• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.206-211
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• 1993

This paper presents a new identification method which utilizes fuzzy inference in parameter identification. The proposed system has an additional control loop where a real plant is replaced by a plant model. The control system to be designed is to satisfy the following specifications: 1) It has zero steady-state error. 2) It has adequate damping characteristics. 3) 1),2) satisfied, it has a shortest rise-time. Fuzzy rules describe the relationship between comparison results of the features and magnitude of modification in the model parameter values. This method is effective in auto-tuning because the response of the closed loop is verified. The proposed method is tested in simulation for several plants with high-order lags and dead-times.

• Transactions of The Korea Fluid Power Systems Society
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• v.7 no.4
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• pp.23-31
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• 2010

As the analysis and design technologies for electro-magnetic actuation has advanced over the years, proportional solenoid valve is gaining acceptance in wide range of industrial and commercial applications because of its superior characteristics over the conventional AOV or MOV, such as improved performance, reduced maintenance costs. This research deals with the position controller design of two-stage flow control solenoid valve. Investigation of steady-state characteristics and dynamic model identification for pilot disc is performed. Least square method to minimize the error magnitude of frequency response between the closed-loop and target system is applied to the design of PI-controller gains. From the experiments of step and frequency response, it is concluded that the controller meets the performance specification of target system, which verifies the usefulness of controller design method for proportional solenoid valve.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.2
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• pp.248-254
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• 2018

In this paper, a Monte Carlo-based Recursive Least Square(MC-RLS) method is presented to directly identify the inverse model of the dynamical system. Although a RLS method has been used for the identification based on the deterministic data in the closed loop controlled form, it would be better for RLS to identify the model with random data. In addition, the inverse model obtained by inverting the identified forward model may not work properly. Therefore, MC-RLS can be used for the inverse model identification without proceeding a numerical inversion of an identified forward model. The performance of the proposed method is verified through experimental studies on a control moment gyroscope.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.489-493
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• 1989

In this paper a new approach to adaptive control using a combination of both direct and indirect methods has been proposed. Based on the estimates of the plant parameters and the current values of the control parameters, closed-loop estimation errors .epsilon.$_{\theta}$(t) and .epsilon.$_{k}$(t) are defined. These in turn are used in the adaptive laws for updating both identification as well as control parameters. The global uniform stability of the overall system is shown by constructing a Lyapunov function.n.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.664-669
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• 2001

Continuous-time controller design is proposed using feedback system identification in frequency domain. System stability imposed by a new controller is checked in the function of a conventional closed-loop system, instead of a poorly modeled plant due to non-linearity and disturbance as well as unstable components, etc. The stability of the system is evaluated in view of Nyquist stability. All the equations are formulated in the framework of the discrete-time system. Simulation results are shown on the plant with input saturation and DC disturbance.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.99-104
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• 2001

Discrete-time controller design is proposed using feedback system identification in frequency domain. System Stability imposed by a new controller is checked in the function of a conventional closed-loop system, instead of a poorly modeled plant due to non-linearity and disturbance as well as unstable components, etc. The stability of the system is evaluated in view of Popov criterion. All the equations are formulated in the framework of the discrete-time system. Simulation results are shown on the plant with input saturation components, DC disturbance and a pure integration.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.11
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• pp.928-934
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• 2002

A natural way to cope with fault tolerant control (FTC) problems is to modify the control parameters according to an online identification of the system parameters when a fault occurs. However. due to not only difficulties Inherent to the online multivariable identification in closed-loop systems, such as modeling errors, noise or the lack of excitation signals, but also long time requirement to identify the post-fault system and implemeutation of control problems during the identification process, we propose an alternative approach based on the observer-based fault detection and isolation (FDI) and model reference adaptive control (MRAC). The proposed robust fault diagnosis method is based on a bank of observers. We also propose a model reference adaptive control with changeable reference models according to the occurred faults. Simulation results of a flight control example show the validity and applicability of the proposed algorithms.

• Journal of Mechanical Science and Technology
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• v.17 no.12
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• pp.1855-1866
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• 2003

This paper discusses an entire procedure for a robust controller design and its implementation of an AMB (active magnetic bearing) spindle, which is part II of the papers presenting details of system modeling and robust control of an AMB spindle. Since there are various uncertainties in an AMB system and reliability is the most important factor for applications, robust control naturally gains attentions in this field. However, tight evaluations of various uncertainties based on experimental data and appropriate performance weightings for an AMB spindle are still ongoing research topics. In addition, there are few publications on experimental justification of a designed robust controller. In this paper, uncertainties for the AMB spindle are classified and described based on the measurement and identification results of part I, and an appropriate performance weighting scheme for the AMB spindle is developed. Then, a robust control is designed through the mixed ${\mu}$ synthesis based on the validated accurate nominal model of part I, and the robust controller is reduced considering its closed loop performance. The reduced robust controller is implemented and confirmed with measurements of closed-loop responses. The AMB spindle is operated up to 57,600 rpm and performance of the designed controller is compared with a benchmark PID controller through experiments. Experiments show that the robust controller offers higher stiffness and more efficient control of rigid modes than the benchmark PID controller.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.153-156
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• 1999

The technique is reported of identifying parameters in off-line process. The technique demands that closed-loop system consists of a reference and two-degree-of-freedom controllers (TDFC) in real process. A model process is the same as the real process except their parameters. Deviations are differences between the reference and the output of the plant or the model. The technique is based on minimizing identification error between the two deviations. The parameter differences between the plant and the model are characterized of mean value and of variance which are derived from the identification error. Consequently, the algorithm which identifies the unknown plant parameters is shown by minimizing the mean value and the variance, respectively, within double convergence loops. The technique is applied to course change of a ship. The plant deviation at the first trial is shown to occur in replacing the nominal parameters by the default parameters. The plant deviation at the second trial is shown to not occur in replacing the nominal parameters by the identified parameters. Hence, the identification technique is confirmed to be feasible in the real field.

• Transactions of the Korean Society of Mechanical Engineers
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• v.14 no.3
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• pp.513-525
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• 1990

This paper presents Adaptive Robust Servocontrol(ARSC) scheme, which is an explicit(or indirect) pole-assignment adaptive algorithm with the property of "robustness". It guarantees asymptotic regulation and tracking in the presence of finite parameter perturbations of the unknown plant(or process) model. The controller structure is obtained by transforming a robust control theory into an adaptive control version. This controller structure is combined with the model estimation algorithm which includes a dead-zone for bounded noise. It is proved theoretically that this combination of control and identification is globally convergent and stable. It is also shown, through a real-time simulation study, that the desired closed-loop poles of the augmented system can be assigned directly, and that the adjustment mechanism of the scheme tunes the controller parameters according to the assigned closed-loop poles.oop poles.