• Journal of the Korean Society for Precision Engineering
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• v.22 no.7 s.172
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• pp.102-111
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• 2005

In this paper, we address a position control for a parallel stage, which is levitated and driven by electric magnetic force. This consists of a levitating object (called platen) with 4 permanent magnetic linear synchronous motors in parallel. Each motor generates vertical force for suspension against gravity and propulsion force horizontally as well. This stage can generate six degrees of freedom motion by the vertical and horizontal force. A dynamic equation of the stage system is derived based on Newton-Euler method and it's special Jacobian matrix describing a relation between the limited velocity and Cartesian velocity is done. There are proposed two control methods for positioning which are Cartesian space controller and Actuator space controller. The control performance of the Cartesian space controller is better than the Actuator space controller in task space trajectory while the Actuator space controller is simpler than the Cartesian space controller in controller realization.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1820-1823
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• 1997

For the Cartesian space position controlled robot, it is required to have the accurate mapping from the Cartesian space to the joint space in order to command the desired joint trajectories correctly. since the actual mapping from Cartesian space to joint space is obtained at the joint coordinate not at the actuator coordinate, uncertainty in Jacobian can be present. In this paper, two feasible neural network schemes are proposed to compensate for the kinematic Jacobian uncertainties. Uncertainties in Jacobian can be compensated by identifying either actuator Jacobian off-line or the inverse of that in on-line fashion. the case study of the stenciling robot is examined.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.540-546
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• 2013

This paper presents a trajectory planning algorithm for TMR (Two-wheeled Mobile Robots). The trajectory is developed in joint space and considers the physical limits of a TMR. First, we present a process for generating a smooth curve through a Bezier curve. The trajectory for the center of the TMR following the Bezier curve is developed through a convolution operator taking into consideration its physical limits. The trajectory along the Bezier curve is regenerated using time-dependent parameters which correspond to the distance driven by the velocity of the center of the TMR in a sampling time. The velocity commands in the Cartesian space are converted to actuator commands for two wheels. In case that the actuator commands exceed the maximum velocity, the trajectory is redeveloped with compensated center velocity. We also suggest a smooth trajectory planning algorithm in joint space for the two segmented paths. Finally, the effectiveness of the algorithm is shown through numerical examples and application to a simulator.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.10
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• pp.930-939
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• 2004

In this paper, both dynamic constraints and kinematic constraints are considered for the analysis of manipulability of robotic systems comprised of multiple cooperating arms. Given bounds on the torques of each Joint actuator for every robot, the purpose of this study is to drive the bounds of task-space acceleration of object carried by the system. Bounds on each joint torque, described as a polytope, is transformed to the task-space acceleration through matrices related with robot dynamics, robot kinematics, object dynamics, grasp conditions, and contact conditions. A series of mathematical manipulations including the procedure calculating minimum infinite-norm solution of linear equation is applied to get the reachable acceleration bounds from given actuator dynamic constrains. Several examples including two robot systems as well as three robot system are shown with the assumptions of complete-constraint contact model(or' very soft contact') and insufficient or proper degree of freedom robot.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.519-524
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• 1998

This paper presents a robust control scheme of free-joint manipulators to overcome actuator failures and uncertain-ties in Cartesian space where tasks are planned. The control scheme has the adaptation law for the upper bound on the norm of uncertainties through the Lyapunov function approach. To solve the dynamic singularity problem in the controller, the singular and nonsingular regions are investigated based on a computer simulation. Then a singularity-free Cartesian trajectory planning is achieved in order to guarantee the availability of the control scheme. To illustrate the validity of the proposed control scheme, simulation results for a three-link planar robot arm with a free joint are shown.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.9
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• pp.887-893
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• 2009

