• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.2
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• pp.61-70
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• 2012

This paper describes terrain-adaptive attitude controller for a hybrid mobile platform which operates in wheel & track mode. The wheel mode of the hybrid mobile platform allows quick driving performance in the flatland, while the track mode provides adaptive movement in the rough ground or stairway. The switching of the platform between two modes is automatically controlled by attitude controller algorithm. In addition, in the track mode, the platform automatically adjusts its attitude angle to overcome the obstacles in front. This paper demonstrates the attitude controller for the aforementioned wheel-track hybrid mobile platform in order to overcome terrain obstacles by using an adaptive method. The driving performance of the hybrid mobile platform has been tested and verified in various surrounding environments in both wheel and track mode. Further, this paper presents the experiments by using the track structure of mobile platform on forming adaptive attitude under various types of obstacles. The practicability and effectiveness of the proposed attitude controller of the platform has been demonstrated in urban building and a test-bed.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1233-1236
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• 1996

Attitude Control System for a Hydrofoil type catamaran in wave is designed using a Decentralized Adaptive Control technique which is announced already by authors. This automatic attitude control system is designed for its good seaworthiness and for robustness on the variation of center of gravity. The performance is compared with a PID controller and the results show that the Decentralized Adaptive controller has better stability on the variation of the center of gravity.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.3
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• pp.240-245
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• 2010

The controller of a model reference adaptive control monitors the plant's inputs and outputs to acknowledge its characteristics. It then adapts itself to the characteristics it encounters instead of behaving in a fixed manner. An important part of every adaptive scheme is the adaptive law for estimating the unknown parameters on line. A more precise model is required to improve performance and to stabilize a given dynamic system, such as a satellite in which performance varies over time and the coefficients change due to disturbances, etc. After model identification, the robust controller ($H{\infty}$) is designed to stabilize the rigid body and flexible body of a satellite, which can be perturbed due to disturbance. The result obtained by the $H{\infty}$ controller is compared with that of the proportional and integration controller which is commonly used for stabilizing a satellite.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.12
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• pp.1226-1231
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• 2008

A design of attitude controller for a tiltrotor is presented augmenting L1 adaptive control, neural networks, and feedback linearization. The neural networks compensate for the modeling error caused by the lack of knowledge of tiltrotor dynamics while the L1 adaptive control allows high adaptation gains in adaptation laws thereby, satisfying tracking performance requirement. The efficacy of this control methodology is illustrated in high-fidelity nonlinear simulation of a tiltrotor by flying the tiltrotor in different flight modes from where the L1 adaptive controller with neural networks is originally designed for.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.6
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• pp.2421-2427
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• 2012

This paper is discussed the design on non-linear adaptive attitude controller for quadrotor UAV. Quadrotor UAV featured to have four rotor, required the special controller to compensate for the model parameter uncertainties as the unstable nonlinear system. In this research, we designed the adaptive controller to compensate for the payload changes even though it is changed with industrial applications. Especially, based on the mathematical model of UAV, non-linear adaptive controller is suggested and the stability is verified using the Lyapunov function and finally proved its performance and effectiveness of update laws with various payload by simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.3
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• pp.233-239
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• 2005

This paper presents the design and evaluation of a tiltrotor attitude controller. The implemented response type of the command augumentation system is Attitude Command Attitude Hold. The controller architecture can alleviate the need for extensive gain scheduling and thus has the potential to reduce development time. The control algorithm is constructed using the feedback linearization technique. And an on-line adaptive architecture that employs a neural network compensating the model inversion error caused by the deficiency of full knowledge tiltrotor aircraft dynamics is applied to augment the attitude control system. The use of Lyapunov stability analysis guarantees boundedness of the tracking error and network parameters. The performance of the controller is evaluated against ADS-33E criteria, using the nonlinear tiltrotor simulation code for Bell TR301 developed by KARI. (Korea Aerospace Research Institute)

• International Journal of Aeronautical and Space Sciences
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• v.14 no.2
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• pp.172-182
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• 2013

This paper focuses on the modeling and intelligent control of the new Eight-Rotor MAV, which is used to solve the problem of the low coefficient proportion between lift and gravity for the Quadrotor MAV. The Eight-Rotor MAV is a nonlinear plant, so that it is difficult to obtain stable control, due to uncertainties. The purpose of this paper is to propose a robust, stable attitude control strategy for the Eight-Rotor MAV, to accommodate system uncertainties, variations, and external disturbances. First, an interval type-II fuzzy neural network is employed to approximate the nonlinearity function and uncertainty functions in the dynamic model of the Eight-Rotor MAV. Then, the parameters of the interval type-II fuzzy neural network and gain of sliding mode control can be tuned on-line by adaptive laws based on the Lyapunov synthesis approach, and the Lyapunov stability theorem has been used to testify the asymptotic stability of the closed-loop system. The validity of the proposed control method has been verified in the Eight-Rotor MAV through real-time experiments. The experimental results show that the performance of the interval type-II fuzzy neural network based adaptive sliding mode controller could guarantee the Eight-Rotor MAV control system good performances under uncertainties, variations, and external disturbances. This controller is significantly improved, compared with the conventional adaptive sliding mode controller, and the type-I fuzzy neural network based sliding mode controller.

• Bulletin of the Korean Space Science Society
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• 2011.04a
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• pp.32.2-32.2
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• 2011

State dependent Riccati equation (SDRE) control technique has been widely used in the control society. Although it solves nonlinear optimal control problems, which minimizes state error and control efforts simultaneously, it has drawbacks when it is to be applied to the real time systems in that it requires much computational efforts. So the real time system whose computational ability is limited (for example, satellites) cannot afford to use SDRE controller. To solve this problem, a hybrid controller which is based on MSDRE (Modified SDRE) and ANFIS (Adaptive Neuro-Fuzzy Inference System) has been proposed by Abdelrahman et al. (2010). We propose a hybrid controller based on SDRE and ANFIS, and apply the hybrid controller to the hardware attitude simulator to perform a HIL (Hardware-In-the-Loop) simulation. Through HIL simulation, it is demonstrated that the hybrid controller satisfies the control requirement and the computation load is reduced significantly. In addition, the effects of statistical properties of the ANFIS training data to the performance of the ANFIS controller have been analyzed.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2120-2125
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• 2005

The principal idea of vibration isolation is to filter out the response of the system over the corner frequency. The isolation objectives are to transmit the attitude control torque within the bandwidth of the attitude control system and to filter all the high frequency components coming from vibration equipment above the bandwidth. However, when a reaction wheels or control momentum gyros control spacecraft attitude, vibration inevitably occurs and degrades the performance of sensitive devices. Therefore, vibration should be controlled or isolated for missions such as Earth observing, broadcasting and telecommunication between antenna and ground stations. For space applications, technicians designing controller have to consider a periodic vibration and disturbance to ensure system performance and robustness completing various missions. In general, past research isolating vibration commonly used 6 degree order freedom isolators such as Stewart and Mallock platforms. In this study, the vibration isolation device has 3 degree order freedom, one translational and two rotational motions. The origin of the coordinate is located at the center-of-gravity of the upper plane. In this paper, adaptive notch filter finds the disturbance frequency and the reference signal in filtered-x least mean square is generated by the notch frequency. The design parameters of the notch filter are updated continuously using recursive least square algorithm. Therefore, the adaptive filtered-x least mean square algorithm is applied to the vibration suppressing experiment without reference sensor. This paper shows the experimental results of an active vibration control using an adaptive filtered-x least mean squares algorithm.