• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.2
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• pp.540-552
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• 1996

In this paper, a compensation method of disturbance using a disturbance observer is proposed for a force control of a pneumatic robot manipulator. The generated torque by a pneumatic actuator can be estimated based on the pressure signals. The inner torque control system is constructed by feeding back the generated torque to improve the dynamic characteristics of the actuator. In order to reduce the influence of disturbances comprising friction torque, parameter variations of plant and environment and so on, the reaction torque control system is constructed with a disturbance observer which estimates the disturbances based on the reference input to the inner torque control system and the reaction torque sensed with a forced sensor. From some simulations and experiments, it is confirmed that the proposed control system is effective to improve the robustness for the friction torque and the parameter change of object in the force control of a pneumatic robot manupulator.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.4
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• pp.243-250
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• 2003

In this paper, the speed controller of permanent-magnet synchronous motor (PMSM) using the RBF neural (NN) disturbance observer is proposed. The suggested controller is designed using the input-output feedback linearization technique for the nominal model of PMSM and incorporates the RBF NN disturbance observer to compensate for the system uncertainties. Because the RBF NN disturbance observer which estimates the variation of a system parameter and a load torque is employed, the proposed algorithm is robust against the uncertainties of the system. Finally, the computer simulation is carried out to verify the effectiveness of the proposed method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.463-466
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• 2002

The Field Robot means the machinery applied for outdoor tasks in construction, agriculture and undersea etc. In this paper, to field-robotize a hydraulic excavator, we have proposed a robust and systematic controller design method. Disturbance observer is used as inner controller to reshape the excavating system into the linear dynamics of nominal model by compensating coupled nonlinear terms, model uncertainties and external load variations. Using the linear model that is obtained through off-line system identification, a H control scheme is applied to construct a disturbance observer and a servo-controller systematically.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.55 no.4
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• pp.402-410
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• 2019

This paper deals with the disturbance observer (DOB) based sliding mode control (SMC) for a DC motor to control motor rotating speed precisely and to ensure strong robustness against disturbance including load torque and parameter variation. The reason of steady state error in speed on conventional SMC without DOB is analyzed in detail. Especially, the suggested DOB is designed to prevent measuring noise and harmonics caused by derivative operation on rotating speed. The control performance of the DOB based SMC is evaluated by the various simulations. The simulation results showed that the DOB based SMC had more robust performance than the SMC system without DOB. Especially, precise speed control was possible even though motor parameter variation and load torque was added to the system.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.6
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• pp.397-402
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• 2016

This paper proposes a robust tracking control for constrained uncertain linear systems by combining a disturbance observer (DOB) and linear matrix inequality (LMI) based state feedback control. To this end, the state feedback control is designed for the nominal system and then a DOB based feed-forward control is added to reject uncertainties. In doing so, the DOB and state feedback controller are joined in a way that the combined control satisfies the input constraints and closed loop stability is guaranteed. Simulation results are provided to show that the proposed control scheme successfully stabilizes uncertain systems.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.5
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• pp.299-307
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• 2003

The local structure of CMAC neural networks (NN) results in better and faster controllers for nonlinear dynamical systems. In this paper, we propose a CMAC NN-based disturbance observer and its corresponding controller for a flexible joint robot. The CMAC NN-based disturbance observer compensates for the parametric uncertainties and the external disturbances throughout the entire mechanical system. Finally, a simulation result is given to demonstrate the effectiveness of proposed design method's robust tracking performance.

• Journal of Electrical Engineering and Technology
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• v.2 no.2
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• pp.280-285
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• 2007

This paper presents a robustly adaptive flux observer for speed-sensorless induction motor control. The proposed approach employs additional robustifying signals to cope with the parametric uncertainties instead of designing an estimator, which has been normally used in power electronic drives. For that, the sliding-mode like adaptive controls are designed and their gain parameters are determined so that the observer dynamics are stable in the sense of Lyapunov, and furthermore they can guarantee the robustness against parametric uncertainties in induction motor systems. Estimated rotor speed is to be used to generate feedback control signal for the speed sensorless vector control system. To show the validity and efficiency of the proposed system, simulation results are presented.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2320-2322
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• 2001

This paper describes the design of a robust adaptive neural-net(NN) observer for uncertain nonlinear dynamical system. The Lyapunov synthesis approach is used to guarantee a uniform ultimate boundedness property of the state estimation error, as well as of all other signals in the closed-loop system. Especially, for reducing the dynamic oder of the observer, we propose a new method in which no strictly positive real(SPR) condition is needed with on-line estimation of weights of the NNs. No a priori knowledge of an upper bounds on the uncertain terms is required. The theoretical results are illustrated through a simulation example.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.1 s.232
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• pp.59-66
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• 2005

In this paper, a robust stationary Kalman filter is designed by minimizing selected performance indices so that it is less sensitive to uncertainties. The uncertainties include not only stochastic factors such as process noise and measurement noise, but also deterministic factors such as unknown initial estimation error, modeling error and sensing bias. To reduce the effect on the uncertainties, three performance indices that should be minimized are selected based on the quantitative error analysis to both the deterministic and the stochastic uncertainties. The selected indices are the size of the observer gain, the condition number of the observer matrix, and the estimation error variance. The observer gain is obtained by optimally solving the multi-objectives optimization problem that minimizes the indices. The robustness of the proposed filter is demonstrated through the comparison with the standard Kalman filter.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.115-120
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• 2004

This paper concerns the active aeroelastic control of flapped wing systems exposed to blast and/or the sonic boom in an incompressible flow field. This is achieved via implementation of a robust estimation capability (sliding mode observer: SMO), and of the use of the deflected flap as to suppress the flutter instability or enhance the subcritical aeroelastic response to blast loads. To this end, a control methodology using LQG(Linear Quadratic Gaussian) in conjunction with SMO is implemented, and its performance toward suppressing flutter and reducing the vibrational level in the subcritical flight speed range is demonstrated. Moreover, its performances are compared to the ones provided via implementation of conventional LQG with Kalman filter.