• Korean Chemical Engineering Research
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• v.45 no.1
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• pp.103-108
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• 2007

HAZOP analysis is a systematic method on the basis of the experts' experience and knowledge and is used for hazard identification and risk assessment by using brainstorming method. So, HAZOP analysis has been applied to major chemical industries efficiently. But it does not apply to small and midium chemical industries because of the insufficiency of the experts. Hence, in this study a new hazard identification method is proposed by modifying complexity and expertise of the HAZOP analysis and will be contributed to improve risk management for small and midium chemical industries.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.145-148
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• 1999

It is known that Volterra kernel models can represent a wide variety of nonlinear chemical processes. Also, it is necessary for Volterra model identification to excite the process to be identified with a signal having wide range of frequency spectrum and high enough amplitude of input signals. Kashiwagi[4 ∼ 7] has recently shown a method for measuring Volterra kernels up to third order using pseudorandom M-sequence signals. However, in practice, since it is not always possible to apply such input sequences to the actual chemical plants. Even when we can apply such a pseudorandom signal to the process, it takes much time to obtain higher order Volterra kernels. Considering these problems, the authors propose here a new method for practical identification of Volterra kernels by use of approximate open differential equation (ODE) model and simple plant test. Simulation results are shown for verifying the usefulness of our method of identification of nonlinear chemical processes.

• Korean Chemical Engineering Research
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• v.46 no.5
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• pp.949-957
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• 2008

Estimating the first order plus time delay model on the basis of the step responses has been widely used in industry for the tuning of PID controllers. Even though various model identification methods from simple graphical approaches to complicated approaches based on least squares method have been proposed, simple approaches to incorporate noisy step responses are rarely available. In this research, we will compare and analyze recent approaches using the integrals of the step responses and develop an improved identification method to incorporate real situations more effectively.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.430-435
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• 1992

Hazard identification is one of the most important task in process design and operation. This work has focused on the development of a knowledge-based expert system for HAZOP (Hazard and Operability) studies which are regarded as one of the most systematic and logical qualitative hazard identification methodologies but which require a multidisciplinary team and demand much time-consuming, repetitious work. The developed system enables design engineers to implement existing checklists and past experiences for safe design. It will increase efficiency of hazard identification and be suitable for educational purposes. This system has a frame-based knowledge structure for equipment failures/process material properties and rule networks for consequence reasoning which uses both forward and backward chaining. To include wide process knowledge, it is open-ended and modular for future expansion. An application to LPG storage and fractionation system shows the efficiency and reliability of the developed system.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.26.2-26
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• 2001

It is known that Volterra kernel model can represent a wide variety of nonlinear chemical processes. But almost all Volterra kernel models which appeared in the literature are up to second order, because it was difficult to measure higher order Volterra kernels. Kashiwagi has recently shown a method for measuring Volterra kernels up to third order using pseudorandom M-sequence signals. In this paper, the authors verified the applicability of this method for chemical processes using polymerization reactor simulation. Also, the authors have recently proposed a practical Identification method for chemical processes, which is based on the combination of off-line nonlinear identification and on-line linear identification. This method is also applied to the identification of polymerization reactor, and we obtained ...

• Analytical Science and Technology
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• v.34 no.3
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• pp.99-114
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• 2021

Substance identification is the first step in implementing chemical legislation, such that subsequent hazard and risk assessments can be accurately followed. Based on the web page and related guidance documents of the European Chemicals Agency and available consortia information, the procedure for substance identification carried out in Registration, Evaluation, Authorization and Restriction of Chemicals (REACH) is surveyed. In this study, the importance of substance identification and substance sameness check, as well as the necessity of generating a substance identity profile (SIP) are considered. In addition, the SIPs of several substance types are presented, which focused on information utilization in the instrumental analysis results and organization of information to generate the SIP. Analytical science can contribute to the accurate and effective implementation of chemical regulation at the starting stage of substance identification. However, understanding of the regulation and consequent final wrap-up of analytical results as a SIP should be followed for communication among registrants in Substance Information Exchange Forum (SIEF) as well as with related authorities.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.2
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• pp.109-113
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• 2002

Van de Vusse reactor is known as a highly nonlinear chemical process and has been considered by a number of researchers as a benchmark problem for nonlinear chemical process. Various identification methods for nonlinear system are also verified by applying these methods to Van de Vusse reactor. From the point of view of identification, only the Volterra kernel of second order has been obtained until now. In this paper, the authors show that Volterra kernels of nonlinear Van de Vusse reactor of up to 3rd order are obtained by use of M-sequence correlation method. A pseudo-random M-sequence is applied to Van de Vusse reactor as an input and its output is measured. Taking the crosscorrelation function between the input and the output, we obtain up to 3rd order Volterra kernels, which is the highest order Volterra kernel obtained until now for Van de Vusse reactor. Computer simulations show that when Van de Vusse chemical process is identified by use of up to 3rd order Volterra kernels, a good agreement is observed between the calculated output and the actual output.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1762-1765
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• 1997

Some ill-conditioned processes are very sensitive to small element-wise uncertainties arising in classical element-by-element model identifications. For such processes, accurate identification of simgular values and right singular vectors are more important than theose of the elements themselves. Singular values and right singular vectors can be found by iteraive identification methods which implement the input and output transformations iteratively. Methods based on SVD decomposition, QR decomposition and LU decomposition are proposed and compared with the Kuong and Mac Gregor's method. Convergence proofs are given. These SVD and QR mehtods use normal matrices for the transformations which cannot be calculated analytically in general and so they are hoard to apply to dynamic processes, whereas the LU method used simple analyitc transformations and can be directly applied to dynamic processes.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1883-1887
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• 1991

Identification theory for linear discrete system has been presented by a great many reference, but research works for identification of continuous-time system are less than preceding identification. In fact, a great man), systems for engineering are continuous-time systems, hence, research for identification of continuous-time system has important meaning. This paper offers the following results: 1. Corresponding relations for the parameters of continuous-time model and discrete model may be shown, when single input-output system has general characteristic roots. 2. To do identification of single variable continuity linear system with stability constraints from samples of input-output data, it is necessary to use optimization with stability constraints. 3. Main results of this paper may be explained by a simple example.

• International Journal of Control, Automation, and Systems
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• v.5 no.5
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• pp.508-514
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• 2007

Properties and potential applications of the block pulse response circulant matrix (PRCM) and its singular value decomposition (SVD) are investigated in relation to MIMO control and identification. The SVD of the PRCM is found to provide complete directional as well as frequency decomposition of a MIMO system in a real matrix form. Three examples were considered: design of MIMO FIR controller, design of robust reduced-order model predictive controller, and input design for MIMO identification. The examples manifested the effectiveness and usefulness of the PRCM in the design of MIMO control and identification. irculant matrix, SVD, MIMO control, identification.