• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.437-440
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• 1989

In the paper a failure detection and diagnosis method of a stochastic system is proposed. It is based on the comparison of the moving averages generated from outputs of the real plant and a modeled normal plant. The proposed method allows us to locate the failed sensor and can be efficiently used for the failure detection and diagnosis of a plant with many sensors.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.550-553
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• 1986

This paper presents a procedure for the time-scale separation and a design method for the sub-optimal composite regulator and Kalman filter of the large-scale discrete stochastic system with two time-scale properties. Provided that the fast sub-system is asymptotically stable, the reduced-order regulator and Kalman filter for the slow sub-system with dominant modes is designed as a sub-optimal regulator for the system.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.168-173
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• 1987

The optimal Input design problem for linear system Which have the common parameters in the system and noise transfer functions. Exploiting the assumed Model structure and deriving the information matrix structure in detail, D-optimal open-loop stochastic input can be realized as an ARMA process under the Input or output variance constraints. In spite of the reduced order, It Is necessary to develop an efficient algorithms for the optimation with respect to the .rho..

• The Transactions of the Korean Institute of Electrical Engineers
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• v.33 no.9
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• pp.372-376
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• 1984

This paper discusses on the stochastic adaprive control which uses a least squares method in the parameter adaptation law. Especially we study on the reason why existing methods have adopted modified least squares methods. After examining the performances of these methods for time-varying systems, we propose a new method to deal with such a situation, study on the stability problem, and finally show the effectiveness of the method with a computer simulation example.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.107-110
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• 1996

Continuing advances in the formulation and solution of risk-sensitive control problems have reached a point at which this topic is becoming one of the more intriguing modern paradigms of feedback thought. Despite a prevailing atmosphere of close scrutiny of theoretical studies, the risk-sensitive body of knowledge is growing. Moreover, from the point of view of applications, the detailed properties of risk-sensitive design are only now beginning to be worked out. Accordingly, the time seems to be right for a survey of the historical underpinnings of the subject. This paper addresses the beginnings and the evolution, over the first quarter-century or so, and points out the close relationship of the topic with the notion of optimal cost cumulates, in particular the cost variance. It is to be expected that, in due course, some duality will appear between these notions and those in estimation and filtering. The purpose of this document is to help to lay a framework for that eventuality.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1225-1228
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• 1987

It is shown that the singularly perturbed continuous-time system is led to two different discrete versions according to slow or fast sampling rates. The design of stabilizing feedback control of singularly perturbed discrete-time stochastic system is decomposed into the design of slow and fast controllers, which is combined to form the composite control. Composite control law is derived for the case of both single rate measurement and multirate measurement.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.152-155
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• 1994

The presence of joint elasticity or the arm flexibility causes low damped oscillatory position error along a desired trajectory. We utilize a stochastic model for describing the fast dynamics and the approximation error. A second order shaping filter is synthesized such that its spectrum matches that of the fast dynamics. Augmenting the state vector of slow part with that of shaping filter, we obtain a nonlinear dynamics to which a Gaussian white noise is injected. This modeling approach leads us to the design of an extended Kalman filter(KEF) and a linear quadratic Gaussian(LQG) control scheme. We present the simulation results of this control method. The simulation results show us that our Kalman filtering approach is one of prospective methods in controlling the flexible arms.

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.444-452
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• 2008

We propose an intelligent predictive control approach for a nonlinear networked control system (NCS) with time-varying delay and random observation. The control is given by the sum of a nominal control and a corrective control. The nominal control is determined analytically using a linearized system model with fixed time delay. The corrective control is generated online by a neural network optimizer. A Markov chain (MC) dynamic Bayesian network (DBN) predicts the dynamics of the stochastic system online to allow predictive control design. We apply our proposed method to a satellite attitude control system and evaluate its control performance through computer simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.8
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• pp.1400-1406
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• 2016

This paper presents a new adaptive converter control approach for electric motor systems whose voltage source is excited from photovoltaic (PV) power generators. First, an electric model is represented with dynamic states and output velocity of such DC motor systems. We propose a hybrid converter control law in which a state feedback control is applied as an auxiliary control framework. Moreover, control parameter estimation is derived to realize adaptive converter systems for effective control performance against stochastic PV power excitation in practice. We carry out stability analysis for such converter system by using a well-known eigenvalue theory. Lastly, numerical simulation is conducted to test reliability of the proposed converter control approach and prove its superiority in the control point of view.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.186-193
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• 2008

The Internet's low cost and ubiquity present an attractive option for real-time distributed control of processes on the factory floor. When integrated with the Internet, the LonWorks open control network can give ubiquitous accessibility with the distributed control nature of information on the factory floor. One of the most important points in real-time distributed control of processes is timely response. There are many processes on the factory floor that require timely response. However, the uncertain time delay inherent in the network makes it difficult to guarantee timely response in many cases. Especially, the transmission characteristics of the LonWorks/IP network show a highly stochastic nature. Therefore, the time delay problem has to be resolved to achieve high performance and quality of the real-time distributed control of the process in the LonWorks/IP Virtual Device Network (VDN). It should be properly predicted and compensated. In this paper, a new distributed control scheme that can compensate for the effects of the time delay in the network is proposed. It is based on the PID controller augmented with the Smith predictor and disturbance observer. Designing methods for output feedback filter and disturbance observer are also proposed. Tracking position control experiment of a geared DC Servo motor is performed using the proposed control method. The performance of the proposed controller is compared with that of the Internal Model Controller (IMC) with the Smith predictor. The result shows that the performance is improved and guaranteed by augmenting a PID controller with both the Smith predictor and disturbance observer under the stochastic time delay in the LonWorks/IP VDN.