scholarly journals Sistem Kendali PID pada Modus Transisi Terbang Tiltrotor

2015 ◽  
Vol 5 (2) ◽  
pp. 199 ◽  
Author(s):  
Syafrizal Akhzan ◽  
Andi Dharmawan
Keyword(s):  
Control System ◽  
Standard Deviation ◽  
Negative Feedback ◽  
Pitch Angle ◽  
Roll Angle ◽  
Transition Mode ◽  
Brushless Motor ◽  
Full Speed ◽  
Yaw Angle ◽  
Average Angle

AbstrakTiltrotor merupakan jenis pesawat tanpa awak yang dapat lepas landas secara vertikal dan terbang maju dengan kecepatan penuh. Kemampuan ini didukung dengan adanya aktuator yang dapat mengubah sudut baling-baling pada modus transisi. Tanpa adanya sistem kendali pada modus hovering dan transisi, akan menyebabkan tiltrotor sulit untuk dikendalikan. Penelitian ini bertujuan merancang dan membuat sistem yang mampu menstabilkan tiltrotor dengan mempertahankan sudut orientasi roll, pitch, dan yaw tiltrotor pada modus hovering dan transisi menggunakan pengendali PID.Pengendali PID menggunakan negative feedback yang berasal dari pembacaan sensor accelerometer, gyroscope, dan magnetometer dengan metode DMP dan Madgwick quaternion menghasilkan keluaran pulsa untuk mengendalikan kecepatan motor brushless dan posisi sudut motor servo. Hasil dari pengendali PID juga dibandingkan dengan pengendali P dan PI.Sesuai dengan pengujian, sistem kendali pada modus transisi pada sudut roll dengan setpoint 0o mampu mempertahankan posisi sudut roll pada sudut rata-rata 0.48o dengan standar deviasi 1.75o, pada sudut pitch dengan setpoint 25o mampu mempertahankan posisi sudut pitch pada sudut rata-rata 25.26o dengan standar deviasi 2.87o, pada sudut yaw mampu mempertahankan posisi sudut yaw pada rentang 10o hingga 0o dengan sudut rata-rata 3.78o dan standar deviasi 1.83o. Kata kunci—tiltrotor, PID, modus transisi Abstract Tiltrotor is an unmanned aerial vehicle which can take off vertically and fly with full speed. These abilities are supported by actuators, which can change the angle of propellers in transition mode. Without control system in hovering mode and transition mode, it will be difficult to control tiltrotor. The purpose of this research is to design the system which can stabilize the tiltrotor by maintaining oriented angle of tiltrotor’s roll, pitch, and yaw in hovering mode and transition mode using PID controller.PID controller uses negative feedback which is obtained from accelerometer, gyroscope, and magnetometer by using DMP method and Madgwick quaternion to produce the pulse to control the velocity of brushless motor and angle position of servo motor. The result of PID controller is also compared to P controller and PI controller.According to the test, control system in transition mode for roll angle with setpoint 0o is capable to maintain roll angle at average angle 0.48o with standard deviation 1.75o, for pitch angle with setpoint 25o is capable to maintain pitch angle at average angle 25.26o with standard deviation 2.87o, for yaw angle is capable to maintain yaw angle at range 10o to 0o with average angle 3.78o and standard deviation 1.83o. Keywords—tiltrotor, PID, transition mode 

scholarly journals Cone Algorithm of Spinning Vehicles under Dynamic Coning Environment

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Shuang-biao Zhang ◽  
Xing-cheng Li ◽  
Zhong Su
Keyword(s):  
Pitch Angle ◽  
Euler Angle ◽  
Roll Angle ◽  
Angle Error ◽  
Attitude Error ◽  
Spinning Process ◽  
Cone Algorithm ◽  
Definition Of ◽  
Yaw Angle ◽  
The Relationship

Due to the fact that attitude error of vehicles has an intense trend of divergence when vehicles undergo worsening coning environment, in this paper, the model of dynamic coning environment is derived firstly. Then, through investigation of the effect on Euler attitude algorithm for the equivalency of traditional attitude algorithm, it is found that attitude error is actually the roll angle error including drifting error and oscillating error, which is induced directly by dynamic coning environment and further affects the pitch angle and yaw angle through transferring. Based on definition of the cone frame and cone attitude, a cone algorithm is proposed by rotation relationship to calculate cone attitude, and the relationship between cone attitude and Euler attitude of spinning vehicle is established. Through numerical simulations with different conditions of dynamic coning environment, it is shown that the induced error of Euler attitude fluctuates by the variation of precession and nutation, especially by that of nutation, and the oscillating frequency of roll angle error is twice that of pitch angle error and yaw angle error. In addition, the rotation angle is more competent to describe the spinning process of vehicles under coning environment than Euler angle gamma, and the real pitch angle and yaw angle are calculated finally.

