• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.1
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• pp.17-25
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• 2014

This paper presents the formulation of an impedance controller for regulating the contact force with the environment. To achieve an accurate force tracking control, uncertainties in both robot dynamics and the environment require to be addressed. As part of the framework of the proposed force tracking formulation, a neural network is introduced at the desired trajectory to compensate for all uncertainties in an on-line manner. Compensation at the input trajectory leads to a remarkable structural advantage in that no modifications of the internal force controllers are required. Minimizing the objective function of the training signal for a neural network satisfies the desired force tracking performance. A neural network actually compensates for uncertainties at the input trajectory level in an on-line fashion. Simulation results confirm the position and force tracking abilities of a robot manipulator.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.3
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• pp.382-392
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• 1999

Industrial robots have increased in both the number and applications in today's material handling systems. However, traditional approaches to robot controling have had limited success in complicated environment, especially for real time applications. One of the main reasons for this is that most traditional methods use a set of kinematic equations to figure out the physical environment of the robot. In this paper, a neural network model to solve robot manipulator's inverse kinematics problem is suggested. It is composed of two Self-Organizing Feature Maps by which the workspace of robot environment and the joint space of robot manipulator is inter-linked to enable the learning of the inverse kinematic relationship between workspace and joint space. The proposed model has been simulated with two robot manipulators, one, consisting of 2 links in 2-dimensional workspace and the other, consisting of 3 links in 2-dimensional workspace, and the performance has been tested by accuracy of the manipulator's positioning and the response time.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.4
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• pp.104-109
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• 1997

A robust controller design to corrdinate a robot manipulator under unknown system parameters and bounded disturbance inputs is presented in this paper. Generally, robust controllers require high input torque so that they may face input saturation in actual application due to the power limitation of the actuator. To solve this problem, an improved robust controller with saturated input torque using a fuzzy logic control is proposed. Numerical examples are shown to validate the proposed controller using two degree-of-freedom planar arm.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.423-427
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• 1993

A velocity planning method is proposed that ensures collision-free and minimal delay-time motions for two robotic manipulators and auxiliary equipments. Additional path, which makes robot start with possible largest speed, is added to the original prescribed path of one of two robots, and this running start along the additional path reduces delay time introduced to avoid collision between the robots and therefore reduces total traveling time.

• Journal of Mechanical Science and Technology
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• v.17 no.7
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• pp.999-1010
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• 2003

Uninterrupted power supply has become indispensable during the maintenance task of active electric power lines as a result of today's highly information-oriented society and increasing demand of electric utilities. This maintenance task has the risk of electric shock and the danger of falling from high place. Therefore it is necessary to realize an autonomous robot system using electro-hydraulic manipulators because hydraulic manipulators have the advantage of electric insulation and power/mass density. Meanwhile an electro-hydraulic manipulator using hydraulic actuators has many nonlinear elements, and its parameter fluctuations are greater than those of an electrically driven manipulator. So it is relatively difficult to realize not only stable contact work but also accurate force control for the autonomous assembly tasks using hydraulic manipulators. In this paper, the robust force control of a 6-link electro-hydraulic manipulator system used in the real maintenance task of active electric lines is examined in detail. A nominal model for the system is obtained from experimental frequency responses of the system, and the deviation of the manipulator system from the nominal model is derived by a multiplicative uncertainty. Robust disturbance observers for force control are designed using this information in an H$\_$$\infty$/ framework, and implemented on the two different setups. Experimental results show that highly robust force tracking by a 6-link electro-hydraulic manipulator could be achieved even if the stiffness of environment and the shape of wall change.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.61-64
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• 1996

This paper presents a new approach to the design of self-tuning adaptive control system that is robust to the changing dynamic configuration as well as to the load variation factors using Digital signal processors for robot manipulators. TMS32OC50 is used in implementing real-time adaptive control algorithms to provide advanced performance for robot manipulator. In this paper, an adaptive control scheme is proposed in order to design the pole-placement self-tuning controller which can reject the offset due to any load disturbance without a detailed description of robot dynamics. Parameters of discrete-time difference model are estimated by the recursive least-square identification algorithm, and controller parameters are determined by the pole-placement method. Performance of self-tuning adaptive controller is illustrated by the simulation and experiment for a SCARA robot.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2004-2009
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• 2003

A robust optimal control design is proposed in this study for rigid robotic systems under the unknown load and the other uncertainties. The uncertainties are quadratically bounded for some positive definite matrix. Iterative method finding the Q weighting matrix is shown. Computer simulations have been done for a weight-lifting operation of a two-link manipulator and the result of the simulation shows that the proposed algorithm is very effective for a robust control of robotic systems.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.1075-1079
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• 1989

In this paper a robust control design is developed for the control of a multi-joint manipulators using sliding observer. The sliding observer is introduced to estimate the angular velocity of the links under the disturbance input. The feedback control is designed by the use of the estimated value of the angular velocity .theta.. The VSS control laws is introduced to ensure the robustness concerning the disturbance inputs. To illustrate the effectiveness of the proposed method, a computer simulation is performed for a two-joint manipulator.

• Journal of Mechanical Science and Technology
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• v.14 no.2
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• pp.188-196
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• 2000

In this paper, our aim is to develop a model for two cooperating flexible manipulators handling a rigid object by using lumped parameters. This model is in turn analyzed on MATLAB. In order to validate the model, a precise simulation model is developed using $ADAMS^{TM}$ (Automatic Dynamic Analysis of Mechanical System). Moreover, to clarify the discussion, the motions of a dual-arm experimental flexible manipulator are considered. Using the developed model, we control a robotic system with a symmetric hybrid position/force control scheme. Finally, experiments and simulations are performed, and a comparison of simulation results with experimental results is given to a rerify the validity of our model.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1115-1120
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• 2003

The present paper shows the possible development of particle swarm optimization (PSO) based fuzzy-neural networks (FNN) which can be employed as an important building block in real life robot systems, controlled by voice-based commands. The PSO is employed to train the FNNs which can accurately output the crisp control signals for the robot systems, based on fuzzy linguistic spoken language commands, issued by an user. The FNN is also trained to capture the user spoken directive in the context of the present performance of the robot system. Hidden Markov Model (HMM) based automatic speech recognizers are developed, as part of the entire system, so that the system can identify important user directives from the running utterances. The system is successfully employed in a real life situation for motion control of a redundant manipulator.