• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.970-972
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• 1998

In this paper, the standard Dole, Glover, Khargoneker, and Francis (abbr. : DGKF 1989) $H_{\infty}$ controller $(H_{\infty}C)$ is extended to the nonlinear feedback linearization-$H_{\infty}$ /sliding mode controller (NFL-$H_{\infty}$/SMC) to solve the problem associated with the full state feedback for the unmeasurable state variables in the conventional SMC, to obtain the smooth control as the linearized controller for a linear system (or to cancel the nonlinearity for the nonlinear system), and to improve the time-domain performance under worst case.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.564-566
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• 1998

A robot manipulator is a nonlinear time varying MIMO system. Therefore, when a robot manipulator operates at high speeds, the performance of pursuing its trace becomes worse due to the increased nonlinearity of system. Several nonlinear control methods are introduced for solving this problem. But, these methods need a large amount of calculations, so it is necessary to use the controller equipped with a faster and more efficient processing ability. In this paper, we designed the Rhino XR-3 Robot Controller which controls five joints concurrently. To reduce the size of the controller and to control 6 dc-servo motors in real time, we use the TMS320c31, the high-speed digital signal processor.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.6
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• pp.62-70
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• 2008

An adaptive fuzzy backstepping controller is proposed for the motion control for a single-link flexible-joint robot in the presence of parametric uncertainties. Fuzzy logic system is used to approximate the uncertainties of functions and a backstepping technique is employed to deal with the mismatched problem. A compensation controller is also employed to estimates the bound of approximation error so that the shattering effect of the control effort can be reduced. Thus the asymptotic stability of the closed loop control system can be obtained based on a Lyapunov synthesis approach. Numerical simulation results for a single-link flexible-joint robot are included to show the effectiveness of proposed controller.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.1
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• pp.138-144
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• 2000

Robot manipulators, which are nonlinear structures and have uncertain system parameters, have complex in dynamics when are operated in unknown environment. To compensate for estimate errors of the uncertain system parameters and to accomplish the desired trajectory tracking, nonlinear robust controllers are appropriate. However, when estimation errors or tracking errors are large, they require large input torques, which may not be satisfied due to torque limits of actuators. As a result, their stability can not be guaranteed. In this paper, a new robust control scheme is presented to solve stability problem and to achieve fast trajectory tracking in the presence of torque limits. By using fuzzy logic, new desired trajectories which can be reduced are generated based on the initial desired trajectory, and torques of the robust controller are regulated to not exceed torque limits. Numerical examples are shown to validate the proposed controller using an uncertain two degree-of-freedom underwater robot manipulator.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.12
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• pp.655-660
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• 2004

This paper deals with the design of a fixed-structure $H_\infty$ power system stabilizer (PSS) by using an iterative linear matrix inequality (LMI) method. The fixed-structure $H_\infty$ controller is represented in terms of LMIs with a rank condition. To solve the non-convex rank-constrained LMI problem, a linear penalty function is incorporated into the objective function so that minimizing the penalized objective function subject to LMIs amounts to a convex optimization problem. With an increasing sequence of the penalty parameter, the solution of the penalized optimization problem moves towards the feasible region of the original non-convex problem. The proposed algorithm is, therefore, convergent. Numerical experiments show the practical applicability of the proposed algorithm.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.12
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• pp.1152-1160
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• 2007

In this paper we deal with a design of integral sliding mode controller to reject the disturbance force acting on the suspension system in the magnetically levitated system which is propelled by the linear induction motor. The control scheme comprises an integral controller which is designed for achieving zero steady-state error under step disturbances, and a sliding mode controller which is designed for enhancing robustness under plant uncertainties. A proper continuous design signal is introduced to overcome the chattering problem. The disturbance force produced by the linear motor is formularized by using a curve fitting of the experimental raw data. Computer simulations show the effectiveness of the designed integral sliding mode controller to reject the disturbance force.

• Journal of Advanced Navigation Technology
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• v.22 no.4
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• pp.325-335
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• 2018

Limited access to state information in the design of a feedback controller has brought out a significant amount of research on the design of an output feedback controller. Despite its long endeavor to find an optimal one, it is still an open problem. Thus, we focus on the comparison of existing states of arts in the design of a static output feedback controller in terms of stability and complexity so as to find further research direction in this field. To this end, we present eight design methods in a unified presentation. We also provide the complete description of algorithms which can be applicable to any system configuration. Stability performance and complexity in terms of processing time are evaluated through numerical simulations. Simulation results show that the algebraic controller (AC) algorithm [20] has the smallest complexity while the scaling linear matrix inequality (SLMI) algorithm [18] seems to achieve the best stability in most cases with much higher complexity.

• Journal of the Korean Society of Mechanical Technology
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• v.20 no.6
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• pp.809-817
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• 2018

The model predictive controller performance of the mobile robot is set to an arbitrary value because it is difficult to select an accurate value with respect to the controller parameter. The general model predictive control uses a quadratic cost function to minimize the difference between the reference tracking error and the predicted trajectory error of the actual robot. In this study, we construct a predictive controller by transforming it into a quadratic programming problem considering velocity and acceleration constraints. The control parameters of the predictive controller, which determines the control performance of the mobile robot, are used a simple weighting matrix Q, R without the reference model matrix $A_r$ by applying a quadratic cost function from which the reference tracking error vector is removed. Therefore, we designed the predictive controller 1 and 2 of the mobile robot considering the constraints, and optimized the controller parameters of the predictive controller using a genetic algorithm with excellent optimization capability.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2589-2592
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• 2003

In this paper, a robust mixed H$_2$/H$\_$$\infty$/ output feedback control method is applied to the design of loop filter for PLL carrier phase tracking. The proposed method successfully copes with large S-curve slope uncertainty and a significant decision delay in the closed-loop that may exist In modern receivers due to a convolutional decoder or an equalizer. The objective is to design an output feedback controller which minimizes the H$_2$performance while satisfying the H$\_$$\infty$/ performance to guarantee the gain margin and phase margin for linear time invariant(LTI) polytopic uncertain systems. LMIs based approach is given to solve this problem. We can verify the H$\_$$\infty$/ performance satisfaction and minimize the phase detector error through the simulation result.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.981-986
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• 1988

A controller synthesis procedure for precise tracking of reference inputs in the sense of spheres is applied to a 3 d.o.f. robotic manipulator. This methodology applies to a class of nonlinear systems with input uncertainty and parameter uncertainty. The 3 d.o.f. manipulator to be controlled is subjected to varying payloads and is required to follow specified joint trajectories to within prespecified tolerances. The design procedure above lends itself naturally to this type of control problem. The appeal of such a design procedure lies on a special decomposition which exploits linear control theory on the one hand and facilitates a separate treatment of the effects of nonlinearities and the uncertainties on the other.