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Volume 47, Issue 9
Displaying 1-9 of 9 articles from this issue
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Special Issue on Recent Contributions of Control Technologies in Industry Fields
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[in Japanese], [in Japanese], [in Japanese], [in Japanese]2011 Volume 47 Issue 9 Pages 355
Published: 2011
Released on J-STAGE: January 21, 2012
JOURNAL FREE ACCESSDownload PDF (139K)
Paper
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Masaharu WATANABE, Fumiaki TOMITA, Kenichi MARUYAMA, Yoshihiro KAWAI, ...2011 Volume 47 Issue 9 Pages 356-365
Published: 2011
Released on J-STAGE: January 21, 2012
JOURNAL FREE ACCESSThe miscorrespondence in stereo image analysis, which is caused by occlusion among images with failure in edge detection, often occurs in real factory environment, and this seriously disturbs the object localization and pose estimation. This work shows that, even under such conditions, the location and attitude of target object can precisely be measured, based on the three base-line trinocular stereo image analysis, using a “model-based verification” method, i.e., a model-based object recognition method including a multi-modal optimization algorithm. This method is suitable for real applications which need object localization and pose estimation, like a bin picking of parts randomly placed on factory automation.View full abstractDownload PDF (2043K) -
Mingcong DENG, Shengjun WEN, Akira INOUE2011 Volume 47 Issue 9 Pages 366-373
Published: 2011
Released on J-STAGE: January 21, 2012
JOURNAL FREE ACCESSIn this paper, a sensorless robust nonlinear control for travelling cranes is proposed. The control objectives are to control two outputs, the dispalcement of the travelling trolley and swing angle of the pay load using one input force, that is, the control system is an underactuated system. To control the outputs, a real-time measurement of the outputs is neccessary. But the real-time measurement of the swing angle using hardware sensors is difficult and a software method for the measurement is required. However, the crane system is described as a nonlinear dynamic system including uncertainty, which represents estimation errors of motion friction and viscous friction and unmodeled dynamics. Because of the uncertainty, it is difficult to estimate swing angle of the payload using model-based methods. This paper uses data-based Support Vector Regression for dealing with the above problem. And to enhance the generalizing ability and to apply to estimation of the swing angle in this system, this paper newly proposes to use a generalized Gaussian function as a kernel fucntion and real-time estimation of the two parameters of the function, that is, variance and shape parameter of the generalized Gaussian function. As the control law, two feedback loops are used. First is robust nonlinear stabilizing control law based on right coprime factorization approach. Second is given outside of the first feedback loop and it is nonlinear tracking controller. For the tracking controller, an optimization scheme is derived. Finally, experimental results are given to show the effectiveness of the proposed scheme.View full abstractDownload PDF (928K) -
Hiroya SEKI, Souichi AMANO, Genichi EMOTO2011 Volume 47 Issue 9 Pages 374-379
Published: 2011
Released on J-STAGE: January 21, 2012
JOURNAL FREE ACCESSAn initial design of an advanced control system for an industrial crystallizer train is addressed. The target process is a part of para-xylene production process, and it consists of five scraped surface crystallizers, two centrifugal separators, and two hydrocyclones. An operation policy is derived by solving a constrained nonlinear optimization problem on the basis of a nonlinear process model. Multiloop and multivariable control systems are designed to realize the derived operation policy and their performances are compared through simulation studies. The process is found to be highly interacting and constraint switching is likely to occur under operation condition changes, so that application of constrained multivariable model predictive control may be well justified. The procedures demonstrated in this study will help perform a feasible study for unconventional applications of advanced control technology.View full abstractDownload PDF (640K) -
Yoshio TANGE, Chikashi NAKAZAWA2011 Volume 47 Issue 9 Pages 380-387
Published: 2011
Released on J-STAGE: January 21, 2012
