• Journal of the Korean Institute of Navigation
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• v.21 no.1
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• pp.109-118
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• 1997

In this paper, applications of multilayer neural networks to control of flexible robot beam are considered. The multilayer nerual networks can be used to approximate any continuous function to a desired degree of accuracy and the weights are updated by Gradient Method. When a flexible beam is rotated by a motor through the fixed end, transverse vibration may occur. The motor torque should be controlled insuch a way that the motor rotates by a specified angle, while simultaneously stabilizing vibration of the flexible manipulators so that is arrested as soon as possbile at the end of rotation. Accurate control of lightweight beam during the large changes in configuration common to robotic tasks requires dynamic models that describe both rigid body motions, as well as the flexural vibrations. Therefore, a linear dynamic state-space model of for a single link flexible robot beam is derived and PD controller, LQP controller, and inverse dynamical neural networks controller are composed. The effectiveness the proposed control system is confirmed by computer simulation.

• Structural Engineering and Mechanics
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• v.62 no.5
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• pp.619-629
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• 2017

This paper focuses on the study of complete dynamic modeling and maximum dynamic load carrying capacity computation of N-flexible links and N-flexible joints mobile manipulator undergoing large deformation. Nonlinear dynamic analysis relies on the Timoshenko theory of beams. In order to model the system completely and precisely, structural and joint flexibility, nonlinear strain-displacement relationship, payload, and non-holonomic constraints will be considered to. A finite element solution method based on mixed method is applied to model the shear deformation. This procedure is considerably more involved than displacement based element and shear deformation can be readily included without inducing the shear locking in the element. Another goal of this paper is to present a computational procedure for determination of the maximum dynamic load of geometrically nonlinear manipulators with structural and joint flexibility. An effective measure named as Moment-Height Stability (MHS) measure is applied to consider the dynamic stability of a wheeled mobile manipulator. Simulations are performed for mobile base manipulator with two flexible links and joints. The results represent that dynamic stability constraint is sensitive when calculating the maximum carrying load. Furthermore, by changing the trajectory of end effector, allowable load also changes. The effect of torsional spring parameter on the joint deformation is investigated in a parametric sensitivity study. The findings show that, by the increase of torsional stiffness, the behavior of system approaches to a system with rigid joints and allowable load of robot is also enhanced. A comparison is also made between the results obtained from small and large deformation models. Fluctuation range in obtained figures for angular displacement of links and end effector path is bigger for large deformation model. Experimental results are also provided to validate the theoretical model and these have good agreement with the simulated results.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.10
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• pp.114-119
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• 2002

The aim of this paper is to clarify the structural compliance of the constrained flexible manipulator and to develop the force control algorithm by using the compliance of the links. The proposed structural compliance control consists of the position control to utilize a flexible manipulator model (considering the compensation for the elastic deflection of links) and the passive force control to utilize the rigid manipulator model (without considering the compensation for the elastic deflection of links). We present the experimental results for the case when applying the only position control, and when applying the structural compliance control. Finally, a comparison between these results is presented to show the performance of our method.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.1
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• pp.62-68
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• 1996

Linear controllers, such as LQG/LTR controller, have been investigated to control flexible link manipulators. The performance and complexity of these depend largely on the linearized model upon which the controller is designed. In this study, singular perturbation model is tested in designing a LQG/LTR controller for a flexible link manipulator. The order of the resulting controller is much lower than the one based on a full model. Through numerical study, it is shown that the performance of the proposed controller reaches reasonably to the one based on the full model.

• Smart Structures and Systems
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• v.1 no.1
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• pp.13-27
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• 2005

Simultaneous precision positioning and vibration suppression of a reciprocating flexible manipulator is investigated in this paper. The flexible manipulator is driven by a multifunctional active strut with fuzzy logic controllers. The multifunctional active strut is a combination of a motor assembly and a piezoelectric stack actuator to simultaneously provide precision positioning and wide frequency bandwidth vibration suppression capabilities. First, the multifunctional active strut and the flexible manipulator are introduced, and their dynamic models are derived. A control strategy is then proposed, which includes a position controller and a vibration controller to achieve simultaneous precision positioning and vibration suppression of the flexible manipulator. Next, fuzzy logic control approach is presented to design a fuzzy logic position controller and a fuzzy logic vibration controller. Finally, experiments are conducted for the fuzzy logic controllers and the experimental results are compared with those from a PID control scheme consisting of a PID position controller and a PID vibration control. The comparison indicates that the fuzzy logic controller can easily handle the non-linearity in the strut and provide higher position accuracy and better vibration reduction with less control power consumption.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.280-284
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• 1997

In this paper, Nonlinear VSS control based on bang-bang control concept is derived under the assumption that the control input is bounded. We try to derive control algorithm which has almost same performance as the time optimal control. We focus this control scheme on the real implementation of DC motor position controller of flexible link, i.e. we obtain the switching curves from the real data of DC motor system operating under the full maximum and minimum applied voltages. State space is separated into several regions and we set different switching surfaces in each region to reduce chattering problem. The efficiency of the proposed controller is compared with PID controller and it is shown that the controller converges fast than PID controller without chattering. The hybrid controller scheme is also proposed not only to control the position of hub but also to reduce the vibration of end tip of flexible link.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.342-345
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• 1995

This paper describes the design process and the experimental results of a fuzzy logic controller to control the tip position of a fixible-link manipulator, directly driven by a AC motor, with a large payload. The joint angle fuzzy logic controller is designed without a costly nonlinear system analysis of the flexible manipulator and the AC motor drive system. The state variables for the fuzzy logic controller are joint angle, joint velocity, link deflection, and link deflection velocity. The simulation and experimental results show that the joint position control is not satisfactory when the controller is designed under the assumption of no link flexibility and that stable joint position control and link vibration suppression can be cahieved with the fuzzy logic controller suggested in this paper.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.9
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• pp.1245-1247
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• 2014

This paper presents a robust position tracking controller for motor-driven flexible joint manipulators using only the motor angle measurement. The control problem is not easy because the link position is hard to estimate in the presence of parameter uncertainties. The proposed controller consists of a feedback linearization controller (FLC) and two proportional-integral observers (PIOs) that estimate both system states including the link position and an equivalent disturbance for compensating the parameter uncertainties. Comparative computer simulations are conducted to demonstrate the effectiveness of the proposed control algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.11
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• pp.1103-1109
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• 2008

Since the flexible joint robots with motor dynamics are represented by the fifth-order nonlinear sγstem, it is difficult and complex to design the controller for electrically driven flexible-joint (EDFJ) robots. In this paper, we propose a simple adaptive control method to solve this problem. It is assumed that the model uncertainties of the robots dynamics, joint flexibility, and motor dynamics are unknown. For the simple control design, the dynamic surface design method is applied, and all uncertainties in the robot and motor dynamics are compensated by using the adaptive function approximation technique. It is proved that all signals in the controlled closed-loop system are uniformly ultimately bounded. Simulation results for three-link EDFJ manipulators are provided to validate the effectiveness of the proposed control system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.101-106
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• 1997

This paper proposes a stable adaptive neural network control(NNC) for fixable joint manipulators. For designing the stable adaptive NNC, the flexible system dynamics is separated into fast and slow subdynamics according to singular perturbation concept. For the slow subdynamics, an adaptive NNC is designed to warrant the system stability and NN learning by lyapunov stability criterion. And to stabilize the fast dynamics, derivative control loop is installed. Through numerical simulation, the performance of the proposed NNC was compared to that of an adaptive controller designed based on the knowledge of the system dynamics. The proposed NNC shows much improvement over the conventional adaptive controller.