• Journal of the Korean Society for Precision Engineering
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• v.17 no.4
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• pp.181-188
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• 2000

Input shaping is a method fur reducing residual vibration. Vibration is eliminated by convolving an input shaper, which is a sequence of impulses, with the desired system command. It has been applied to robot with a flexible manipulator. But it can be applied to the reduction of residual vibration far overhead crane. In this paper, input shaping shows good performance for anti-sway of overhead crane. In the z-domain, we designed an input shaper and calculated the sensitivity of it. If sensitivity is calculated in the z-domain, the shapes of sensitivity curves are expected easily. Accordingly, it is easy to design an input shaper in the z-domain. We compared the response of a system with shaper to it without that. Also, we compared El shaper to ZV shaper in view of robustness.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.65-68
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• 1996

Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. The TMS32OC31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the, network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time, control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.224-229
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• 1997

This paper compares the control techniques for position control experiments of a fixible robot moving in a vertical plane. The flexible manipulator is modeled as an Euler-beroulli beam. Elastic deformantion is representedusing the assumed model method. A comparison function which satisfies all geometric and natural boundary conditions of a cantilever beam with an end mass is used as an assumed mode shape. Lagrange's equation is utilized for the development of a discretized model. Control schemes are developed using PID control,pole placement control and discrete Linear Quadratic Regulater(LQQ). The effectiveness of the developed control schems are compared using computer simulation in view of practical experiment. The simulation results show that PID control is very effective in practical implementation.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.22-31
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• 1999

In this paper, a robust observer design method for nonlinear multi input multi-output(MINO) plants is presented. This method enables the extension of the time delay observer (TDO) for nonlinear SISO plants in the phase variable form to MIMO plants. The designed TDO reconstructs the states of the plant expressed in the generalized observability canonical form (GOBCF), yet requiring neither the transformation of a plant, nor the real time computation coordinates, the observer turned out to be computationally efficient and easy to design for nonlinear MIMO plants. In a simulation of a two-link manipulator with flexible joints, the control performances using TDO appeared to be similar to those using actual states and superior to those using numerical differentiation. Finally, in an experiment with a robot, it was confirmed that the TDO reconstructs the states reliability and TDO can be effectively used in a real closed-loop system.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.209-214
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• 1998

In this paper, we are dealing with the problem of controlling unknown nonlinear dynamical system by using neural networks. A novel error self-recurrent(ESR) neural model is presented to perform black-box identification. Through the various outcome of the experiment, a new neural network is seen to be considerably faster than the BP algorithm and has advantages of being less affected by poor initial weights and learning rate. These characteristics make it flexible to design the controller in real-time based on neural networks model. In addition, we design an adaptive PID controller that Keyser suggested by using ESR neural networks, and present a method on the implementation of adaptive controller based on neural network for practical applications. We obtained good results in the case of robot manipulator experiment.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.963-968
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• 1990

An iterative learning control scheme for tracking control of a class of uncertain nonlinear systems is presented. By introducing a model reference adaptive controller in the learning control structure, it is possible to achieve zero tracking of unknown system even when the upperbound of uncertainty in system dynamics is not known apriori. The adaptive controller pull the state of the system to the state of reference model via control gain adaptation at each iteration, while the learning controller attracts the model state to the desired one by synthesizing a suitable control input along with iteration numbers. In the controller role transition from the adaptive to the learning controller takes place in gradually as learning proceeds. Another feature of this control scheme is that robustness to bounded input disturbances is guaranteed by the linear controller in the feedback loop of the learning control scheme. In addition, since the proposed controller does not require any knowledge of the dynamic parameters of the system, it is flexible under uncertain environments. With these facts, computational easiness makes the learning scheme more feasible. Computer simulation results for the dynamic control of a two-axis robot manipulator shows a good performance of the scheme in relatively high speed operation of trajectory tracking.