• International Journal of Aeronautical and Space Sciences
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• v.4 no.1
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• pp.75-87
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• 2003

The primary objective of this study is to demonstrate ground-based experiment for the attitude control of spacecraft. A two-axis rotational simulator with a flexible ann is constructed with on-off air thrusters as actuators. The simulator is also equipped with payload pointing capability by simultaneous thruster and DC servo motor actuation. The azimuth angle is controlled by on-off thruster command while the payload elevation angle is controlled by a servo-motor. A thruster modulation technique PWM(Pulse Width Modulation) employing a time-optimal switching function plus integral error control is proposed. An optical camera is used for the purpose of pointing as well as on-board rate sensor calibration. Attitude control performance based upon the new closed-loop control law is demonstrated by ground experiment. The modified switching function turns out to be effective with improved pointing performance under external disturbance. The rate sensor calibration technique by Kalman Filter algorithm led to reduction of attitude error caused by the bias in the rate sensor output.

• Journal of Advanced Navigation Technology
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• v.16 no.1
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• pp.1-7
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• 2012

In this research, a single-axis attitude control test bed is developed, and simulation and tests experiments are performed, as a preliminary research of a quad-rotor aerial vehicle development. A single-axis test bed with seesaw configuration is manufactured using two motors and propellers, and the aerodynamic parameters are derived by thrust tests. The response of the system is estimated with Matlab/Simulink, and experiments are performed with attitude control computer and an attitude sensor onboard the test bed. Comparing the results of simulated and tested data, factors of steady-state errors during experiments are found, and performances of used attitude control algorithm and the control computer were verified. In these process, essential preliminary data for attitude control of a quad-rotor unmanned aerial vehicle were acquired.

• Journal of Astronomy and Space Sciences
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• v.29 no.4
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• pp.389-395
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• 2012

The problem of spacecraft attitude control is solved using an adaptive neuro-fuzzy inference system (ANFIS). An ANFIS produces a control signal for one of the three axes of a spacecraft's body frame, so in total three ANFISs are constructed for 3-axis attitude control. The fuzzy inference system of the ANFIS is initialized using a subtractive clustering method. The ANFIS is trained by a hybrid learning algorithm using the data obtained from attitude control simulations using state-dependent Riccati equation controller. The training data set for each axis is composed of state errors for 3 axes (roll, pitch, and yaw) and a control signal for one of the 3 axes. The stability region of the ANFIS controller is estimated numerically based on Lyapunov stability theory using a numerical method to calculate Jacobian matrix. To measure the performance of the ANFIS controller, root mean square error and correlation factor are used as performance indicators. The performance is tested on two ANFIS controllers trained in different conditions. The test results show that the performance indicators are proper in the sense that the ANFIS controller with the larger stability region provides better performance according to the performance indicators.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.672-675
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• 1996

This paper presents algorithm including Kalman filter for transfer alignment of velocity and quaternion matching method, when master inertial navigation system is a gimbled type and slave inertial navigation system is a strapdown type on a cruising ship which is naturally in motion of horizontal axis attitude. And relative attitudes are considered on a measurement equation for quaternion matching between master INS and slave INS.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.6
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• pp.546-551
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• 2011

Tilt sensor is required to control the attitude of the biped robot when it walks on an uneven terrain. Vision sensor, which is used for recognizing human or detecting obstacles, can be used as a tilt angle sensor by comparing current image and reference image. However, vision sensor alone has a lot of technological limitations to control biped robot such as low sampling frequency and estimation time delay. In order to verify limitations of vision sensor, experimental setup of an inverted pendulum, which represents pitch motion of the walking or running robot, is used and it is proved that only vision sensor cannot control an inverted pendulum mainly because of the time delay. In this paper, to overcome limitations of vision sensor, Kalman filter for the multi-rate sensor fusion algorithm is applied with low-quality gyro sensor. It solves limitations of the vision sensor as well as eliminates drift of gyro sensor. Through the experiment of an inverted pendulum control, it is found that the tilt estimation performance of fusion sensor is greatly improved enough to control the attitude of an inverted pendulum.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.438-442
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• 1998

