1,721,123 research outputs found
TOWARD THE SYNTHESIS OF GLOBAL OPTIMUM HEAT-EXCHANGER NETWORKS UNDER MULTIPLE-PERIODS OF OPERATION
No full textAn algorithmic-evolutionary synthesis procedure is proposed for flexible heat exchanger networks (HEN) under multiple-periods of operation. After a feasible network is synthesized at each period, they are combined to form a feasible super network structure which requires maximum energy recovery (MER) at each period and features minimum number of units (MNU). Beginning with the initial feasible super network structure, all the super network structures can be enumerated to generate the minimum cost super network structure. The key steps in the procedure are constituted of must-matches searches at each period and path tracing/list processing constructions that allow not only combination of networks of each period but also development of super network structures adjacent to the initial super network structure in some sense, while keeping maximum energy recovery at each period and minimum number of units. Then a trade-off between MER and MNU is performed to strictly reduce objective function values. The constructions and procedures are rigorously established and effectiveness of the composite algorithm is demonstrated via several test problems. These tests show that the proposed approach can find the optimum networks for the known standard problems, and new MNU/MER networks are identified which to date have not been reported in the literature.X110sciescopu
SYNTHESIS OF HEAT-EXCHANGER NETWORKS WITH MINIMUM NUMBER OF UNITS FOR PINCHED PROBLEMS
No full textAn algorithmic-evolutionary synthesis procedure is studied for generating the maximum energy recovery (MER) and minimum number of units (MNU) networks with the goal of achieving the global optimum network under pinch points. For pinched problems, sufficient conditions are proposed for determining the minimum number of units. These sufficient conditions, together with heuristic matching rules, are used to generate an initial feasible composite MNU/MER network. A split-merge network structure is introduced in order not to violate the prescribed minimum approach temperature. This initial network is successively evolved to obtain improved networks by limited heat load redistribution resulting from the pinch point. The properties and limitations of the constructions and procedures are established and the effectiveness of the heuristic procedure is illustrated with literature test problems.X111sciescopu
Prediction error identification method for continuous-time processes with time delay
No full textWe propose a continuous-time prediction error identification method to identify combined deterministic-stochastic continuous-time processes with time delay. It minimizes the prediction error using the Levenberg-Marquardt optimization method with exact derivatives of the objective function with respect to the adjustable parameters that include the time delay. Compared with previous discrete-time identification methods, the proposed method does not suffer from a small sampling time problem. Also, while previous continuous-time approaches using transforms cannot treat a large sampling time, the proposed method can incorporate directly both small and large sampling times as well as irregular sampling time. It can determine the time delay systematically; meanwhile, previous methods use ad hoe approaches. We derive the error covariance matrix and justify the small sampling problem of discrete-time identification methods.X1131sciescopu
Modified dynamic matrix control
No full textDMC (Dynamic Matrix Control) has been used successfully in industry for the last decade. It can deal with constraints and unusual dynamic behavior directly. It also shows a good control performance for the servo problem. Relatively, it can't reject disturbances systematically. We propose a modified DMC method to control the regulatory process more efficiently. The proposed DMC method makes the control output by subtracting the estimated disturbance from the control output of the original DMC. Here, the disturbance is estimated by a new disturbance estimator. It shows better control performances than the original DMC.X111sciescopu
Adaptive monitoring statistics with state space model updating based on canonical variate analysis
No full textA new multivariate statistical model updating by using a recursive state space model updating based on CVA is proposed. The CVA-based monitoring techniques have been researched to detect and isolate process abnormalities in dynamic processes. Two monitoring indices are defined for fault detection, and a state space model updating procedure is developed by using mean, covariance, and correlation updating based on forgetting factor as well as the recursive Cholesky factor updating. To adjust forgetting factors according to variation of process state, the forgetting factor updating criteria are introduced. The proposed method is applied to benchmark models of a continuous stirred tank reactor with a first order reaction and the Tennessee Eastman process (TEP) under transient and time-varying operating conditions. Through the simulation results, we expect that the proposed approach can be applied to time-varying and dynamic processes under transient state.X119sciescopuskc
