 ◽  
pp. 313-316 ◽  
Author(s):  
Xiao Yun Zhang
Keyword(s):  
Control System ◽  
Dynamic Model ◽  
Pid Control ◽  
Control Method ◽  
Design Method ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Control Precision ◽  
Simulation Results ◽  
Intelligent Information

This paper presented a new method based on the Fuzzy self - adaptive PID for BLDCM. This method overcomes some defects of the traditional PID control. Such as lower control precision and worse anti - jamming performance. It dynamic model of BLDCM was built, and then design method for TS fuzzy PID model is given, At last, it compared simulation results of PID control method with TS Fuzzy PID control method. The results show that the TS Fuzzy PID control method has more excellent dynamic antistatic performances, as well as anti-jamming performance. The experiment shows that TS fuzzy PID control has the stronger adaptability robustness and transplant.

Simulation Analysis of Electro-Pneumatic Proportional Fuzzy-PID Control System Based on AMESim/Simulink

2014 ◽  
Vol 945-949 ◽  
pp. 2568-2572
Author(s):  
Si Yuan Wang ◽  
Guang Sheng Ren ◽  
Pan Nie
Keyword(s):  
Control System ◽  
Pid Control ◽  
Pid Controller ◽  
Simulation Analysis ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Proportional Control ◽  
Fuzzy Pid Controller ◽  
Design Requirements ◽  
Set Up

The test rig for hydro-pneumatic converter used in straddle type monorail vehicles was researched, and its electro-pneumatic proportional control system was set up and simulated based on AMESim/Simulink. Compared fuzzy-PID (Proportion Integral Derivative) controller with PID controller through fuzzy logic tool box in Simulink, the results indicate that, this electro-pneumatic proportional control system can meet design requirements better, and fuzzy-PID controller has higher accuracy and stability than PID controller.

Modelling and PID Control of a Quadrotor Aerial Robot

2014 ◽  
Vol 903 ◽  
pp. 327-331 ◽  
Author(s):  
Ismail Mohd Khairuddin ◽  
Anwar P.P.A. Majeed ◽  
Ann Lim ◽  
Jessnor Arif M. Jizat ◽  
Abdul Aziz Jaafar
Keyword(s):  
Pid Control ◽  
Pitch Angle ◽  
Pid Controller ◽  
Pd Controller ◽  
Proportional Integral Derivative ◽  
Hovering Flight ◽  
Proportional Integral ◽  
Aircraft Model ◽  
Aerial Robot ◽  
Aerial Vehicle

This paper elucidates the modeling of a + quadrotor configuration aerial vehicle and the design of its attitude and altitude controllers. The aircraft model consists of four fixed pitch angle propeller, each driven by an electric DC motor. The hovering flight of the quadrotor is governed by the Newton-Euler formulation. The attitude and altitude controls of the aircraft were regulated using heuristically tuned (Proportional-Integral-Derivative) PID controller. It was numerically simulated via Simulink that a PID controller was sufficient to bring the aircraft to the required altitude whereas the attitude of the vehicle is adequately controlled by a PD controller.

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