• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.5
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• pp.311-318
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• 1988

An adaptive control problem for a plant with unmodelled dynamics is studied. The upper bounds of the output due to the unmodelled dynamics and measurement noise is assumed to be known. This problem was studied by Middleton et al. They used a modified form of the least square method in estimating the plant paramaters. In this paper, the bounds of the parameters are estimated by linear programming and the parameters are estimated by the projetion type algorithm incorporating the bounds of the parameters. The stability of the proposed adaptive control system can be proved in nearly the same way as the proof of Middleton. The performance of the proposed method is found to be much better than the method of Midlleton's with respect to the parameter convergence and plant output in computer simulations.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.5
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• pp.319-326
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• 1988

In the presence of unmodeled dynamics, the robustness of adaptive pole assignment control using new pseudo-plant is presented. The pseudo-plant proposed by Donati et al. is modified as the gain of low pass filter can be set from zero to one. This modified pseudo-plant results in the reduction of modeling error. It is shown that not only this approach is insensitive to input frequency but also it improves the conic condition developed by Ortega et al. which is required to assure stability of adaptive control system despite the model-plant mismatch. A simple method to compensate the tracking error due to the use of pseudo-plant is considered.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1644-1645
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• 2007

This paper proposes an adaptive sliding mode control method for trajectory tracking of nonholonomic mobile robots with model uncertainties and external disturbances. The kinematic model represented by polar coordinates are considered to design a robust control system. Wavelet neural networks (WNNs) are employed to approximate arbitrary model uncertainties in dynamics of the mobile robot. From the Lyapunov stability theory, we derive tuning algorithms for all weights of WNNs and prove that all signals of an adaptive closed-loop system are uniformly ultimately bounded.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.5
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• pp.320-325
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• 2016

This paper presents a robust finite-time sliding mode control (SMC) scheme for unknown disturbance and unmodeled nonlinear friction and dynamics in the robotic manipulator. A finite-time SMC (FSMC) surface and finite-time sliding mode controller are constructed to obtain faster error convergence than the conventional infinite-time based SMC. By adding prescribed constraint control term to a finite-time SMC to compensate for unknown disturbance and uncertainties, a robust control scheme can be designed as well as faster convergence control. In addition, simpler controller structure is built by using feed-forwarding upper bound coefficients of each manipulator dynamic parameters instead of model-based control or adaptive observer to estimate unknown manipulator parameters. Simulation and experimental evaluations highlight the efficacy of the proposed control scheme for an articulated robotic manipulator.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.443-447
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• 2001

In this paper, a robust sensorless vector control system for induction motors with a speed estimator and an uncertainty observer is presented. At first, the proposed speed estimator is based on the MRAS(Mode Reference Adaptive System) scheme and constructed with a simple fuzzy logic(FL) approach. The structure of the proposed FL estimator is very simple. The input of the FL is the rotor flux error difference between reference and adjustable model, and the output is the estimated incremental rotor speed Secondly, the unmodeled uncertainties such as parametric uncertainties and external load disturbances are modeled by a radial basis function network(RBFN). In the overal speed control system, the control inputs are composed with a norminal control input and a compensated control input, which are from RBFN observer output and the modeling error of the RBFN, repectively. The compensated control input is derived from Lyapunov unction approach. The simulation results are presented to show the validity of the proposed system.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.5 s.305
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• pp.13-18
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• 2005

Over the last few years, the control of bipedal robot has been considered a promising but difficult research field in the community of robotics. In this paper, a new robust output control method for a bipedal robot is proposed using the adaptive fuzzy logic. The adaptive fuzzy logic is used as an system approximator to cancel the unknown uncertainty. First, a model for a bipedal robot including switching leg influence, uncertainty and disturbance is presented. Second, a controller is designed in which the joint velocity measurement is not required. Fuzzy approximation error estimator is inserted in the system for tuning the fuzzy logic. Finally, the result of the computer simulation is presented to show the validity of the suggested control method.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.4
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• pp.167-175
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• 2001

This paper presents design of active roll controller of a vehicle and experimental study using the electric actuating roll control system. Firstly, parameter sensitivity analysis is performed based on 3DOF linear vehicle model. The controller is designed in the frame work of gain-scheduled H$\infty$ control scheme considering the varying parameters induced by laden and running vehicle condition. In order to investigate a feasibility of an active control system, experimental work is performed using hardware-in-the -loop setup which has been constructed by the devised electric actuating system and the full vehicle model with tire characteristics. The performance is evaluated by experiment using hardware-in-the -loop simulation under the conditions of some steer maneuvers and parameter variations.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.350-353
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• 1994

This paper presents a method to calculate the characteristic root areas and loci band of control systems with uncertainties. First, equations of boundary curves of root areas in the case of additive and multiplicative perturbation are derived. Then, an algorithm for the calculation of the array of closed curves is presented. When the upper bound of the absolute values of frequency responses for the uncertain part, is also frequency-dependent, the frequency-dependent, terms are included in the characteristic equation of the nominal system. This lead to the boundary equations of the root, areas for control systems with frequency-dependent uncertainty. Numerical examples of the control systems with multiplicative perturbations including frequency-dependent terms are presented to verify this calculation method. Finally, its applications to the design of robust control systems, e.g., passive adaptive control systems are also discussed.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1981-1986
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• 2004

In this study, the basic motor control system had been investigated. The controller for this study consists of two main parts, a feedforward controller part and a feedback controller part. Each part will deals with different control problems. The feedback controller deals with robustness and stability, while the feedforward controller deals with response speed. The feedforward controller, used to solve the tracking control problem, is adaptable. To make such a tracking perfect, an adaptive law based on Feedback Error Learning (FEL) is designed so that the feedforward controller becomes an inverse system of the controlled plant. The novelty of FEL method lies in its use of feedback error as a teaching signal for learning the inverse model. The theory in $H^{\infty}$-Control is selected to be applied in the feedback part to guarantee the stability and solve the robust stabilization problems. The simulation of each individual part and the integrated one are taken to clarify the study.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2279-2284
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• 2005

Generally, biped walking is difficult to control because it is a nonlinear system with various uncertainties. In this paper, we design a robust control system based on sliding-mode control (SMC) of 5-link biped robot using the wavelet neural network(WNN), in order to improve the efficiency of position tracking performance of biped locomotion. In our control system, the WNN is utilized to estimate uncertain and nonlinear system parameters, where the weights of WNN are trained by adaptive laws that are induced from the Lyapunov stability theorem. Finally, the effectiveness of the proposed control system is verified by computer simulations.