• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.5
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• pp.852-857
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• 2008

A new adaptive neuro-control algorithm for a SISO strict-feedback nonlinear system is proposed. All the previous adaptive neural control algorithms for strict-feedback nonlinear systems are based on the backstepping scheme, which makes the control law and stability analysis very complicated. The main contribution of the proposed method is that it demonstrates that the state-feedback control of the strict-feedback system can be viewed as the output-feedback control problem of the system in the normal form. As a result, the proposed control algorithm is considerably simpler than the previous ones based on backstepping. Depending heavily on the universal approximation property of the neural network (NN), only one NN is employed to approximate the lumped uncertain system nonlinearity. The Lyapunov stability of the NN weights and filtered tracking error is guaranteed in the semi-global sense.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2146-2148
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• 2002

In this paper, PID control method using genetic algorithm to control the nonlinear multivariable system is presented. Genetic algorithms are global search techniques for nonlinear optimization. For experiment, the x-y rod balancing system with driver circuit board is fabricated. Experiments such as angle and position control for system are performed. The validity and control performance of the GA-based PID controller are confirmed by experimental results.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.161-164
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• 1996

The authors have recently proposed a new method for identifying Volterra kernels of nonlinear control systems by use of M-sequence and correlation technique. A specially chosen M-sequence is added to the nonlinear system to be identified, and the crosscorrelation function between the input and output is calculated. Then every crosssection of Volterra kernels up to 3rd order appears at a specified delay time point in the crosscorrelation. This method is applied to a saturation-type nonlinear feedback control system of mechanical-electrical servo system having torque saturation nonlinearity. Simulation experiments show that we can obtain Volterra kernels of saturation-type nonlinear system, and a good agreement is observed between the observed output and the calculated one from the measured Volterra kernels.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.144-149
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• 1993

This paper discusses a design of a nonlinear control for a class of single-input double-output nonlinear mechanical systems. When conventional linearization methods are applied to the mechanical systems, some problems of oscillation and unstable phenomena arise. The proposed nonlinear control system resolves these problems. In this design the eigenvalues of the closed-loop nonlinear system are assigned to desired locations and local asymptotic stability of the closed-loop system. is guaranteed. The design method is applied to an inverted pendulum system with a moving weight mechanism. Experimental results show that the proposed nonlinear controller is more effective for stability than the usual linear controller.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.4
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• pp.142-147
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• 2000

An overhead crane system which transports an object by girder motion, trolley motion, and hoist motion becomes a nonlinear system because the length of a rope changes. To develope the position control algorithm for the nonlinear crane systems, we apply a nonlinear optimal control method which uses forward and backward difference methods and obtain optimal inputs. This method is suitable for the overhead crane system which is characterized by the differential equation of higher degree and swing motion. From the results of computer simulation, it is founded that the position of the overhead crane system is controlled, and the swing of the object is suppressed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.8
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• pp.1188-1194
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• 1997

In this paper, we design output feedback nonlinear dynamic control law by using state feedback nonlinear dynamic compensator and PI observer and show that the controller can stabilize globally and asymptotically a class of nonlinear systems with mismatched uncertainties. We also show that it is possible for a nonlinear system to use the output of PI observer in place of state variables in case that the nonlinear dynamic control law is used, similarly as in the linear system. The effectiveness of the proposed control law is demonstrated by a numerical simulation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.8
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• pp.1184-1184
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• 1997

In this paper, we design output feedback nonlinear dynamic control law by using state feedback nonlinear dynamic compensator and PI observer and show that the controller can stabilized globally and asymptotically a class of nonlinear systems with mismatched uncertainties. We also show that it is possible for a nonlinear system to use the output of PI observer in place of state variables in case that the nonlinear dynamic control law is used, similarly as in the linear system. The effectiveness of the proposed control law is demonstrated by a numerical simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.979-984
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• 2005

In this study, we suggest a tilt rotor aircraft and attempt to apply a nonlinear model matching control method for its maneuver. The proposed method is very simple and useful to construct the control law for the complicated nonlinear system such as aircraft motion.

• The KIPS Transactions:PartA
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• v.8A no.1
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• pp.56-62
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• 2001

This paper presents a neural network based variable structure control scheme for nonlinear systems. In this scheme, a set of local variable structure control laws are designed on the basis of the linear models about preselected representative points which cover the range of the system operation of interest. From the combination of the set of local variable structure control laws, neural networks infer the approximate control input in between the operating points. The neural network based variable structure control alleviates the effects of model uncertainties, which cannot be compensated by the control techniques using feedback linearization. It also relaxes the discontinuity in the system’s behavior that appears when the control schemes based on the family of the linear models are applied to nonlinear systems. Simulation results of a ball and beam system, to which feedback linearization cannot be applied, demonstrate the feasibility of the proposed method.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.4
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• pp.40-47
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• 2001

In this pater, the QLQG/LTR control method is applied for the position control of the nonlinear timing belt driving sys-tem. Parameters fo the plant are identified by genetic algorithm and nonlinear elements, such as Coulomb friction and dead-zone, and quasi-linearized by RIDE method. Comparing with the LQG/LTR contro. the QLQG/LTR has similar structures of the LQG/LTR, but this method can consider nonlinear effects in designing the controller. Thus, the QLQG/LTR control system is robust to hard nonlinearities such as Coulomb friction, dead-zone, etc. Forma given hard non-linear system through experiments, it is shown that the tracking performance of the QLQG/LTR control system can be very improved that the LQF/LTR control system.