• Journal of Institute of Control, Robotics and Systems
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• v.14 no.11
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• pp.1103-1109
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• 2008

Since the flexible joint robots with motor dynamics are represented by the fifth-order nonlinear sγstem, it is difficult and complex to design the controller for electrically driven flexible-joint (EDFJ) robots. In this paper, we propose a simple adaptive control method to solve this problem. It is assumed that the model uncertainties of the robots dynamics, joint flexibility, and motor dynamics are unknown. For the simple control design, the dynamic surface design method is applied, and all uncertainties in the robot and motor dynamics are compensated by using the adaptive function approximation technique. It is proved that all signals in the controlled closed-loop system are uniformly ultimately bounded. Simulation results for three-link EDFJ manipulators are provided to validate the effectiveness of the proposed control system.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.4
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• pp.371-379
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• 2006

Increasing requirements for the high quality of industrial robot performance made the vibration control issue very important because the vibration makes it difficult to achieve quick response of robot motion and may bring mechanical damage to the robot. This paper presents a vibration control solution for industrial robots which have flexible joints. The joint flexibility is modeled as a two-mass system. And we analyze the vibration problem of a classical P-PI controller when it used for the flexible joints of industrial robots. Then a state feedback controller is designed for vibration suppression of the two-mass system. Finally, a gain-scheduling method is designed for maintaining control performance in spite of the time-varying nature of each joint's load side inertia. Simulation and experimental results show effective vibration suppression and uniform properties in overshoot in spite of the variation of load. The result of this study can be applied to the appropriate gain manipulation of many other mechatronic devices which have the two-mass system with varying load side inertia.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.1
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• pp.108-118
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• 2017

In this paper, the path tracking controller for a surface vessel based on the sliding mode control (SMC) with the switching law is proposed. In order to have no restriction on movement and improved tracking performance, the proposed control system is developed as follows: First, the kinematic and dynamic models in Cartesian coordinates are considered to solve the singularity problem at the origin. Second, the new multiple sliding surfaces are designed with the SMC and approach angle concept to solve the under-actuated property. Third, the switching control system is designed to improve tracking performance. To prove the stability of the proposed switching system under the arbitrary switching, the Lyapunov stability analysis method with the common Lyapunov function is used. Finally, the computer simulations are performed to demonstrate the performance, effectiveness and stability of the proposed tracking controller of a surface vessel.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.2
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• pp.123-128
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• 2002

A fuzzy traffic controller with the control rules and the membership functions generated by using genetic algorithm is presented for crossroad management. Conventional fuzzy traffic controllers use control rules and membership functions generated by human operators. However, this approach does not guarantee the optimal solution to design fuzzy control system. Genetic algorithm is a good solution for an optimal problem requiring domain-specific knowledge that is often heuristic. In this paper, we use genetic algorithms to automatically determine the near optimal rules and their membership functions of fuzzy traffic controllers. The effectiveness of our method was shown through simulation of crossroad network.

• Proceedings of the KIEE Conference
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• 1992.07b
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• pp.1218-1220
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• 1992

This paper presents the three section sliding mode control algorithm based on variable structure current controller design in a synchronous frame and indirect field oriented control method, and applies it to the position control of induction motor. This control scheme solves the problem of robustness loss during the reaching phase that occurs in a conventional VSC strategy, and ensures the stable sliding mode and robustness enhancement throughout an entire response. As the performance of a VSI fed induction motor drives depends on the characteristics of inner loop current controller, it is desired that the current controller have the fast tracking and robust nature. Therefore, we introduced the voltage mapping table based on the concept of voltage space vector for variable structure current control, and implemented fully digital control system using 16-bit microcontroller with on-chip peripherals without additional processing circuits. Simulation and experimental results confirm the validity of this control scheme for robust AC servo drive system of VSI fed induction motor.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.2
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• pp.117-123
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• 2001

To improve control performance of a non-linear system, many other reserches have used the sliding model control algorithm. The sliding mode controller is known to be robust against nonlinear and unmodeled dynamic terms. However, this algorithm raises the inherent chattering caused by excessive switching inputs around the sliding surface. Therefore, in order to solve the chattering problem and improve control performance, this study has developed the sliding mode controller with a perturbation estimator using the observer-based fuzzy adaptive network. The perturbation estimator based on the fuzzy adaptive network generates the control input of compensating unmodeled dynamics terms and disturbance. And the weighting parameters of the fuzzy adaptive network are updated on-line by adaptive law in order to force the estimation errors converge to zero. Therefore, the combination of sliding mode control and fuzzy adaptive network gives rise to the robust and intelligent routine. For evaluation control performance of the proposed approach, tracking control simulation is carried is carried out for the hydraulic motion simulator which is a 6-degree of freedom parallel manipulator.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.3
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• pp.357-364
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• 2015

This research presents a DC-DC converter controller implemented with an analog memory. The structure of the converter will contribute to solve the stability problem unavoidable in a conventional closed loop converter. The analog memory will be used for realizing CAM(Contents Addressable Memory) which contains the output of the converter and the relevant duty ratio, respectively. The operation for reading in the memory is executed with an absolute differencing circuit and a WTA(Winner-Take-All) circuit suitable for a nearest-match function of the CAM. We also present a system architecture that enables highly-paralleled fast writing and quick readout as well as high integration density.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.36-41
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• 2012

This paper presents torque control of DC motor using the velocity profile based acceleration/deceleration controller for automatic guided vehicles (AGVs). This technique has some advantage; to reduce the damage of motors and to extend the life time of motors. First, we generate velocity profiles for three cases and design the state feedback controller using the generated velocity profile as a reference. The state feedback controller has servo system for solving regulation problem. For the verification, we apply the proposed method to control a cart position and shows some simulation result.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.10
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• pp.65-77
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• 2004

In this paper, we propose an adaptive mechanism based on immune algorithm and neural network identifier technique. It is also applied fur an autonomous guided vehicle (AGV) system. When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged due to the abrupt change of PID parameters since the parameters are almost adjusted randomly. To solve this problem, we use the neural network identifier (NNI) technique fur modeling the plant and humoral immune algorithm (HIA) which performs the parameter tuning of the considered model, respectively. After the PID parameters are determined in this off-line manner, these gains are then applied to the plant for the on-line control using an immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough initially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. Finally, the simulation and experimental result fur the control of steering and speed of AGV system illustrate the validity of the proposed control scheme. These results for the proposed method also show that it has better performance than other conventional controller design methods.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.2
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• pp.7-14
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• 2009

In this paper we consider the problem of global finite-time stabilization for a class of uncertain nonlinear systems which include uncertainties. The uncertainties are time-varying disturbances or parameters belong to a known compact set. The proposed design method is based on backstepping and dynamic exponent scaling using an augmented dynamics, from which, a dynamic smooth feedback controller is derived. The finite-time stability of the closed-loop system and boundedness of the controller are preyed by the finite-time Lyapunov stability theory and a new notion 'degree indicator'.