Method of Attitude Measurement Based on the Geomagnetic and Gyroscope

2013 ◽  
Vol 336-338 ◽  
pp. 180-184 ◽  
Author(s):  
Li Long ◽  
He Zhang
Keyword(s):  
Pitch Angle ◽  
Measurement Accuracy ◽  
Performance Test ◽  
Detection System ◽  
Roll Angle ◽  
Angle Error ◽  
Blind Area ◽  
Trajectory Correction ◽  
Yaw Angle ◽  
Attitude Detection

The trajectory correction capability of the Simple guided munitions is directly affected by measurement accuracy of attitude angle. A gesture detection method based on geomagnetic gyro combination is proposed in this paper in order to detect the projectile flight attitude, The yaw angle of the projectile is solved by using runge-kutta algorithm with angle information of MEMS gyro. Then roll angle and pitch angle of the projectile is solved by magnetic field component of the three-axis magnetic sensor. Finally, the whole attitude detection system is installed in three-axis non-magnetic turntable to have a performance test. Experimental results show that the attitude solution results error is small. Nearby blind area, the roll angle error reduced to 5° and the pitch angle error reduced to 4°. In other locations, the roll angle error reduced to 2° and the pitch angle error reduce to 1°. The measurement accuracy increased nearly tenfold, can satisfy the trajectory correction demand of simple guidance ammunition.

scholarly journals Attitude Measurement of Special Aircraft Based on Geomagnetic and Angular Velocity Sensors

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Zhang Pingan ◽  
Wang Wei ◽  
Gao Ming ◽  
Che Jinli
Keyword(s):  
Mathematical Model ◽  
Angular Velocity ◽  
Pitch Angle ◽  
Roll Angle ◽  
Trajectory Data ◽  
Angle Error ◽  
Attitude Test ◽  
Blind Area ◽  
Yaw Angle ◽  
The Mathematical Model

Aiming at the problem of attitude test of special aircraft in flight, the combined test technology of geomagnetic sensor and angular velocity sensor is studied. The mathematical model of special aircraft roll attitude test based on combined measurement is established. The error models of special aircraft roll angle based on yaw angle input and pitch angle input are derived, respectively, and based on the actual flight trajectory data of aircraft, the mathematical model of special aircraft roll attitude test is established The simulation results show that the roll angle error input by yaw angle is between -0.4° and 0.9°, while the roll angle error input by pitch angle is between -0.4° and 1.2°, which shows that the calculation accuracy of roll angle input by yaw angle is higher, and the existence of magnetic measurement blind area is verified. In this paper, the method of judging the blind area of geomagnetic survey and the algorithm model of eliminating the influence of blind area are proposed.

scholarly journals Penalaan Mandiri Full State Feedback dengan LQR dan JST Pada Kendali Quadrotor

2019 ◽  
Vol 9 (1) ◽  
pp. 21
Author(s):  
Faisal Fajri Rahani ◽  
Tri Kuntoro Priyambodo
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Pitch Angle ◽  
State Feedback ◽  
Roll Angle ◽  
Full State ◽  
Full State Feedback ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Yaw Angle

Quadrotor is one type of unmanned aerial vehicle that has the ability to vertical takeoff and landing. In this research, a system designed to stabilize quadrotor during flight condition by maintaining at angle of roll, pitch, yaw, and x, y, and z axis position using LQR full state feedback with artificial neural network (ANN).The LQR full state feedback method uses 12 states with each K constant being tuned with ANN. This research implements ANN method to change feedback constant at angle of roll, pitch, and yaw and x, y, and z axis. The artificial neural network method uses 12 input layers, 12 hidden layers, and 1 output layer.Testing with ANN improved the rise time to ± 2.18 seconds at the roll angle, ± 1.23 seconds at the pitch angle, and ± 0.31 seconds at the yaw angle. Improved settling time value up to ± 2.41 seconds at roll angle, ± 1.23 seconds at pitch angle, and ± 1.07 seconds at yaw angle. Improved steady state eror value of ± 0.61% at roll angle, ± 4.88% at pitch angle, and ± 0.82% at the yaw angle.

