• 한국생산제조학회지
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• 제19권5호
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• pp.645-652
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• 2010

For free motions, vibration suppression of single flexible manipulators has been one of the hottest research topics. However, for cooperative motions of multiple flexible manipulators, a little effort has been devoted for the vibration suppression control. So, the aim of this paper is to develop a hybrid force/position control and vibration suppression control scheme for multiple cooperation flexible manipulators handling a rigid object. In order to clarify the discussion, the motions of dual-arm experimental flexible manipulator are considered. Using the developed model, we control a robotic system with hybrid position/force control scheme. Finally, Experiments are performed, and a comparison of experimental results is given to clarify the validity of our control scheme.

• 제어로봇시스템학회지
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• 제5권2호
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• pp.29-34
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• 1999

• 대한기계학회논문집
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• 제19권6호
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• pp.1371-1381
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• 1995

A novel hybrid control scheme to actively control the endpoint position of a very flexible single-link manipulator is proposed. The control scheme consists of a motor mounted at the beam hub and a piezofilm actuator bonded to the surface of the flexible link. The control torque of the motor to produce a desired motion is firstly determined by employing the sliding mode control theory on the equation of motion of the rigid link having the same mass as that of the proposed flexible link. The torque is then applied to the flexible manipulator in order to activate the commanded motion. During the motion, undesirable oscillation is actively suppressed by applying a feedback control voltage to the piezofilm actuator. Consequently, the imposed desired position is accomplished. In order to demonstrate high control performances accrued from the proposed method, computer simulations are undertaken by treating both regulating and tracking control problems.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1624-1627
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• 1997

The 6-DOF parallel manipulator is a closed-kindmatic chain robot manipulator that is capable of providing high structural rigidity and positional accuracy. Because of its advantage, the parallel manipulator have been widely used in many engineering applications such as vehicle/flight driving simulators, rogot maniplators, attachment tool of machining centers, etc. However, the kinematic analysis for the implementation of a real-time controller has some problem because of the lack of an efficient lagorithm for solving its highly nonliner forward kinematic equation, which provides the translational and orientational attitudes of the moveable upper platform from the lenght of manipulator linkages. Generally, Newton-Raphson method has been widely sued to solve the forward kinematic problem but the effectiveness of this methodology depend on how to set initial values. This paper proposes a hybrid method using genetic algorithm(GA) and Newton-Raphson method to solve forward kinematics. That is, the initial values of forward kinematics solution are determined by adopting genetic algorithm which can search grobally optimal solutions. Since determining this values, the determined values are used in Newton-Raphson method for real time calcuation.

• International Journal of Control, Automation, and Systems
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• 제5권6호
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• pp.674-680
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• 2007

The probabilistic roadmap (PRM) method, which is a popular path planning scheme, for a manipulator, can find a collision-free path by connecting the start and goal poses through a roadmap constructed by drawing random nodes in the free configuration space. PRM exhibits robust performance for static environments, but its performance is poor for dynamic environments. On the other hand, reinforcement learning, a behavior-based control technique, can deal with uncertainties in the environment. The reinforcement learning agent can establish a policy that maximizes the sum of rewards by selecting the optimal actions in any state through iterative interactions with the environment. In this paper, we propose efficient real-time path planning by combining PRM and reinforcement learning to deal with uncertain dynamic environments and similar environments. A series of experiments demonstrate that the proposed hybrid path planner can generate a collision-free path even for dynamic environments in which objects block the pre-planned global path. It is also shown that the hybrid path planner can adapt to the similar, previously learned environments without significant additional learning.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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• pp.340-345
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• 1994

Dynamic hybrid position/force control of flexible manipulators is proposed. First, a 2 D.O.F. flexible manipulator is modeled using the spring-mass model. Second, the equation of motion considering the tip constraints is derived. Third, hybrid position/force control algorithm is derived. In this control algorithm, the differentiable order of the desired trajectory and the stability condition are different from the case of rigid manipulators. Lastly, to verify the effectiveness of the proposed control algorithm, simulation results are presented.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 추계학술대회 논문집
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• pp.161-164
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• 2000

An improved robust hybrid control law is proposed This law uses the separated bounding function: so uncertainties of each axis does not affect the others. Also, this law uses the separated $\varepsilon$, so we can take different $\varepsilon$ for each axis This law guarantees the practical stability in sense of Lyapunov. Simulation was performed to validate this law using a four-axis SCARA type robot manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.638-641
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• 1992

In this paper, a hybrid position/force control scheme is proposed. The control scheme modifies the position command for force control against constraint surface of environment and is very simply designed and implemented. The merits of the control scheme are that it can cope with change of constraint conditions and small position inaccuracy of the environment. A constraint surface position observer is also proposed to reduce disturbances on controlled force.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.863-868
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• 1992

This paper presents a method on applying Genetic Algorithm(GA), which is a well-known high performance optimizing algorithm, to construct the self-organizing fuzzy logic controller. Fuzzy logic controller considered in this paper utilizes Sugeno's hybrid inference method, which has an advantage of simple defuzzification process in the inference engine. Genetic algorithm is used to find the optimal parameters in the FLC. The proposed approach will be demonstrated using 2 d.o.f robot manipulator to verify its effectiveness.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2000년도 춘계학술대회논문집A
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• pp.517-522
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• 2000

When a real robot manipulator is mathematically modeled. uncertainties are not avoidable. The uncertainties are often nonlinear and time-varying. The uncertain factors collie from imperfect knowledge ok system parameters. payload change. friction. external disturbance. and etc. In this paper. we propose a class of robust hybrid controls of manipulators without knowing the exact stiffness and provide the stability analysis. Simulation results are provided to show the effectiveness of the algorithms.