• 제어로봇시스템학회논문지
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• 제6권4호
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• pp.305-312
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• 2000

This paper presents a new control scheme using a sliding mode controller with a multilayer neural network for the robot manipulator operating under the sea which has large uncertainties such as the buoyancy and the added mass/moment of inertia. The multilayer neural network using the error back propagation loaming algorithm acts as a compensator of the conventional sliding mode controller to improve the control performance when the initial assumptions of uncertainty bounds are not valid. Computer simulation results show that the proposed control scheme gives an effective path way to cope with the unexpected large uncertainties in the underwater robot manipulator.

• 한국정밀공학회지
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• 제6권4호
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• pp.108-118
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• 1989

An adaptive control scheme has been recognized as an effective approach for a robot manipulator to track a desired trajectory in spite of the presence of nonliearity and parameter uncertainty in robot dynamics model. In this paper, an adaptive control scheme for a robot manipulator is proposed to design robust controller using model reference adaptive control technique and hyperstability theory but it does away with] assumption that the process is characterized by a linear model remaining time invariant during the adaptation process. The performance of controller is demonstrated by the simulation about position and speed control of a six-link manipulator with disturbance and payload variation.

• 드라이브 ㆍ 컨트롤
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• 제12권4호
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• pp.41-47
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• 2015

Hydraulic manipulators have been widely used in many different fields due to their high force/torque to inertia ratio. The increased speed of hydraulic manipulators requires solutions to problems ranging from mechanical design to the need to determine a robot model suitable for model-based control. As a solution, this paper presents the integration of SolidWorks with Simscape for designing and controlling hydraulic manipulators. The integration provides a platform for the rapid control prototyping of a hydraulic robot without the need to build actual prototypes. The mechanical drawings of a manipulator are first created using Solidworks and are then imported into Simscape, where the manipulator is represented by connected block diagrams based on the principle of physical modeling. Simulation examples for a 3D manipulator made by KNR SYSTEM INC are verified to show the effectiveness of the presented platform.

• 전자공학회논문지B
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• 제29B권10호
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• pp.59-68
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• 1992

In this paper, we proposed coordinator description and ambiguity on the hybrid controller for position/force control of robot manipulator. When the hybrid controller is desiged based on the PID control conception, the parameter sharing problem must be considered. However, selection problem of coordinate system on n-DOF robot manipulator control is unsolved. Moreover, contact force on object and change of shape make another problems. And it is very difficult to figure out the accurate mathematical model of manipulator on account of ambiguity and nonlinearity of actuator. Therfore, we design a new hybrid controller, FPID(Fuzzy PID). For verifying the validity of the controller, we tried computer simulation of this system. As a result, we can get remarkable improvement of overdamping and overshooting. Also we can solve compicance problem effectively. Furthermore, ambiguity problem is solved by adding control knowledge based compensator. So robust controller can be acheived, too.

• International Journal of Control, Automation, and Systems
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• 제5권6호
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• pp.630-642
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• 2007

In this paper, we propose a direct model reference adaptive fuzzy control (MRAFC) for MIMO nonlinear systems whose structure is represented by the Takagi-Sugeno fuzzy model. The adaptive law of the MRAFC estimates the approximation error of the fuzzy logic system so that it provides asymptotic tracking of the reference signal for the systems with uncertain or slowly time-varying parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop system. In addition, the plant state tracks the state of the reference model asymptotically with time for any bounded reference input signal. To verify the validity and effectiveness of the MRAFC scheme, the suggested analysis and design techniques are applied to the tracking control of robot manipulator and simulation studies are carried out. In the control design, the MRAFC is combined with feedforward PD control to make the actual joint trajectories of the robot manipulator with system uncertainties track the desired reference joint position trajectories asymptotically stably.

• 한국해양공학회지
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• 제34권3호
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• pp.180-193
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• 2020

In this study, the end-effector tracking performance of a manipulator installed on a remotely operated vehicle (ROV) for autonomous underwater intervention is verified. The underwater manipulator is an ARM 7E MINI model produced by the ECA group, which consists of six joints and one gripper. Of the six joints of the manipulator, two are revolute joints and the other four are prismatic joints. Velocity control is used to control the manipulator with forward and inverse kinematics. When the manipulator approaches a target object, it is difficult for the ROV to maintain its position and posture, owing to various disturbances, such as the variation in both the center of mass and the reaction force resulting from the manipulator motion. Therefore, it is necessary to compensate for the influences and ensure the relative distance to the object. Simulations and experiments are performed to track the trajectory of a virtual object, and the tracking performance is verified from the results.

• 제어로봇시스템학회논문지
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• 제6권1호
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• pp.66-72
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• 2000

As the demand for the design of modular manipulators or special purpose manipulators has increased, task based design to design an optimal manipulator for a given task become more and more important. However, the complexity with a large number of design parameters, and highly nonlinear and implicit functions are characteristics of a general manipulator design. To achieve the goal of task based design, it is necessary to develop a methodology to solve the complexity. This paper addresses how to determine the kinematic parameters of a two-degrees of freedom manipulator with parallelogram five-bar link mechanism from a given task, namely, how to map a given task into the kinematic parameters. With simplified example of designing a manipulator with five-bar link mechanism, the methodology for task based design is presented. And it introduces formulations of a given task and manipulator specifications, and presents a new dexterity measure for manipulator design. Also the optimization problem with constraints is solved by using a genetic algorithm that provides robust search in complex spaces.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 D
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• pp.1960-1961
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• 2006

In this paper, The trajectory control of robot manipulator is proposed. It divides by trajectory planning and tracking control. A trajectory planning and tracking control of robot manipulator is used to the neural network and evolutionary algorithm. The trajectory planning provides not only the optimal trajectory for a given cost function through evolutionary algorithm but also the configurations of the robot manipulator along the trajectory by considering the robot dynamics. The computed torque method (C.T.M) using the model of the robot manipulators is an effective means for trajectory tracking control. However, the tracking performance of this method is severely affected by the uncertainties of robot manipulators. The Radial Basis Function Networks(RBFN) is used not to learn the inverse dynamic model but to compensate the uncertainties of robot manipulator. The computer simulations show the effectiveness of the proposed method.

• 한국항해학회지
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• 제21권3호
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• pp.55-66
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• 1997

In this paper, applications of neural networks to vibration control of flexible single link robot manipulator are ocnsidered. The architecture of neural networks is a hidden layer, which is comprised of self-recurrent one. Tow neural networks are utilized in a control system ; one as an identifier is called neuro identifier and the othe ra s a controller is called neuro controller. The neural networks can be used to approximate any continuous function to any desired degree of accuracy and the weights are updated by dynamic error-backpropagation algorithm(DEA). To guarantee concegence and to get faster learning, an approach that uses adaptive learning rates is developed by introducing a Lyapunov function. When a flexible manipulator is ratated by a motor through the fixed end, transverse vibration may occur. The motor torque should be controlle dinsuch as way, that the motor is rotated by a specified angle. while simulataneously stabilizing vibration of the flexible manipulators so that it is arrested as soon as possible at the end of rotation. Accurate vibration control of lightweight manipulator during the large body motions, as well as the flexural vibrations. Therefore, dynamic models for a flexible single link manipulator is derived, and LQR controller and nerual networks controller are composed. The effectiveness of the proposed nerual networks control system is confirmed by experiments.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국내학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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• pp.86-91
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• 1988

The analytical studies and applicability of the implementation of the controller for the simple flexible arm studies and discussed in this thesis with the goal of developing flexible manipulator arm control. Minimum-time position control and quadractic-optimal control are investigated in this thesis. Its validity has been established using numerical simulations.