scholarly journals Sensitivity of a Hand-cranked Nursery Spreader to Operator Variables

1994 ◽  
Vol 12 (4) ◽  
pp. 187-190
Author(s):  
Richard L. Parish
Keyword(s):  
Distribution Pattern ◽  
Pitch Angle ◽  
Sensitivity Study ◽  
Roll Angle ◽  
Several Variables ◽  
The Right ◽  
Yaw Angle

Abstract Hand-cranked rotary spreaders are used to apply granular pesticides to container crops. Pattern was affected by several variables that are controlled by the operator. A sensitivity study was conducted with a typical hand-cranked spreader to determine which operator variables most affected the distribution pattern. Impeller height had little effect. Pattern slide setting had an important effect. Reducing cranking speed affected the pattern; increasing cranking speed did not. Roll angle affected pattern if the right side was angled down, but not if the left Side was angled down. Pitch angle affected the pattern only if the spreader was pitched down. Yaw angle had a major impact on pattern regardless of direction. Width of bed (i.e. distance between spreader passes) affected pattern uniformity.

scholarly journals Fuzzy Logic Controller Application for an Active Two-Axis Solar Tracking System

2020 ◽  
Vol 190 ◽  
pp. 00004
Author(s):  
Chairul Imron ◽  
Imam Abadi ◽  
Nurika Brillianti ◽  
Muhammad Khamim Asy’ari ◽  
Yusilawati Ahmad Nor ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Steady State ◽  
Solar Radiation ◽  
Pitch Angle ◽  
Fuzzy Logic Control ◽  
Tracking System ◽  
Logic Control ◽  
Solar Tracking ◽  
Yaw Angle

The changes in the intensity of solar radiation cause the electrical power produced by solar panels to be not optimal. The solar panel position control system to the position of the solar is an effort to overcome this problem. There are four Light Dependent Resistor (LDR) sensors placed on the sides of the four cardinal directions. The difference in the intensity of solar radiation received by each sensor causes the position of the solar panel to turn perpendicular to the position of the solar. The control method used is fuzzy logic control with three membership functions. The controlled variables are pitch angle and yaw angle in an active two-axis solar tracking system. Input fuzzy logic control is an error, and output is PWM. The results of the performance of the pitch angle control system produce settling time for 10 s and error steady-state obtained by 0.080 %, while for the yaw angle control system produces settling time for 13 s and steady-state error is obtained at 0.038 %. The existence of a control system resulted in an increase in the percentage of power above 30 % with a power difference of 7.49 W to a fixed panel.

scholarly journals A peduncle detection method of tomato for autonomous harvesting

2021 ◽  
Author(s):  
Jiacheng Rong ◽  
Guanglin Dai ◽  
Pengbo Wang
Keyword(s):  
Pose Estimation ◽  
Pitch Angle ◽  
Detection Method ◽  
Geometric Model ◽  
Average Error ◽  
Long Distance ◽  
End Effector ◽  
Key Points ◽  
Yaw Angle ◽  
Cutting Point

AbstractFor automating the harvesting of bunches of tomatoes in a greenhouse, the end-effector needs to reach the exact cutting point and adaptively adjust the pose of peduncles. In this paper, a method is proposed for peduncle cutting point localization and pose estimation. Images captured in real time at a fixed long-distance are detected using the YOLOv4-Tiny detector with a precision of 92.7% and a detection speed of 0.0091 s per frame, then the YOLACT +  + Network with mAP of 73.1 and a time speed of 0.109 s per frame is used to segment the close-up distance. The segmented peduncle mask is fitted to the curve using least squares and three key points on the curve are found. Finally, a geometric model is established to estimate the pose of the peduncle with an average error of 4.98° in yaw angle and 4.75° in pitch angle over the 30 sets of tests.

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