• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.24-24
• /
• 2000

This paper proposes a design method of sliding mode observer for SISO linear systems with a disturbance input. We first construct an observer with a constant gain matrix, a feedforward injection map and an external feedforward compensation signal input. Using the second Lyapunov method, we present a sufficient condition for the existence of sliding mode observer. The proposed observer guarantees that the state error trajectories enter a certain region in finite time and remain inside thereafter.

• Journal of Drive and Control
• /
• v.14 no.2
• /
• pp.45-51
• /
• 2017

Semi-submersible drilling rigs are offshore plants that perform functions such as ocean exploration for oil and gas acquisition, drilling and production, and storage and unloading of crude oil and gas. Semi-submersible drilling rigs use watertight dampers as emergency buoyancy holders. Since the watertight damper is an emergency shutoff device, it is mainly driven by a pneumatic driving system that can operate without a power supply. The pneumatic driving system has highly non-linear characteristics due to compressibility of air and external disturbance such as static and Coulomb friction. In this paper, a new control algorithm is proposed for a watertight damper driving system based on the sliding mode control with a disturbance observer. To evaluate control performance and robust stability of the designed controller, the control results were compared with the results obtained using the state feedback controller. As a result, it was confirmed that the pneumatic driving system for driving the watertight damper using the sliding mode controller with a disturbance observer can obtain excellent control performance against the parameter changes and the disturbance input.

• Journal of Drive and Control
• /
• v.14 no.2
• /
• pp.9-15
• /
• 2017

The steering systems of all-terrain cranes have been developed with various control strategies for the stability and drivability. To optimally control the input steering angle, an accurate mathematical model that represents the actual crane dynamics is required. The derivation of an accurate mathematical model to optimally control the steering angle, however, is difficult since the steering-control strategy generally varies with the magnitude of the crane's longitudinal velocity, and the postures of the crane's working parts vary while it is being driven. To address this problem, this paper proposes an automatic steering-control algorithm that is based on the MPC (model predictive control) with a disturbance observer for all-terrain cranes. The designed disturbance observer of this study was used to estimate the error between the base steering model and the actual crane. A model predictive controller was used for the computation of the optimal steering angle, along with the use of the base steering model with an estimated uncertainty. Performance evaluations of the designed control algorithms were conducted based on a curved-path scenario in the Matlab/Simulink environment. The performance-evaluation results show a sound reference-path-tracking performance despite the large uncertainties.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.29 no.4A
• /
• pp.363-369
• /
• 2004

We propose, for the first time to our knowledge, a novel gain-clamping method for EDFA in WDM add/drop networks by introducing a disturbance observer technique. The control input signal for gain-clamping is composed of a nominal control signal and an additional control signal of compensating the gain fluctuations caused by channel add/drops. Based on disturbance observer technique, we designed the additional control signal such that it has the compensating information of estimated disturbance resulted from channel add/drops. The circuit for generating additional control signal can easily be implemented by using simple electronic devices. We proved the superiority of the new technique over the previous ones by showing simulation results of minimized dips and spikes that appear in power profile of EDFA in the process of channel add/drops.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.48 no.8
• /
• pp.996-1003
• /
• 1999

This paper propose a position-speed controller with an estimator which can estimate states and disturbance. The overall control system consists of two parts: the position-speed controller and an estimator. The Kalman filter applied as state-feedback controller is an optimal state estimator applied to a dynamic system that involves random perturbations and gives a linear, unbiased and minimum error variance recursive algorithm to optimally estimate the unknown state. Therefore, we consider the error problem about the servo system modeling and the measurement noise as a stochastic system and implement a optimal state observer, and enhance the estimate performance of position and speed using that. Using two-degree-of freedom(TDOF) conception, we design the command input response and the closed loop characteristics independently. The servo system is to improve the closed loop characteristics without affecting the command imput response. The characteristics of the closed loop system is improved by suppressing disturbance torque effectively with the disturbance observer using a inverse-transfer matrix. Therefore, the performance of overall position-speed controller is enhanced. Finally, the performance of the proposed controller is exemplified by some simulations and by applying the real servo system.

