• Proceedings of the KSME Conference
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• 2007.05a
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• pp.1115-1119
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• 2007

Five control methods (Speed Control, PID Gain Scheduling, Loop Time Control, Simple PID, Switching Control) have been applied to the control of an Inline Co-axial valve by the simulation of AMESim. The simulation results have shown that the speed control method is the most stable and the fastest way to reach to the set point in the simulation of the flow control. Moreover, It has been found that the five control methods have the almost same characteristics in the power consumption, the counter electromotive force, and the motor angular velocity. According to the analysis results, the fast and stable control characteristics of the speed control method is the most suitable for the flow control using a inline co-axial valve with a DC(BLCD) motor.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.5
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• pp.1-8
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• 2013

This paper implements an integrated vehicle chassis system of ACC(Adaptive Cruise Control) and LKS(Lane Keeping System) based on OSEK OS to vehicle operating system and analyzes its performance through experiments. In recent years active safety and advanced driver assistance system has discussed to improve safety of vehicle. Among the rest, We integrate ACC that controls longitudinal velocity of vehicle and LKS that assists a vehicle in maintaing its driving lane, then implement integrated control system in vehicle. Implemented control system uses OSEK/VDX proposed standard, which is aiming at reusability and safety of software for vehicle and removal hardware dependence of application software. Redesigned control system based on OSEK OS, which is supported by OSEK/VDX, can manage real-time task, process interrupt and manage shared resource. We show by results performed EILS(ECU-In-the-Loop Simulation) that OSEK OS-based integrated controller of ACC and LKS is equivalent conventional integrated controller of ACC and LKS.

• The Journal of Korea Robotics Society
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• v.2 no.2
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• pp.109-118
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• 2007

The thruster is the crucial factor of an underwater vehicle system, because it is the lowest layer in the control loop of the system. In this paper, we propose an accurate and practical thrust modeling for underwater vehicles which considers the effects of ambient flow velocity and angle. In this model, the axial flow velocity of the thruster, which is non-measurable, is represented by ambient flow velocity and propeller shaft velocity. Hence, contrary to previous models, the proposed model is practical since it uses only measurable states. Next, the whole thrust map is divided into three states according to the state of ambient flow and propeller shaft velocity, and one of the borders of the states is defined as Critical Advance Ratio (CAR). This classification explains the physical phenomenon of conventional experimental thrust maps. In addition, the effect of the incoming angle of ambient flow is analyzed, and Critical Incoming Angle (CIA) is also defined to describe the thrust force states. The proposed model is evaluated by comparing experimental data with numerical model simulation data, and it accurately covers overall flow conditions within 2N force error. The comparison results show that the new model's matching performance is significantly better than conventional models'.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1051-1059
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• 2008

In the development process of an ECU (Electrical Control Unit), numerous tests are necessary to evaluate the performance and control algorithm. The vehicle based test is expensive and requires long time. Also, it is difficult to guarantee the safety of the test driver. To overcome the various problems faced in the development process, the ECU test has been done using HIL (Hardware In the Loop). The HIL environment has the actual hardware including an ECU and a virtual vehicle model. In this paper, the test platform environment is devloped for the AWS ECU black box test. The test platform is built on HIL (Hardware In the Loop) architecture. Using the developed test platform, the control algorithm of the AWS ECU can be evaluated under the virtual driving condition of the bi-modal tram. Driving conditions, such as a front steering angle and vehicle velocity, are defined through the PC (Personal Computer) input. Input signals are transformed to electrical signals in the PC. These signals become the input conditions of the AWS ECU. The AWS ECU is stimulated by arbitory input conditons, and responses of the system are observed.