Nonlinear dynamic process monitoring based on dynamic kernel PCA
No full textNonlinear dynamic process monitoring based on dynamic kernel principal component analysis (DKPCA) is proposed. The kernel functions used in kernel PCA (KPCA) are profitable for capturing nonlinear property of processes and the time-lagged data extension is suitable for describing dynamic characteristic of processes. DKPCA enables us to monitor an arbitrary process with severe nonlinearity and (or) dynamics. In this respect, it is a generalized concept of multivariate statistical monitoring approaches. A unified monitoring index combined T-2 with SPE is also suggested. The proposed monitoring method based on DKPCA is applied to a simulated nonlinear process and a wastewater treatment process. A comparison study of PCA, dynamic PCA, KPCA, and DKPCA is investigated in terms of type I error rate, type II error rate, and detection delay. The monitoring results confirm that the proposed methodology results in the best monitoring performance, i.e., low missing alarms and small detection delay, for all the faults. (C) 2004 Elsevier Ltd. All rights reserved.X1193sciescopu
Process monitoring based on probabilistic PCA
No full textThis paper proposes a multivariate process monitoring method based on probabilistic principal component analysis (PPCA). First we will summarize several well-known statistical process monitoring methods, e.g. univariate/multivariate Shewhart charts, and the PCA-based method, i.e. Q and Hotelling's T-2 charts. And then the probabilistic method will be proposed and compared to the existing methods. In essence, the univariate Shewhart chart, multivariate Shewhart chart, Q chart, and T-2 chart are unified to the probabilistic method. The PPCA model is calibrated by the expectation and maximization (EM) algorithm similar to PCA by NIPALS algorithm; EM algorithm will be explained briefly in the article. Finally, through an illustrative example, we will show how the probabilistic method works and is applied to the process monitoring. (C) 2003 Elsevier Science B.V. All rights reserved.X1190sciescopu
A new completion time algorithm considering an out-of-phase policy in batch processes
No full textTo raise the scheduling efficiency in batch processes, we propose a new approach is to consider an out-of-phase operating mode. Previous scheduling algorithms which have been concerned only with single-unit single-stage case problems are extended. We suggest new completion time algorithms of single-product and multiproduct batch processes for the unlimited intermediate storage (UIS) and no intermediate storage (NIS) case from the single-product multicampaign model. To check out the effect of our algorithm and to visualize processing progress, we develop the program calculating and displaying the Gantt chart mapping-Gantt Man. Five simple examples are presented to show the effectiveness of the proposed algorithms.X112sciescopu
Limitations and countermeasures of PID controllers
No full textIt is well-known that PID controllers show poor control performances for an integrating process and a large time delay process. Moreover, it cannot incorporate ramp-type set-point change or slow disturbance. We discuss the above-mentioned limitations of the PID controller. Through the analysis of the limitations, simple techniques are developed to avoid these poor control performances and incapabilities. We introduce a control structure composed of two PID controllers to manipulate both the set-point change process and the input disturbance rejection process. A simple feedforward and feedback loop are proposed to treat a ramp-type set point and disturbance (low-frequency set paint and disturbance). In addition, an internal feedback loop is introduced to incorporate integrating processes, and a tuning strategy using the model reduction is proposed to efficiently tune the controller for high-order processes. A dead-time compensator is used to manipulate a large time delay process more efficiently.X1153sciescopu
A synthesis of multiproduct batch plants considering both in-phase and out-of-phase modes
No full textA heuristic procedure using a NLP(NonLinear Programming) is developed for the preliminary design of multiproduct batch plants. The procedure determines equipment volumes/batch sizes and allows structural features such as in-phase and out-of-phase modes of operation and nonidentical parallel units in a stage. The previous approaches in solving the synthesis problem as MINLP(Mixed Integer NonLinear Programming) problem so far, have considered only out-of-phase mode. In this paper, using a NLP formulation combined with heuristics, we deal with the problems where in-phase mode and out-of-phase mode are simultaneously considered. The first step of our procedure, by heuristics and table analyses, is to determine how the parallel equipment operates every stage for each product. And then, using a NLP formulation, we determine the unit volumes and batch sizes. This paper demonstrates the effectiveness of our approach in solving two problems of batch plant design.X115sciescopu
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