• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.3
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• pp.525-531
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• 2001

The paper demonstrates that RBF(Radial Basis Function) networks can be used effective for the identification of inverted pendulum system. With the parallel arrangement of the RBF networks controller and PD controller, some characteristics were compared through simulation performance.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.93-95
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• 2005

When a control system is designed computer simulations are important because they provide a way to test the performances of the control law and determine some design parameters of the control system. Since most real situations are different from those of the simulations, however, it is required to manage uncertainties of the plant and analyze errors fast and correctly. For this we consider a convenient monitoring system which can display real systems responses exactly and check the performances of the control systems. In this paper, an approach to design a monitoring system is presented by using C++Builder program which is based on PC. Firstly we introduce the structure and functions of the monitoring system. Then, an inverted-pendulum control system is investigated by using the monitoring system.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.499-502
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• 1996

In this paper, we propose a fuzzy iterative learning controller(FILC). It can control fully unknown dynamic plants through iterative learning. To design learning controllers based on the steepest descent method, it is one of the difficult problems to identify the change of plant output with respect to the change of control input(.part.e/.part.u). To solve this problem, we propose a method as follows: first, calculate .part.e/.part.u using a similarity measure and information in consecutive time steps, then adjust the fuzzy logic controller(FLC) using the sign of .part.e/.part..u. As learning process is iterated, the value of .part.e/.part.u is reinforced. Proposed FILC has the simple architecture compared with previous other controllers. Computer simulations for an inverted pendulum system were conducted to verify the performance of the proposed FILC.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2350-2355
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• 2005

In this paper, we introduce biped walking robot which can static walking with 22 degree-of-freedoms. The developed biped walking robot is 480mm tall and 2500g, and 22 RC servo motors are used to actuate. Before made an active algorithm, we generated the motions of robot with the motion simulator which developed using by C language. The two dimension simulator is Based on the inverse kinematics and D-H transform. The simulator implements various motions as inputted the ankle's trajectory. Also we developed a simulator which is applied the principle of inverted pendulum to acquires the center of gravity. As we use this simulator, we can get the best appropriate angle of ankle and pelvis when the robot lifts up its one side leg during the working. We implement the walking motions which is based on the data(angle) getting from both of simulators. The robot can be controlled by text shaped command through RF signal of wireless modem which connected with laptop computer by serial cable.

• Journal of Industrial Technology
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• v.24 no.A
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• pp.99-107
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• 2004

This paper considers reinforcement learning control with the self-organizing map. Reinforcement learning uses the observable states of objective system and signals from interaction of the system and the environments as input data. For fast learning in neural network training, it is necessary to reduce learning data. In this paper, we use the self-organizing map to parition the observable states. Partitioning states reduces the number of learning data which is used for training neural networks. And neural dynamic programming design method is used for the controller. For evaluating the designed reinforcement learning controller, an inverted pendulum of the cart system is simulated. The designed controller is composed of serial connection of self-organizing map and two Multi-layer Feed-Forward Neural Networks.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.416-419
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• 2001

In this paper a new approach to estimate scaling factors of fuzzy controllers such as the fuzzy PID controller and the fuzzy PD controller is presented. The performance of the fuzzy controller is sensitive to the variety of scaling factors[1]. The desist procedure dwells on the use of evolutionary computing(a genetic algorithm) and estimation algorithm for dynamic systems (the inverted pendulum). The tuning of the scaling factors of the fuzzy controller is essential to the entire optimization process. And then we estimate scaling factors of the fuzzy controller by means of two types of estimation algorithms such as Neuro-Fuzzy model, and regression polynomial [7]. This method can be applied to the nonlinear system as the inverted pendulum. Numerical studies are presented and a detailed comparative analysis is also included.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.519-521
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• 1999

An adaptive fuzzy controller is constructed from a set of fuzzy IF-THEN rules whose parameters are adjusted on-line according to some adaptation law for the purpose of controlling the plant to track a given trajectory. Adaptive fuzzy controller of this paper is designed based on the Lyapunov synthesis approach The adaptive fuzzy controller is designed through the following steps: first, construct an initial controller based on linguistic descriptions(in the form of fuzzy IF-THEN rules) about the unknown plant from human experts; then, develop an adaptation law to adjust the parameters of the fuzzy controller on-line, the adaptive fuzzy controllers are used to control the inverted pendulum to track a given trajectory.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2227-2229
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• 2004

Fault Detection and Isolation(FDI) schemes using unknown input functional observers with very low order are presented. These schemes resolve the major practical difficulties with all FDI systems employing multiple observers for residual generation and can be implemented by the use of microprocessors that are normally used in commercial processes mainly due to the simplicity of the residual generation block. Various design objectives including detection, isolation, estimation and compensation of instrument fault/or process fault are achievable with these schemes. The proposed FDI scheme is applied to an inverted pendulum control system for instrument fault detection.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.681-686
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• 1991

In this paper, a novel self-organizing fuzzy plus PID control algorithm is proposed and analyzed by extensive computer simulations and experiments with an inverted pendulum. Specifically, the proposed self-organizing fuzzy controller consists of a typical fuzzy reasoning part and self organizing part in which both on-line and off-line algorithms are employed to modify the 'then' part of the fuzzy rules and to decide how much fuzzy rules are to be modified after evaluating the control performance, respecfively. And the fuzzy controller is replaced by a PID controller in a prespecified region near by the set point for good settling actions.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.9
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• pp.834-838
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• 2013

This paper proposes a new ball robot which has a four axis structure and four motors that directly actuate the ball to move or to maintain the balance of the robot. For the Balancing control, it is possible to use non-model-based controller to control simply without complex formula. All the gains of the controller are heuristically adjusted during the experiments. The tilt angle is measured by IMU sensors, which is used to generate the control input of the roll and pitch controller to make the tilt angle zero. The performance of the designed control system has been verified through the real experiments with the developed ball robot.