• Journal of the Korean Society for Precision Engineering
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• v.11 no.6
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• pp.20-27
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• 1994

This paper presents a controller design to coordinate a robot manipulator under unknown system parameters and bounded disturbance inputs. To control the motion of the manipulator, an inverse dynamics control scheme is applied. Since parameters of the robot manipulators such as mass and inertia are not perfectly known, the difference between the actual and estimated parameters works as a disturbance force. To identify the unknown parameters, an improved adaptive control algorithm is directly derived from a chosen Lyapunov's function candidate based on the Lyapunov's Second Method. A robust control algorithm is devised to counteract the bounded disturbance inputs such as contact forces and disturbing forces coming from the difference between the actual and the estimated system parameters. Numerical examples are shown using three degree-of-freedom planar arm.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.12
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• pp.967-972
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• 2001

In this paper, an adaptive robust nonlinear predictive controller is developed for the continuous time nonlinear systems whose control objective is composed of the system output and its desired value. The basic control law is derived from the continuous time prediction model and its feedback dynamcis shows another from if input and output linearization. In order to cope with the parameter uncertainty, robust control is incorporated into the basic control law and the asymptotic convergence of tracking error to a certain bounded region is guaranteed. For stability and performance improvement within the bounded region, an adaptive control is introduced. Simulation tests for the motion control of an underwater wall-ranging robot confirm the performance improvement and the robustness of this controller.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.3
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• pp.643-650
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• 2017

The control of flexible joint robot is getting more attentions because its applications are more frequently used for robot systems in these days. This paper proposes a robust impedance controller for the flexible joint robot by using integral sliding mode control and backstepping control. The sliding mode control decouple disturbances completely but requires matching condition for disturbances. The dynamic model of flexible joint robot is divided into motor side and link side and the disturbance of the link side does not satisfy matching condition and cannot be decoupled directly by the actual input in the motor side. To overcome this difficulty, backstepping control technique is used with sliding mode control. The mismatched disturbance in the link side is changed into matched one in the respect to virtual control input which is the state controlled by actual input in the motor side. Integral sliding mode control is used to preserve the impedance control performance and the improved robustness at the same time.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.10
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• pp.1047-1052
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• 2008

In this paper, we design an image-based robust controller to compensate uncertainties with image Jacobian and robot dynamics due to uncertain depth measurement and load variations. The proposed controller with eye-in-hand structure has separate terms to compensate each of uncertainties. The ultimate boundedness of the closed-loop system is proved by the Lyapunov approach. The performance of the proposed control system is demonstrated by simulation and experimental results a 5-link robot manipulator with two degree of freedom.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.1
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• pp.9-16
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• 2004

In this paper, we propose a robust controller for robot manipulators with parametric uncertainties using feature-based visual servo control system. In order to improve trajectory error of the robot manipulators due to the parameter variation, integral action is included in the dynamic control of part in inner subroutine of the control system. This integral action also reduces feature error in the steady state. The stability analysis of the closed-loop system is shown by the Lyapunov method. The effectiveness of the proposed method is shown by simulation and experimental results on the 5 link robot manipulator with two degree of freedom.

• The Journal of Korea Robotics Society
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• v.18 no.2
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• pp.172-181
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• 2023

This paper presents research on the stability of control for a quadruped robot with two different leg structure designs. The focus of the research is on the design and analysis of the leg structures in terms of their impact on the stability and robustness of the robot's motion. First, a static analysis was performed in the simulation to compare the structural strength of the legs when the same force was applied. Secondly, two quadruped robots were built, each equipped with differently designed legs, and performed trot gait walking in the real world. And the states of the robots and the torques of each joint were analyzed and compared. In conclusion, based on the results of structural analysis in simulation and the actual walking experiments with the robots, it was demonstrated that the legs designed to be structurally robust improved the control stability of the quadruped robot.

• Journal of Mechanical Science and Technology
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• v.15 no.3
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• pp.339-350
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• 2001

To overcome problems in tracking error related to the unmodeled dynamics in the high speed operation of industrial robots, many researchers have used sliding mode control, which is robust against parameter variations and payload changes. However, these algorithms cannot reduce the inherent chattering which is caused by excessive switching inputs around the sliding surface. This study proposes a fuzzy-sliding mode control algorithm to reduce the chattering of the sliding mode control by fuzzy rules within a pre-determined dead zone. Trajectory tracking simulations and experiments show that chattering can be reduced prominently by the fuzzy-sliding mode control algorithm compared to a sliding mode control with two dead zones, and the proposed control algorithm is robust to changes in payload. The proposed control algorithm is implemented to the SCARA (selected compliance articulated robot assembly) robot using a DSP (digital signal processor) for high speed calculations.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.258-266
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• 2012

This paper describes a biped walking algorithm for a hydraulic humanoid robot on inclined floors. To realize stable and robust biped walking, the walking algorithm was divided into five control strategies. The first is a joint position control strategy. This strategy is for tracking desired joint position trajectories with a gain switching. The second is a multi-model based ZMP (Zero Moment Point) control strategy for dynamic balance. The third is a walking pattern flow control strategy for smooth transition from step to step. The fourth is an ankle compliance control, which increases the dynamic stability at the moment of floor contact. The last is an upright pose control strategy for robust walking on an inclined floor. All strategies are based on simple pendulum models and include practical sensory feedback in order to implement the strategies on a physical robot. Finally, the performance of the control strategies are evaluated and verified through dynamic simulations of a hydraulic humanoid on level and inclined floors.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.267-270
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• 1995

In this paper, a variable structure control scheme with a terminal sliding mode is proposed for robot manipulators. The proposed control scheme guarantees that the output tracking error converges to zero in finite time, and the overall system shows robust property against parametric uncertainties and external disturbances all the time.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.4
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• pp.259-266
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• 2015

This study presents new scheme for various walking pattern of biped robot under the limitted enviroments. We show that the neural network is significantly more attractive intelligent controller design than previous traditional forms of control systems. A multilayer backpropagation neural network identification is simulated to obtain a learning control solution of biped robot. Once the neural network has learned, the other neural network control is designed for various trajectory tracking control with same learning-base. The main advantage of our scheme is that we do not require any knowledge about the system dynamic and nonlinear characteristic, and can therefore treat the robot as a black box. It is also shown that the neural network is a powerful control theory for various trajectory tracking control of biped robot with same learning-vase. That is, we do net change the control parameter for various trajectory tracking control. Simulation and experimental result show that the neural network is practically feasible and realizable for iterative learning control of biped robot.