• Proceedings of the KIEE Conference
• /
• 2003.11c
• /
• pp.380-383
• /
• 2003

This paper proposes a new and simple input prediction method for robust servo system. This servo system uses robust tracking control system based on both Coprime Factorization(CF) and Zero Phase Error Tracking control system. The CF control system can be designed simply and systematically. Moreover, this system has not only stability but also robustness and disturbance rejection ability The optical disk tracking servo system can detect only the tracking error. So the new and simple input prediction system proposed in this paper estimates the reference input signal from the tracking error. Numerical simulation results show that the proposed method is effective.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.57 no.6
• /
• pp.915-923
• /
• 2008

This paper focuses on optimal tuning of nonlinear parameters of a dual-input power system stabilizer(dual-input PSS), which can improve the system damping performance immediately following a large disturbance. Until recently, various PSS models have developed to bring stability and reliability to power systems, and some of these models are used in industry applications. However, due to non-smooth nonlinearities from the interaction between linear parameters(gains and time constants of linear controllers) and nonlinear parameters(saturation output limits), the output limit parameters cannot be determined by the conventional tuning methods based on linear analysis. Only ad hoc tuning procedures('trial and error' approach) have been used. Therefore, the steepest descent method is applied to implement the optimal tuning of the nonlinear parameters of the dual-input PSS. The gradient required in this optimization technique can be computed from trajectory sensitivities in hybrid system modeling with the differential-algebraic-impulsive-switched(DAIS) structure. The optimal output limits of the dual-input PSS are evaluated by time-domain simulation in both a single machine infinite bus(SMIB) system and a multi-machine power system in comparison with those of a single-input PSS.

• Journal of Advanced Marine Engineering and Technology
• /
• v.33 no.8
• /
• pp.1196-1202
• /
• 2009

In this paper, an estimator design of underwater environment changes is proposed by using observer techniques for ROV control system. The underwater environment changes are considered as an external disturbance term for ROV model and it is added into the input term of ROV model. To estimate the environment changes, a PI observer which does not effect the external disturbance input term is proposed. To verify the effectiveness of the proposed method, the step and the sinusoidal environment changes are considered in simulation. The proposed method will be applied to design the haptic controller for ROV in future.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.15 no.2
• /
• pp.497-506
• /
• 1991

In this paper, a new construction for training simulator of R/C helicopter based on two types of servo controller is proposed. Two modified algorithms (algorithm I and II) for servo controller design are presented. Algorithm I is developed by adopting Davison's method in the case that the expressions for the homogeneous differential equations of reference input and disturbance are different types, and algorithm II is done by considering error weighting function for the servo controller of algorithm I . The linear fractional transformation method is incorporated in both design methods in order to assign the closed loop poles of the servo system in a specified region. The helicopter simulator is composed by the gimbals with two freedom of rolling and pitching. The reliability and validity for the design methods of the proposed servo controller are investigated through the practical experiment for the simulator by using 16bits micro-computer with A/D and D/A converters. It can be observered from the experimental results that the proposed servo controller is applicable to practical plants since the simulator is robust for the arbitrary disturbance and it follows to the given reference input without significant steady state error.

• Proceedings of the KIEE Conference
• /
• 2006.07d
• /
• pp.1868-1870
• /
• 2006

Neural network is used in many fields of control systems, but input-output patterns of a control system are not easy to be obtained and by using as single feedback neural network controller. And also it is difficult to get a satisfied performance when the changes of rapid load and disturbance are applied. To resolve those problems, this paper proposes a new algorithm which is the neural network controller. The new algorithm uses the neural network instead of activation function to control object at the output node. Therefore, control object is composed of neural network controller unifying activation function, and it supplies the error back propagation path to calculate the error at the output node. As a result, the input-output pattern problem of the controller which is resigned by the simple structure of neural network is solved, and real-time learning can be possible in general back propagation algorithm. Application of the new algorithm of neural network controller gives excellent performance for initial and tracking response and it shows the robust performance for rapid load change and disturbance. The proposed control algorithm is implemented on a high speed DSP, TMS320C32, for the speed of 3-phase induction motor. Enhanced performance is shown in the test of the speed control.