The helicopter system is non-linear and complex. Futhermore, because of absence of an accurate mathematical model, it is difficult accurately to control its attitude. But we can control the non-modeled system with the uncertainty and unstructure using the fuzzy control algorithm. Therefore, we apply optimized fuzzy controllers for the control of its elevation angle and azimuth one using expert's intuitions and knowledges. The simulation and experimental results of the hellicopter simulator CE150 with MATLAB shall be introduced.

• Journal of the Korean Society of Propulsion Engineers
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• v.16 no.6
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• pp.62-72
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• 2012

Divert and attitude control system(DACS) plays an important role for orbit transfer and attitude control, and therefore becomes important subject for recent space vehicle and Precision Guided Missile(PGM) development. To develop DACS system, main research areas include shape combination of pintle and nozzle to maximize thrust change, and reduction of aerodynamic pintle load to minimizle pintle driving force, and development of multi-axis control algorithm. In this paper, introduction, classification, and overseas/domestic research and development program, and prospects of DACS are reviewed and summarized.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.6
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• pp.547-552
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• 2015

In this paper, an ARS-EKF based motion counting algorithm for repetitive exercises such as calisthenics is proposed using a smartwatch. Raw sensor signals from accelerometers and gyroscopes are widely used for conventional smartwatch counting algorithms based on pattern recognition. However, generated features from raw data are not intuitive to reflect the movement of motions. The proposed motion counter algorithm is composed of navigation based feature generation and counting with error correction. The candidate features for each activity are velocity and attitude calculated through an ARS-EKF algorithm. In order to select those features which reveal the characteristics of each motion, an exercise frame from the initial sensor frame is introduced. Counting processes are basically based on the zero crossing method, and misdetected counts are eliminated via simple classification algorithms considering the frequency of the counted motions. Experimental results show that the proposed algorithm efficiently and accurately counts the number of exercises.

• The Journal of Korea Robotics Society
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• v.15 no.1
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• pp.32-38
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• 2020

This paper describes a method for tracking attitude and position of underwater robots. Underwater work with underwater robots is subject to differences in work efficiency depending on the skill of the operator and the utilization of additional sensors. Therefore, this study developed an underwater robot that can operate autonomously and maintain a certain attitude when working underwater to reduce difference of work efficiency. The developed underwater robot uses 8 thrusters to control 6 degrees of freedom motion, IMU (Inertial Measurement Unit), DVL (Doppler Velocity Log) and PS (Pressure Sensor) to measure attitude and position. In addition, the thruster allocation algorithm was designed to follow the control desired value using 8 thrusters, and the motion control experiments were performed in the engineering water basin using the thruster allocation method.

• International Journal of Aeronautical and Space Sciences
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• v.16 no.4
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• pp.581-589
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• 2015

This paper describes a monocular vision-based formation flight technology using two fixed wing unmanned aerial vehicles. To measuring relative position and attitude of a leader aircraft, a monocular camera installed in the front of the follower aircraft captures an image of the leader, and position and attitude are measured from the image using the KLT feature point tracker and POSIT algorithm. To verify the feasibility of this vision processing algorithm, a field test was performed using two light sports aircraft, and our experimental results show that the proposed monocular vision-based measurement algorithm is feasible. Performance verification for the proposed formation flight technology was carried out using the X-Plane flight simulator. The formation flight simulation system consists of two PCs playing the role of leader and follower. When the leader flies by the command of user, the follower aircraft tracks the leader by designed guidance and a PI control law, and all the information about leader was measured using monocular vision. This simulation shows that guidance using relative attitude information tracks the leader aircraft better than not using attitude information. This simulation shows absolute average errors for the relative position as follows: X-axis: 2.88 m, Y-axis: 2.09 m, and Z-axis: 0.44 m.