In this paper, a mask-panel alignment robot system is considered for IT industry applications. Two kinds of solutions are suggested which are required in constructing a control system for the alignment robot with actuation redundancy. First, the kinematic solution for the 4PPR parallel positioning mechanism is formulated for an arbitrary initial posture, which relates the mask-panel misalignment in the task space and the desired actuator displacements in the joint space. Secondly, in order to increase the stiffness of the control motion and also to avoid the mechanical lock which may happen due to the redundant actuation, a new synchronous control method is proposed which has the merit of coordinating joint control motions while not losing individual joint control performance. In addition, the engineering process to develop a visual alignment robot system is described with the results of experimental setup and GUI software. Finally, the experimental results demonstrate the effectiveness of the proposed alignment system control methodology and how much beneficial it will be in real industrial applications.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.6
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• pp.484-491
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• 2002

We developed a new type of human-sized BWR (biped walking robot) driven by a new actuator based on the ball screw which has high strength and high gear ratio. Each leg of the robot is composed of three pitch joints and one roll joint. In all, a 10 degree-of-freedom robot with two balancing joints was developed. A new type of actuator for the robot is proposed, which is composed of four bar link mechanism driven by the ball screw. The robot overcomes the limit of the driving torque of conventional BWRs. The BWR was designed to walk autonomously by adapting small DC motors for the robot actuators and has a space to board DC battery and controllers. In the performance test, the BWR performed sitting-up and down motion, and walking motion. Through the test, we found the possibility of a high performance biped-walking.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.306-309
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• 2005

This parer describes the tracking control simulation of 6-DOF shaking table with a bell crank structure, which converts the direction of reciprocating movements. For the Joint coordinate-based control which uses lengths of each actuator, the trajectory conversion process inverse kinematics is performed. Applying the Newton-Euler approach, the dynamic equation of the shaking table is derived. To cope with nonlinear problems, time-delay control(TDC) is considered, which has been noted for its exceptional robustness to parameter uncertainties and disturbance, in addition to steady-state accuracy and computational efficiency. If the nominal model is equal to the real system, joint coordinate-based control can be very efficient. However, manufacturing tolerances installation errors and link offsets contaminate the nominal values of the kinematic parameters used in the kinematic model of the shaking table. To compensate differences between the nominal model and the real system. the joint coordinate-based control using acceleration feedback in the Cartesian coordinate space is proposed.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1983-1989
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• 2005

Industrial robots are powerful, extremely accurate multi-jointed systems, but they are heavy and highly rigid because of their mechanical structure and motorization. Therefore, sharing the robot working space with its environment is problematic. A novel pneumatic artificial muscle actuator (PAM actuator) has been regarded during the recent decades as an interesting alternative to hydraulic and electric actuators. Its main advantages are high strength and high power/weight ratio, low cost, compactness, ease of maintenance, cleanliness, readily available and cheap power source, inherent safety and mobility assistance to humans performing tasks. The PAM is undoubtedly the most promising artificial muscle for the actuation of new types of industrial robots such as Rubber Actuator and PAM manipulators. However, some limitations still exist, such as the air compressibility and the lack of damping ability of the actuator bring the dynamic delay of the pressure response and cause the oscillatory motion. In addition, the nonlinearities in the PAM manipulator still limit the controllability. Therefore, it is not easy to realize motion with high accuracy and high speed and with respect to various external inertia loads in order to realize a human-friendly therapy robot To overcome these problems a novel controller, which harmonizes a phase plane switching control method with conventional PID controller and the adaptabilities of neural network, is newly proposed. In order to realize satisfactory control performance a variable damper - Magneto-Rheological Brake (MRB) is equipped to the joint of the manipulator. Superb mixture of conventional PID controller and a phase plane switching control using neural network brings us a novel controller. This proposed controller is appropriate for a kind of plants with nonlinearity uncertainties and disturbances. The experiments were carried out in practical PAM manipulator and the effectiveness of the proposed control algorithm was demonstrated through experiments, which had proved that the stability of the manipulator can be improved greatly in a high gain control by using MRB with phase plane switching control using neural network and without regard for the changes of external inertia loads.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.293-298
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• 1993

In this paper, methods for computing the time-optimal motion of a robotic manipulator are presented that considers the nonlinear manipulator dynamics, actuator constraints, joint limits, and obstacles. The optimization problem can be reduced to a search for the time-optimal path in the n-dimensional position space. These paths are further optimized with a local path optimization to yield a global optimal solution. Time-optimal motion of a robot with an articulated arm is presented as an example.