• Journal of Navigation and Port Research
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• v.31 no.5 s.121
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• pp.325-332
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• 2007

This study develops a control algorithm on berthing/unberthing system using a joystick for ships with thrusters and a rudder. A nonlinear mathematical model for low speed maneuvering of typical container ships is used to develop a MIMO(multi-input multi-output) nonlinear control algorithm for velocity feedback joystick control. Also a virtual HILS(hardware in the loop simulation) software program for berthing/unberthing is developed to test the performance of the nonlinear and a PID control algorithm. The program is developed using LabWindow/CVI, and a user can see current position and desired trajectory of ship in a monitor, then he can control forward and yaw velocities of a ship using a joystick. The simulation results show that the nonlinear mfd the PID controller have superior performance over a simple open loop joystick control algorithm.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1027-1030
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• 1996

The purpose of this study was to develop systematic diagnostic system testing easily, rapidly vestibular function of patients suffered from vestibular syndrome such as nausea vomiting, dizzness, ataxia. Diagnostic system composed of rotatory chair system which rotated sinusoidally patients against their vertical axis for purpose of invoking eye movement by vestibulo-ocular reflex and the softwares which storaged eye movement into computer and analyzed eye movement. Rotatory chair system consisted of comfortable chair and DC servomotor with reducer(1:80) by controlled servo in field of nonlinear motor control, double feedback loops system containing velocity feedback loop and position feedback loop was applied to this sever controlled rotatory chair system. Maximum rotatory velocity of rotatory chair was upto 60 degree per second and frequency range was 0.01 to 0.64 Hz. These above results suggest that clinical rotatory chair system may test easily, rapidly vestibular function and diagnose etiology of dizziness, thus giving effective assistance on the treatment of dizziness patients.

• Transactions of The Korea Fluid Power Systems Society
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• v.5 no.4
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• pp.26-31
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• 2008

This paper deals with the issue of position tracking control of a clamp-cylinder for injection moulding machine with electric-hydrostatic drives. A fixed displacement pump is utilized in combination with AC motor in order to directly control a clamp-cylinder. A clamp-cylinder may be required to operate under a variety of operating conditions. Therefore, robust control performance is important in position tracking control applications. In order to accommodate mismatches between the real plant and the model used for controller design, discrete-time sliding mode control is developed by combining a velocity feedforward loop. From tracking control experiments, it is shown that significant reduction in position tracking error is achieved through the use of sliding mode control.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.340-343
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• 1992

Fundamental positioning characteristics of a dual-axis Sawyer linear motor are described. The Sawyer motor is capable of high positional accuracy. An electronic control unit of the motor whose velocity is proportional to the frequency of the electric current was produced in our laboratory. The positioning system was constructed using two Sawyer motors, an air bearings suspension unit and an electronic control unit. The stable motion of the motor was confirmed on the open loop operation. The adjustable operating conditions were the live load of 1 kg, the maximum acceleration of 1.2G and the maximum velocity of 350 mm/s. Absolute positioning accuracy was improved within .+-.5.mu.m, on microstep operating conditions of dividing one pitch of 508.mu.m into 508 steps. The following two conclusions were obtained. An accelerating-cruising-decelerating control is effective for reduction in the travel time required. Also, microstep operation is effective for improving the resolution of position.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1500-1505
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• 2004

This paper presents the design and control of a small Brushless DC (BLDC) Motor for entertainment robots. In order to control the developed BLDC motor, Adaptive Fuzzy Control (AFC) scheme via Parallel distributed Compensation(PDC) is developed for the multi- input/multi-output plant model represented by the Takagi-Sugeno(TS) model. The alternative AFC scheme is proposed to provide asymptotic tracking of a reference signal for the systems with uncertain or slowly time-varying parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop system. In addition, the plant state tracks the state of the reference model asymptotically with time for any bounded reference input signal. The suggested design technique is applied to the velocity control of a developed small BLDC motor for entertainment robots.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.1
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• pp.54-64
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• 1997

In this paper, a method of dynamic modeling and a dynamic control of a mobile robot are presented to show the superiority of the dynamic control comparing to the PD control. This dynamic model is derived from the cartesian coordinates using lagrange equations. Based upon the derived dynamic model, we implemented the dynamic control of the mobile robot using the computed torque method. Time varying non-linear friction terms are not incroporated in this dynamic model. Instead, those are considered as disturbances. This uncertainty in dynamic model of mobile robot is compensated by the outer loop controller using PD algorithm. The validity of this model and the control algorithm are confirmed through the experiments, where the dynamic control algorithm demonstrated robust velocity tracking performance against the unmodeled non-linear frictions. The superiority of this algorithm is demonstrated by comparing to classical PD control algorithm.