JOURNAL FREE ACCESSDisturbance suppression is one of most required performances in process control. We recently proposed a new disturbance suppression mechanism applicable for model predictive control in order to enhance disturbance suppression performance for ramp-like disturbances. The proposed method utilized the prediction error of controlled values and generates a disturbance compensation signal by a constant gain feedback. In this paper, we propose an improved version of the disturbance suppression mechanism by applying a low-pass filter and parameter tuning methods by which we can make the mechanism more tolerant to various disturbances such as ramp, step, and other supposable ones. We also show numerical simulation results with an oil distillation tower plant.View full abstractDownload PDF (807K) -
Hidekazu KUGEMOTO, Satoshi YOSHIMURA, Satoru HASHIZUME, Takashi KAGEYA ...2011 Volume 47 Issue 9 Pages 388-395
Published: 2011
Released on J-STAGE: January 21, 2012
JOURNAL FREE ACCESSA plant control diagnosis technology was developed to improve the performance of plant-wide control and maintain high productivity of plants. The control performance diagnosis system containing this technology picks out the poor performance loop, analyzes the cause, and outputs the result on the Web page. Meanwhile, the PID tuning tool is used to tune extracted loops from the control performance diagnosis system. It has an advantage of tuning safely without process changes. These systems are powerful tools to do Kaizen (continuous improvement efforts) step by step, coordinating with the operator. This paper describes a practical technique regarding the diagnosis system and its industrial applications.View full abstractDownload PDF (2431K) -
Masayoshi DOI, Kazuhisa NAGAMOTO, Kenichi IDENAWA, Yasuchika MORI2011 Volume 47 Issue 9 Pages 396-403
Published: 2011
Released on J-STAGE: January 21, 2012
JOURNAL FREE ACCESSShip's handling is difficult because the response of ship's maneuver is slow with the big inertia. First, this study identifies the ship's maneuverability, which is expressed as Auto-Regressive Moving Average (ARMA) model, by steering. Second, a time delay of the angular velocity is verified. Finally, this study design a ship's steering control system. The angular velocity is controlled by applying Generalized Minimum Variance Control (GMVC) of predictive control method. Especially, GMVC's control method is arranged by adding a operating limit for the ship's steering control.View full abstractDownload PDF (980K) -
Arata EJIRI, Jun SASAKI, Yusuke KINOSHITA, Junya FUJIMOTO, Tsugito MAR ...2011 Volume 47 Issue 9 Pages 404-411
Published: 2011
Released on J-STAGE: January 21, 2012
JOURNAL FREE ACCESSFor the purpose of contributing to global environment protection, several research studies have been conducted involving clean-burning diesel engines. In recent diesel engines with Exhaust Gas Recirculation (EGR) systems and a Variable Nozzle Turbocharger (VNT), mutual interference between EGR and VNT has been noted. Hence, designing and adjusting control of the conventional PID controller is particularly difficult at the transient state in which the engine speed and fuel injection rate change. In this paper, we formulate 1st principal model of air intake system of diesel engines and transform it to control oriented model including an engine steady state model and a transient model. And we propose a model-based control system with the LQR Controller, Saturation Compensator, the Dynamic Feed-forward and Disturbance Observer using a transient model. Using this method, we achieved precise reference tracking and emission reduction in transient mode test with the real engine evaluations.View full abstractDownload PDF (2390K) -
—Model Refinement for FOUP Load—Kenji SAWADA, Kosuke TANAKA, Seiichi SHIN, Kenji KUMAGAI, Hisato YONED ...2011 Volume 47 Issue 9 Pages 412-419
Published: 2011
Released on J-STAGE: January 21, 2012
JOURNAL FREE ACCESSThis paper presents a modeling of an automatic guided vehicle (AGV) to achieve a model-based control. The modeling includes 3 kinds of choices; a choice of input-output data pair from 14 candidate pairs, a choice of system identification technique form 5 candidate techniques, a choice of discrete to continuous transform method from 2 candidate methods. In order to obtain reliable plant models of AGV, an approach for calibration between a statistical model and a physical model is also here. In our approach, the models are combined according to the weight of AGV. As a result, our calibration problem is recast as a nonlinear optimization problem that can be solved by quasi-Newton's method.View full abstractDownload PDF (750K)
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