• The Transactions of the Korean Institute of Electrical Engineers
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• v.35 no.5
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• pp.177-184
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• 1986

An effective cartesian coordinate model is presented to control a robot motion along a prescribed timebased hand trajectory in cartesian coordinates and to provide an adaptive feedback design approach utilizing self-tuning control methods without requiring a detailed mathematical description of the system dynamics. Assuming that each of the hybrid variable set of velocities and forces at the cartesian coordinate level is mutually independent, the dynamic model for the cartesian coordinate control is reduced to first-order SISO models for each degree of freedom of robot hand, including a term to represent all unmodeled effects, by which the number of parameters to be identified is minimized. The self-tuners are designde to minimize a chosen performance criterion, and the computed control forces are resolved into applied joint torques by the Jacobian matrix. The robustness of the model and controller is demonstrated by comparing with the other catesian coordinate controllers.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.4
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• pp.364-370
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• 1990

In this paper, we propose a self-tuning PID controller for unknown systems with time-varying delay. Using pole placement equations, we derive the controller that can be extended to the multi-step time delay case. The time-varying delays are estimated by a prediction error delay method using multiple predictors. Since the order of the estimation vector is not increased, the persistant exciting condition of control input is alleviated. Since the least square method gives biased parameter estimates for colored noise cases, the recursive instrumental variable method is used to estimate system parameters. The computational burden of the proposed method is less than the conventional adaptive methods. Computer simulations are performed to illustrate the efficiency of the proposed method.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.5
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• pp.267-275
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• 2012

In this paper, we present the model-based autonomic computing framework for a cyber-physical system which provides a self-management and a self-adaptation characteristics. A development process using this framework consists of two phases: a design phase in which a developer models faults, normal status constrains, and goals of the CPS, and an operational phase in which an autonomic computing engine operates monitor-analysis-plan-execute(MAPE) cycle for managed resources of the CPS. We design a hierachical architecture for autonomic computing engines and adopt the Model Reference Adaptive Control(MRAC) as a basic feedback loop model to separate goals and resource management. According to the GroundVehicle example, we demonstrate the effectiveness of the framework.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.426-429
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• 1989

The robust self-tuning controller is designed which is guaranteed the asymptotic regulation and tracking in the presence of a bounded parameter perturbation. The global stability in the presence of a finite noise and disturbance is ensured. The controller has a error driven structure, and involves the common model of a disturbance and reference input in the internal model. The adaptive system tunes the controller parameters such that the quadratic performance index which involves a weighting factor is optimized.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.11
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• pp.1207-1218
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• 1990

The lack of persistent excitation (PE) can be the reason of freezing in the recursive least square estimators and the covariance windup in the exponential weighted least square estimators. We present a theoretical analysis of these phenomena and a simple method to check the exciting condition in real time. Using these results and under some conditions such as slowly time varying Plant and a tracking problem for set point, a robust self-tuning regulators without PE is proposed. In this algorithm, when PE is not satisfied, only plant gain is estimated, and then the system parameters are corrected by it. It is shown that the gain adaptive scheme makes the robustness to be improved against modeling error, off-set, and correlated noise etc, by the results of analysis and simulations.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.5
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• pp.225-234
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• 2000

In this paper, we present an nonlinear PID controller with network based compensator which consists of a conventional PID controller that controls the linear components and neuro-compensator that controls the output errors and nonlinear components. This controller is based on the Harris's concept where he explained that the adaptive controller consists of the PID control term and the disturbance compensating term. The resulting controller's architecture is also found to be very similar to that of Wang's controller. This controller adds a self-tuning ability to the existing PID controller without replacing it by compensating the output errors through the neuro-compensator. Various simulations and comparative studies have proven that the proposed nonlinear PID controller produces superior results to other existing PID controllers. When applied to an actual magnetic levitation system which is known to be very nonlinear, it has also produced an excellent results.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.105-109
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• 2001

This paper discuss the real-time self-tuning learning control based on evolutionary computation, which proves its the superiority in the finding of the optimal solution at the off-line learning method. The individuals are reduced in order to learn the evolutionary strategy in real-time, and new method that guarantee the convergence of evolutionary mutations are proposed. It possible to control the control object varied as time changes. As the state value of the control object is generated, applied evolutionary strategy each sampling time because the learning process of an estimation, selection, mutation in real-time. These algorithms can be applied, the people who do not have knowledge about the technical tuning of dynamic systems could design the controller or problems in which the characteristics of the system dynamics are slightly varied as time changes.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.3
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• pp.25-34
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• 1992

This paper proposes a Self-Tuning control algorithm for tracking the reference trajectory by measuring the end-point of robot manipulator whose links are light and flexible, and the performance of it is tested through the computer simulation. As an object of system, a flexible robot manipulator with two-links is considered and an assumed mode shape method including gravity force is adopted to analyze the vibration modes for each links and dynamics equation is derived. The controller is designed as a combined form which consists of dynamic feedforward compensator and self-tuning feedback controller. The one supplies nominal torque and the other supplies variational torque to manipulator. Apart from the, K-incremental predictor is also proposed in order to eliminate the offset error. and it shows that the result of simulation adapted well to load change and rapid velocity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.173-187
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• 2022

Recent studies have focused on self-management of hypertension using smart devices (cellular phones, tablets, watches). It has proven to be an effective tool for early detection and control of high Blood Pressure (BP) without affecting patients' daily routines. This systematic review surveys the existing self-monitoring systems, evaluate their effectiveness and compares the different approaches. We investigated the current systems in terms of various attributes, including methods used, sample size, type of investigation, inputs/ outputs, rate of success in controlling BP, group of users with higher response rate and beneficiaries, acceptability, and adherence to the system. We identified some limitations, shortcomings, and gaps in the research conducted recently studying the impact of mobile technology on managing hypertension. These shortcomings can generate future research opportunities and enable it to become more realistic and adaptive. We recommended including more observable factors and human behaviors that affect BP. Furthermore, we suggested that vital monitoring/logging and medication tuning are insufficient to improve hypertension control. There is also a need to observe and alter patient behavior and lifestyles.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.2
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• pp.168-177
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• 1996

In this paper, we propose an on-line recognition system of chinese characters using an adaptive resonance theory-1(ART-1) neural network. Strokes, primitive components of chinese characters are usually warped into a cursive form and classifying them is very difficult. To deal with such cursive strokes, we use an ART-1 neural network that has the following advantages: (1) it automatically assembles similar patterns together to form classes in a self-organized manner: (2) it directly accesses the recognition codes corresponding to binary input patterns after self-stabilizing; (3) it doesn't tends to get trapped in local minima, or globally incorrect solutions. A database for character recognition also dynamically constructed with generalized character lists, and a new character can be included simply by adding a new sequence to the list. Character recognition is achieved by traversing the chinese datbase with a sequence of recognized strokes and positional relations between the strokes. To verify the performance of the system. We tested it for 1800 daily-used basic chinese second per character. This results suggest that the proposed system is pertinent to be put into practical use.