A new oscillating-plate type viscometer, which makes instant and continuous measurement of viscosity for high temperature material possible, is developed and utilized. This viscometer is designed for industrial use, and viscosity can be measured automatically with high accuracy and easy operation. The measured value of viscosity is evaluated by using mold flux in continuous casting process, and it is verified that proper control of viscosity and primary crystallization temperature for mold flux yields continuous casting products of good quality and prevents troubles in casting. This method of viscosity measurement is currently used in various areas such as the examination of newly received mold flux, the selection of optimum fluidity characteristics for various casting conditions, and the development and the improvement of mold flux.
The simple adaptive control (SAC) method being applied to non-ASPR plants including pneumatic servo systems, it becomes indispensable to furnish a parallel feedforward compensator (PFC) to the system. Also, a fine adjustment of parameters in PFC is required to keep stability and to attain a desirable performance. It is, however, difficult to adjust them suitably with little information on the plant. In this paper, we propose an algorithm which tunes them automatically with a watch of improvement of the actual performance. An experiment is also carried out to show the effectiveness of our proposal.
Because of the reasons of favorable features such as high driving force, fast response, fine environmental durability and big distortion about 10 times more than that of PZT, GMM (Giant Magnetrostrictive Material) is suitable for the actuation structure of servovalve. But, GMM distortion depends on the magnitude of coil current and the output-gain declines according to decreasing current magnitude. Then, the dead-zone appears in small current range. One of the important characteristics of servovalve is the fine tracking performance to the reference signal. So far, we attempted to apply linear controllers, such as PI or H∞controller. However GMM tracking performance is inferior to the traditional driving device for reference signal around null area, and this flaw remains as an important matter. In this paper, adopting LPV (Linear Parameter-Varying) system modeling in which we regard the magnitude of input signal as a scheduling parameter, we design a gain scheduling controller and attempt to solve the problem that is caused by the nonlinearities mentioned above. Since it is hard to implement the controller which uses the information on the varying rate of scheduling parameters, we propose a new approach for output-feedback controller design. First, we describe the plant modeling as an LPV system, then present an outline of the controller design synthesis without any information on the varying rate of scheduling parameter and the design process. Lastly, we show the usefulness of the proposed controller by experimental results.
Lost motion is a major disturbance to the contouring accuracy of NC machine tools. Although NC machine tools with plain bearing guideways perform high alignment accuracy, they sometimes show the exponential type lost motion. Conventional step type backlash compensation applied to that lost motion, causes contouring error due to over-compensation. This paper presents a model of a two-body system with a nonlinear damper and a nonlinear spring that exhibits the exponential type lost motion. A compensation method for that lost motion is introduced from the model. Experimental results show the improved performance of the proposed method.
In this paper, an approach to model identification and control of Rapid Thermal Processing (RTP) systems is given for the improvement of controlling the wafer temperature in semiconductor manufacturing. A new parametric identification algorithm based on the nonlinear Wiener model is first applied to identify the RTP system. It includes both subspace method and model parameter optimization. With the iterative optimization procedure, the model parameter converges quickly to the asymptote, and prediction error is greatly reduced. The identification result shows that the Wiener model is superior to a linear model in capturing the RTP dynamics. An EKF-based controller is also designed and implemented for our RTP system. The experiment demonstrates that the controller is capable of steering the dynamic response and thermal uniformity across a wafer over a wide operating envelope.
The purpose of this study is to develop a multi-functional automated process controller for use in a synthesis system of chemical reactions. Chemical reactions can be very complex, making it difficult to control the reaction temperature. In this research, a neural network is proposed for controlling the temperature of the reaction. First, the system dynamics are identified from real time experimental data using a neural network. Next a neural network controller is constructed to regulate the temperature of the chemical reaction, then its effectiveness is tested through simulations and experiments. Finally a neural network diagnostic system is proposed in the event of, machine trouble or human error. A new type of chemical conversion estimation is also proposed from these results, and it is verified that it can efficiently control the chemical reaction using developed the AI process controller.
This paper describes a rolling load modeling method that uses GP (Genetic Programming). It is important to predict the rolling load accurately for manufacturing high quality products in steel industry. Usually, the rolling load is predicted by using a statistical method based on a mathematical model. Even if the adaptive learning is applied to the conventional model, the prediction accuracy can not be improved for high quality manufacturing. In this paper, a new function structure of rolling load model is proposed and function components are determined by GP. This approach makes it possible, not only to achieve the high accuracy prediction, but also to reduce the calculation time for the real time pass scheduling and to apply the model to the rare rolling case with poor data base. It is observed that the new model reduces the standard deviation of the error by 17%, compared with the conventional method.
This paper describes two recovery steam stabilization systems for a fluidized bed incinerator with a high efficiency energy recovery system based on multivariable MPC (Model Predictive Control). One is able to control superheated steam generation rate, temperature and pressure stably by manipulating a steam flow valve, waste feeder speed and primary air flow into the energy recovery zone, because it takes into consideration the interactions which exist in the steam recovery system. The other is composed of a combustion control system and a recovery steam control system based on multivariable MPC. The combustion control system manipulates the waste feeder speed so as to keep oxygen concentration in the incinerator in an appropriate range. Experimental results for a real fluidized bed incinerator show the usefulness of the proposed method.
This paper proposes TACT, an environment to construct reliable systems where periodic tasks are dominant. TACT provides a planning based task scheduling mechanism, which enables the master machine to duplicate its task plan on the slave machine in run-time. Through the duplication, tasks on the slave machine get equivalent to those on the master machine. TACT allows two machines to stand-by alternately. The paper describes the concept, functions, and implementation of TACT. It also shows application of TACT to a steel mill control system.
In this paper, we show an elevator supervisory control system which is able to reduce long waits. There are two ideas in this method. The first is that a special service is prepared for a critical condition like long waits. We use a special call allocation rule called the LW (long waits) reduction rule. The second is that an elevator system always provides potential services for passengers at each floor to increase the effect of the LW reduction rule. We propose a new type of evaluations called the ESD (evaluating service distribution) to evaluate potential services for each floor and to provide them. We have made some simulations with these ideas, and the results show the successful performance in reducing the rate of long waits.