• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.91-99
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• 2003

When the driver suddenly depresses the brake pedal under critical conditions, the desired trajectory of the vehicle can be changed. In this study, the vehicle dynamics and fuzzy logic controller are used to control the vehicle trajectory. The dynamic vehicle model consists of the engine, the rotational wheel, chassis, tires and brakes. The engine model is derived from the engine experimental data. The engine torque makes the wheel rotate and generates the angular velocity and acceleration of the wheel. The dynamic equation of the vehicle model is derived from the top-view vehicle model using Newton's second law. The Pacejka tire model formulated from the experimental data is used. The fuzzy logic controller is developed to compensate for the trajectory error of the vehicle. This fuzzy logic controller individually acts on the front right, front left, rear right and rear left brakes and regulates each brake torque. The fuzzy logic controlling each brake works to compensate for the trajectory error on the split - $\mu$ road conditions follows the desired trajectory.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.12
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• pp.1184-1194
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• 2010

The descent and ascent phases for a lunar lander are composed of several phases. Accordingly, the constraints and control values adequate for each phase are required in order to generate optimal lander's trajectory. The optimal trajectories for descent and ascent phases are generated by the cost function to minimize fuel consumption & attitude variation rates. In this paper, the optimal control problem to make trajectory uses Gauss pseudo-spectral method which is one of the direct approach method. This problem generates lander's reference trajectory, states and controls.

• Journal of the Korean Society of Propulsion Engineers
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• v.25 no.1
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• pp.29-41
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• 2021

The PID controller with fin angle and thrust as control input was designed based on the aerodynamic data of scramjet system. Flight simulation following a given trajectory which strike the target point after climb and cruise with constant dynamic pressure was conducted. After that, the required thrust for the climb and cruise was calculated and the required fuel flow rate for the hydrogen fuel dual mode scramjet combustor was analyzed. The combustor analysis of this study which conducted on integrated model of independently developed inlet, combustor, nozzles and external aerodynamic models, laying the foundation for the integrated design of the air breathing hypersonic system.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.10
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• pp.842-850
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• 2014

This paper presents a trajectory tracking controller for rotorcraft UAVs to improve the tracking performances in the presence of various uncertainties. The proposed tracking method consists of a velocity guidance law based on the relative distance and L1 adaptive augmentation loop for tracking the velocity commands. In the proposed structure, the desired velocity generated by the guidance law is the reference value of the adaptive controller for accurate path tracking. In the guidance law, the desired acceleration is generated based on the relative distance and its derivatives, and then the velocity command of the inner control loop is calculated by integrating the accelerations. $L_1$ augmentation loop supplements the linear controller to guarantee the flight performances such as a tracking accuracy in the presence of the uncertainties. The proposed controller was validated in actual flight tests to successfully demonstrate its capability using a quadrotor UAV.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.5
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• pp.582-590
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• 2007

Nonlinear adaptive control of overhead cranes is investigated for anti-sway trajectory tracking with high-speed hoisting motion. The sway dynamics of two dimensional underactuated overhead cranes is heavily coupled with the trolley acceleration, hoisting rope length, and the hoisting velocity which is an obstacle in the design of decoupling control based anti-sway trajectory tracking control law To cope with this obstacle. we propose a fuzzy nonlinear adaptive anti-sway trajectory tracking control law guaranteeing the uniform ultimate boundedness of the sway dynamics even in the presence of uncertainties in such a way that it cancels the effect of the trolley acceleration and hoisting velocity on the sway dynamics. In particular. system uncertainties, including system parameter uncertainty unmodelled dynamics, and external disturbances, are compensated in an adaptive manner by utilizing fuzzy uncertainty observers. Accordingly, the ultimate bound of the tracking errors and the sway angle decrease to zero when the fuzzy approximation errors decrease to zero. Finally, numerical simulations are performed to confirm the effectiveness of the proposed scheme.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.1
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• pp.29-34
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• 2013

This study presents the remote control of a mobile robot using iPhone based on ad hoc communication. Two control interfaces are proposed to control a mobile robot using iPhone : Remote control by a user and autonomous control. To evaluate the effectiveness of algorithms for trajectory following, a simulator are developed where a virtual robot follows a referenced trajectory in a monitor by iPhone interface. In the proposed simulator, some algorithms are tested how they work well or not for trajectory following of a mobile robot. Comparative results by remote user control and autonomous control are shown. Results of an experiment show that the proposed simulator can be effectively used for testing the effectiveness of autonomous tracking algorithms.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.3
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• pp.9-15
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• 1998

This paper presents an adaptive learning control method for unknown nonlinear systems by combining neuro control and iterative learning control techniques. In the present control system, an iterative learning controller (ILC) is used for a process of short term memory involved in a temporary adaptive and learning manipulation and a short term storage of a specific temporary action. The learning gain of the iterative learning law is estimated by using a neural network for an unknown system except relative degrees. The control informations obtained by ILC are transferred to a long term memory-based feedforward neuro controller (FNC) and accumulated in it in addition to the previously stored infonnations. This scheme is applied to a two link robot manipulator through simulations.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.3
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• pp.50-57
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• 2003

In the paper, the design and evaluation of a helicopter trajectory tracking controller are presented. The control algorithm is implemented using the feedback linearization technique and the two time-scale separation architecture. In addition, and on-line adaptive architecture that employs a neural network compensating the model inversion error caused by the deficiency of full knowledge of helicopter dynamic is applied to augment the attitude control system. Trajectory tracking performance of the control system in evaluated using modified TMAN simulation program representing as Apache helicopter. It is show that the on-line neural network in an adaptive control architecture is very effective in dealing with the performance depreciation problem of the trajectory tracking control caused by insufficient information of dynamics.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.2
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• pp.19-25
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• 2003

For a class of multi-input multi-output nonlinear systems which perform a given task repetitively, an extended type of a direct leaning control (DLC) is proposed using the information on the (vector) relative degree of a multi-input multi-output system. Existing DLC methods are observed to be applied to a limited class of systems with the relative degree one and a new DLC law is suggested which can be applied to systems having higher relative degree. Using the proposed control law, the control input corresponding to the new desired output trajectory is synthesized directly based on the control inputs obtained from the learning process for other output trajectories. To show the validity and the performance of the proposed DLC, simulations are performed for trajectory tracking control of a two-axis SCARA robot.

• Journal of Drive and Control
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• v.17 no.2
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• pp.45-54
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• 2020

The IMV is a combination of four two-way valve systems which replace a conventional four-way spool valve to improve efficiency mostly in excavator hydraulics. As the environmental regulations for construction equipment have tightened, some overseas advanced companies have released commercial excavators in which the MCV is implemented with the IMVs. Development of the IMV type MCV relies on the control algorithm as well as the robust performance of proportional flow control valves. In this study, the IMV controller was designed and verified with experiments for the excavator working unit, which determines the IMV mode of operation and the extent of the valve opening in consideration of the load conditions on hydraulic actuators. First, the open-loop controller was designed with a joystick command vs. a PSV reference current map comprising several control parameters in to compensate for the different flow characteristics and non-linearities of two-way flow control valves. Second, the closed-loop controller was designed with the PI control fed by the actuator displacement and outputs actuator percent effort equivalent to the operator's joystick command. Finally, the performance of the IMV type MCV was verified with the trajectory control of position references derived from the energy consumption test standard. Experimental results showed the control performance of the IMV developed in this study, and suggest that future studies to be conducted to advance technical progress.