• Journal of Institute of Control, Robotics and Systems
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• v.4 no.5
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• pp.636-643
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• 1998

This paper is presents multivariable control scheme for industrial robot manipulators. The control scheme consists of two loops. The modeling error between linearized robot model and actual robot model is compensated in error compensation loop. The PID control loop is designed for pole assignment to stability of robot system and utilized for trajectory tracking. Alternatively computer simulation results are given for illustration purpose of suggested controller.

• 한국신재생에너지학회:학술대회논문집
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• 2007.06a
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• pp.109-112
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• 2007

In this paper, a mathematical modeling was developed to simulate 1kW class air cooled Polymer Electrolyte Membrane Fuel Cell(PEMFC) system. The proposed modeling was conducted under SIMULINK based environment. The model ing was developed based on the thermodynamic and chemical equilibrium. The objective is to design and implement the entire fuel cell system model ing including the system controller modeling. The fuel cell process and the control system modeling should have to be connected with each other simultaneously， therefore the two types of modeling influences each other when the system simulator run. The fuel cell modeling libraries are simulated using the SIMULINK under the thermodynamic and chemical equilibrium base. The PID controller application was designed and developed to test the process modeling and verify it. This the prototype development of the fuel cell system to design and test more complicate fuel cell systems, like the residential power generation system. The simulation results was compared to the real PEMFC system performance. We have achieved the reasonable accordance with the Lab test and the simulation results.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.4_1
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• pp.513-519
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• 2022

In this paper, we describe performances of P-PD controllers in the quadrotor system with steady-state error compensation by adding a corrective term to the system input. A decentralized control system using P-PD controllers was successfully implemented on a quadrotor platform. We also presented the results of a mathematical modeling analysis for control the quadrotor and experimental results for each response performance according to the heading reference value in accordance with the mathematical modeling and P-PD controller design. A control experiment with the real system was implemented for the test platform, and the results were evaluated and compared.

• International Journal of Precision Engineering and Manufacturing
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• v.3 no.4
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• pp.78-86
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• 2002

In this paper, LMI (Linear Matrix Inequality) based on H$\_$$\infty$/ controller for a lire of sight (LOS) stabilization system. It shows that the proposed controller has more excellent stabilization performance than that of the conventional PI-Lead controller. An H$\_$$\infty$/ control has been also applied to the system for reducing modeling errors and the settling time of the system. The LMI-based H$\_$$\infty$/ controller design is more practical in view of reducing a run-time than Riccati-based H$\_$$\infty$/ controller. This H$\_$$\infty$/ controller is available not only to decrease the gain in PI-Lead control, but also to compensate the identifications for the various uncertain parameters. Therefore, this paper, shows that the proposed LMI-based H$\_$$\infty$/ controller had good disturbance attenuation and reference input tracking performance compared with the control performance of the conventional controller under any real disturbances.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.4
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• pp.279-285
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• 2007

The objective of the research is two fold. The first is to design and propose a stable and robust learning control algorithm. The controller is CMAC Learning Controller which consists of a model-based controller, such as LQR or PID, as a reference control and a CMAC. The second objective is to implement a reference control and CMAC at two different sampling rates. Generally, a conventional controller is designed based on a mathematical plant model. However, increasing complexity of the plant and accuracy requirement on mathematical models nearly prohibits the application of the conventional controller design approach. To avoid inherent complexity and unavoidable uncertainty in modeling, biology mimetic methods have been developed. One of such attempts is Cerebellar Model Articulation Computer(CMAC) developed by Albus. CMAC has two main disadvantages. The first disadvantage of CMAC is increasing memory requirement with increasing number of input variables and with increasing accuracy demand. The memory needs can be solved with cheap memories due to recent development of new memory technology. The second disadvantage is a demand for processing powers which could be an obstacle especially when CMAC should be implemented in real-time. To overcome the disadvantages of CMAC, we propose CMAC learning controller with multiple sampling rates. With this approach a conventional controller which is a reference to CMAC at high enough sampling rate but CMAC runs at the processor's unoccupied time. To show efficiency of the proposed method, an inverted pendulum controller is designed and implemented. We also demonstrate it's possibility as an industrial control solution and robustness against a modeling uncertainty.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.909-914
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• 1988

The structure of a digital controller based on modern control theory is more complex than that of a PID controller. In implementing the digital control of an actual system by using the digital controller, we often encounter gaps between theory and practice e.g. quantization error, sampling error, modeling error, contaminated noise etc. In such cases, simulator plays an important role in detecting difficulties. This paper demonstrates the importance of the computer simulator for designing a digital controller. The controller and the simulator are constructed by different computer respectively, with a link between the blocks by analogue signals through the A/D, D/A converters. Through the simulator test, we can evaluate the digital controller; identify and solve difficulties in the digital control. The controller, which pasted the simulator test, is used identically in the actual system. This was a successful procedure for designing the controller. As an example, we successfully constructed the digital controller using the computer simulator for inverted pendulum control. We then compared the control results of simulator and actual equipment. Furthermore we commented on the construction of the computer simulator which exactly expressed the actual system.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.161.4-161
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• 2001

This paper presents adaptive control of robot manipulator using neuro-fuzzy controller Fuzzy logic is control incorrect system without correct mathematical modeling. And, neural network has learning ability, error interpolation ability of information distributed data processing, robustness for distortion and adaptive ability. To reduce the number of fuzzy rules of the FLS(fuzzy logic system), we consider the properties of robot dynamic. In fuzzy logic, speciality and optimization of rule-base creation using learning ability of neural network. This paper presents control of robot manipulator using neuro-fuzzy controller. In proposed controller, fuzzy input is trajectory following error and trajectory following error differential ...

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.922-927
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• 1991

This study is aimed to investigate a design problem of the fuzzy logic controller for the activated sludge process(ASP) in sewage treatment. The modeling technique proposed by Sugeno is used to express the ASP effectively and identification of a fuzzy model of the ASP is carried out utilizing actual operational data obtained from a metropolitan sewage plants. The model-based fuzzy controller is designed by rules generated from the identified ASP fuzzy model. Feasibility of the designed controller is tested through computer simulations.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.777-780
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• 1999

In this paper, a fuzzy logic controller is designed for speed control of a hydraulic inverter elevator. Mathematical modeling of an elevator actuated with hydraulic system is presented and the friction characteristics of a cylinder is examined, which may cause the abrupt increase of the acceleration in the zero-crossing speed region. Simulation results show that the proposed fuzzy logic speed controller yields a better control performance than conventional PID controller.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.173-173
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• 2000

This paper discusses a observer based discrete-time controller design and presents a modified control structure for dual-stage hard disk drive systems using piezoelectric microactuator(MA). In plant modeling, dynamic coupling between VCM and MA is not considered. Each controller is organized independently and designed using pole placement. Simulation result shows that 4th-order controller achieves about 3kHz servo bandwidth and 0.22msec of 2% settling time.