• Journal of Institute of Control, Robotics and Systems
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• v.16 no.10
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• pp.927-932
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• 2010

Estimation methods of motion intention from bio-signal present challenges in man machine interaction(MMI) to offer user's command to machine without control of any devices. Measurements of meaningful bio-signals that contain the motion intention and motion estimation methods from bio-signal are important issues for accurate and safe interaction. This paper proposes a novel motion estimation sensor based on a geometrical muscle changes, and a motion estimation method using the sensor. For estimation of the motion, we measure the circumference change of the muscle which is proportional to muscle activation level using a flexible piezoelectric cable (pMAS, piezo muscle activation sensor), designed in band type. The pMAS measures variations of the cable band that originate from circumference changes of muscle bundles. Moreover, we estimate the elbow motion by applying the sensor to upper limb with least square method. The proposed sensor and prediction method are simple to use so that they can be used to motion prediction device and methods in rehabilitation and sports fields.

• Journal of the Korea Concrete Institute
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• v.18 no.4 s.94
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• pp.543-552
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• 2006

The current design for crack width control in concrete bridges is incomplete in analytical models. As one of the important serviceability limit states, the crack width be considered with the quantitative prediction of the initiation and propagation of corrosion and corrosion-induced cracking. A serviceability limit state of cracking can be affected by the combined effects of bond, slip, cracking, and corrosion of the reinforcing elements. Considering life span of concrete bridges, an improved prediction of crack width affected by time-dependent general corrosion has been proposed for the crack control design. The developed corrosion models and crack width prediction equation can be used for the design and the maintenance of prestressed and non-prestressed reinforcements by varying time, w/c, cover depth, and geometries of the sections. It can also be used as the rational criteria for the maintenance of existing concrete bridges and the prediction of remaining life of concrete structures.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1343-1346
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• 2005

In the cold rolling mill, coil breakage that generated in rolling process makes the various types of troubles such as the degradation of productivity and the damage of equipment. Recent researches were done by the mechanical analysis such as the analysis of roll chattering or strip inclining and the prevention of breakage that detects the crack of coil. But they could cover some kind of breakages. The prediction of Coil breakage was very complicated and occurred rarely. We propose to build effective prediction modes for coil breakage in rolling process, based on data mining model. We proposed three prediction models for coil breakage: (1) decision tree based model, (2) regression based model and (3) neural network based model. To reduce model parameters, we selected important variables related to the occurrence of coil breakage from the attributes of coil setup by using the methods such as decision tree, variable selection and the choice of domain experts. We developed these prediction models and chose the best model among them using SEMMA process that proposed in SAS E-miner environment. We estimated model accuracy by scoring the prediction model with the posterior probability. We also have developed a software tool to analyze the data and generate the proposed prediction models either automatically and in a user-driven manner. It also has an effective visualization feature that is based on PCA (Principle Component Analysis).

• Journal of ILASS-Korea
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• v.25 no.4
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• pp.188-195
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• 2020

To meet stringent emission regulations of automotive engines, fuel injection control techniques have advanced based on reliable and fast computing prediction models. This study aims to develop a reliable lightweight prediction model of fuel injection rates using a small number of input parameters and based on simple fluid dynamic theories. The prediction model uses the geometry of the injector nozzle, needle motion data, injection conditions and the fuel properties. A commercial diesel injector and US No. 2 diesel were used as the test injector and fuel, respectively. The needle motion data were measured using X-ray phase-contrast imaging technique under various fuel injection pressures and injection pulse durations. The actual injector rate profiles were measured using an injection rate meter for the validation of the model prediction results. In the case of long injection durations with the steady-state operation, the model prediction results showed over 99 % consistency with the measurement results. However, in the case of short injection cases with the transient operation, the prediction model overestimated the injection rate that needs to be further improved.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.444-447
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• 2004

A new approach to compute the control moves in Extended Dynamic Matrix Control (EDMC) is presented. In this approach, the number of variables, determined in the inner loop of the control algorithm using iterative methods, is reduced from P , the prediction horizon to M , the control horizon. Since M is usually much smaller than P , this modifies the control algorithm from computational point of view. To justify the modification, the computational requirements are compared to those of the existing EDMC algorithm.

• Journal of the Korea Concrete Institute
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• v.15 no.1
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• pp.87-94
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• 2003

Construction plan and strength control have limitations in construction production field because it is difficult to predict the form removal strength and development of specified concrete strength. However, we can have reasonable construction plan and strength control if prediction of concrete strength is available. In this study, firstly, the newly proposed strength prediction model with maturity method was compared with the logistic model to test the adaptability. Secondly, the determination of time of form removal was verified through the new strength prediction model. As the results, it is found that investigation of the activation energy that are used to calculate equivalent age is necessary, and new strength prediction model was proved to be more accurate in the strength prediction than logistic model in the early age. Moreover, the use of new model was more reasonable because it has low SSE and high decisive factor. If we adopt new strength prediction model at construction field, we can expect the reduced period of work through the reduced time of form removal.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.392-395
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• 2003

In the maritime container terminal, LMTT (Linear Motor-based Transfer Technology) is horizontal transfer system for the yard automation, which has been proposed to take the place of AGV (Automated Guided Vehicle). The system is based on PMLSM (Permanent Magnetic Linear Synchronous Motor) that is consists of stator modules on the rail and shuttle car (mover). Because of large variant of mover's weight by loading and unloading containers, the difference of each characteristic of stator modules, and a stator module's trouble etc., LMCPS (Linear Motor Conveyance Positioning System) is considered as that the system is changed its model suddenly and variously. In this paper, we will introduce the soft-computing method of a multi-step prediction control for LMCPS using DR-FNN (Dynamically-constructed Recurrent Fuzzy Neural Network). The proposed control system is used two networks for multi-step prediction. Consequently, the system has an ability to adapt for external disturbance, cogging force, force ripple, and sudden changes of itself.

• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.3
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• pp.219-225
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• 2005

In this paper, a new discrete-time small signal model of an average current mode control is proposed to predict the inductor current responses. Compared to the peak current mode control, the analysis of the average current mode control is difficult because of its presence of an compensation network. By utilizing sampler model, a new discrete-time small signal model is derived and used to predict the behaviors of an inductor current of average current mode control employing generalized compensation networks. In order to show the usefulness of the proposed model, prediction results of the proposed model are compared to those of the circuit level simulator, PSIM and experiment.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.216-224
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• 1986

This paper treats the modelling and the control of the burnthrough point control system for an industrial sintering process. First, a state-space model is derived by defining new unconventional variables. A simple control law is proposed, which consists of the modified receding horizon control law and the least-squares prediction algorithm. The stability and the tracking properties of this control law are proved. The real-time experiments are carried out in a POSCO sintering plant and satisfactory results are presented in this paper. Before the real-time experiments, computer simulations are done and their results are also given for the comparison with the real-time experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.27.4-27
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• 2001

A stabilizing control method for linear systems with model uncertainties and hard input constraints is developed, which does not require on-line optimizations. This work is motivated by the constrained robust MPC(CRMPC) approach [3] which adopts the dual mode prediction strategy (i.e. free control moves and invariant set) and minimizes a worst case performance criterion. Based on the observation that, a feasible control sequence for a particular state can be found as a linear combination of feasible sequences for other states, we suggest a stabilizing control algorithm providing sub-optimal and feasible control sequences using pre-computed optimal sequences for some canonical states. The on-line computation of the proposed method reduces to simple matrix multiplication.