Proper selection of cooking times is one of the most important decision making tasks in batch pulp cooking. Duration of a batch depends on cooking conditions and must be chosen so that the Kappa number - a measure for...
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Proper selection of cooking times is one of the most important decision making tasks in batch pulp cooking. Duration of a batch depends on cooking conditions and must be chosen so that the Kappa number - a measure for pulp quality - reaches the desired value at the end of the batch. Due to the lack of appropriate industrial sensors for on-line Kappa measurements, Kappa can be determined only after cooking is over by means of analysis in the laboratory. Therefore, a model based system is developed for on-line Kappa estimation and control. The very heart of the system represents the estimation algorithm based on non-linear optimization. It combines a special purpose routine for approximate (but fast) optimum search and Gauss—Newton method for "fine" optimization. This paper surveys some relevant properties of the scheme such as model simplification, "fine" optimization, analysis of identifiability conditions and related numerical problems. A minimum variance Kappa controller is treated as well. Efficiency of the proposed scheme is confirmed by means of the simulated examples and results of practical implementation.
Due to the lack of appropriate industrial sensors for online Kappa measurements, Kappa can be determined only after a batch is over by means of analysis in the laboratory. In view of this, a model-based system is deve...
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Due to the lack of appropriate industrial sensors for online Kappa measurements, Kappa can be determined only after a batch is over by means of analysis in the laboratory. In view of this, a model-based system is developed with the purpose of estimating and controlling Kappa online. A survey is presented of some relevant design issues such as model simplification, approximate parameter estimation, and minimum variance Kappa control. The efficiency of the proposed scheme is illustrated by means of the simulated examples and the results of practical implementation.< >
The principle of in-circuit simulation, with PCs is described and shown for two cases. In the first case, for oil-fired central heating with low power (
The principle of in-circuit simulation, with PCs is described and shown for two cases. In the first case, for oil-fired central heating with low power (<120 kW), the boiler- and the heat-temperature-control of the heating system are presented. The house and the heating system were simulated on a PC. In the second case, the combustion control of a medium-sized industrial boiler (20 MW) is presented. The combustion was simulated on a PC and the combustion control was accomplished by the MMC-90 microcomputer-based multiloop controller.< >
Dynamic modeling of the ankle joint is performed by means of the non-parameteric Wiener-Volterra approach. The original version is extended so that colored noise inputs can be handled. This is imposed from reality, i....
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Dynamic modeling of the ankle joint is performed by means of the non-parameteric Wiener-Volterra approach. The original version is extended so that colored noise inputs can be handled. This is imposed from reality, i.e., all movements of the angle joint must be limited in frequency as well as in amplitude. Experiences related to the method are briefly summarized and supported with results obtained on a normal subject.< >
The authors demonstrate the usefulness of change tracking information from the maintenance programmer's perspective. They split the data into logical groups and find the connections between these groups. They desc...
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The authors demonstrate the usefulness of change tracking information from the maintenance programmer's perspective. They split the data into logical groups and find the connections between these groups. They describe a method to incorporate problem-solving information in a change tracking database. Problem solving is discussed with regard to structured problem-solving techniques for isolating difficult problems. A relational database structure and queries to access the database are discussed. An example of how the change tracking system supports the maintenance problem-solving process is also included.< >
Forgetting of old information is an indispensable part of the real-time estimation whenever tracking of the time varying parameters is required. Its realization depends primarily on available knowledge of the paramete...
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Forgetting of old information is an indispensable part of the real-time estimation whenever tracking of the time varying parameters is required. Its realization depends primarily on available knowledge of the parameter dynamics and nature of input excitation. The paper deals with a class of time varying systems in which the parameters can be (due to prior knowledge) partitioned into two or more groups with respect to their distinct speed of variation. Under no further assumptions the Bayesian approach results in a forgetting scheme which permits application of two or more forgetting factors at the same time. Some properties of the algorithm are analyzed and its performance is illustrated with simulation examples.
Petri net and Markov chain models are developed for manufacturing systems with blocking and deadlock. The authors compute the probability that the system in an absorbing (deadlocked) state, the mean time to deadlock, ...
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Petri net and Markov chain models are developed for manufacturing systems with blocking and deadlock. The authors compute the probability that the system in an absorbing (deadlocked) state, the mean time to deadlock, and the throughput before deadlock, etc., which can be used to compare the performance of various prevention and avoidance strategies. A systematic method for designing locks and interlocks for deadlock avoidance using the reachability graph of the Petri net model is presented.< >
The demand for wider, thinner rolled steel has led to an increasing interest in the control of the strip “shape”. Mechanisms for controlling shape include roll bending, roll tilt (or mill steer) and spray pattern co...
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The demand for wider, thinner rolled steel has led to an increasing interest in the control of the strip “shape”. Mechanisms for controlling shape include roll bending, roll tilt (or mill steer) and spray pattern control. This paper will principally focus on an analysis of the spray control system and the associated interaction between adjacent zones. This paper decribes a new approach to shape control, a mathematical model is derived for the dynamic thermal expansion of the rolls of the a tandem cold rolling mill. The model structure has been specifically designed to facilitate control studies. The system is highly non-linear but the model suggests how the system can be linearized by an appropriate input signal transformation. The linearized system then represents a coupled multi-input multi-output dynamical system linking the cooling water sprays to the measured exit strip shape. This linearized model leads to a dynamical decoupling procedure which reduces the system to a set of single-input single—output control systems. Apart from the application to shape control, the method proposed here has more general applicability since the same kind of problem arises in a variety of cross-machine probelms.
An approach to iterative learning control system design based on 2D system theory is presented. A 2D model for the iterative learning control system which reveals the connections between learning control systems and 2...
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An approach to iterative learning control system design based on 2D system theory is presented. A 2D model for the iterative learning control system which reveals the connections between learning control systems and 2D system theory is established. A learning control algorithm is proposed, and the convergence of learning using this algorithm is guaranteed by 2D stability. The learning algorithm is applied successfully to the trajectory tracking control problem for a parallel link robot manipulator. The excellent performance of this learning algorithm is demonstrated by computer simulation results.< >
A likelihood ratio test is used to detect the portion of the prediction error variance caused by changes in parameters. It results in a simple rule for adjusting the dispersion factor in the parameter covariance matri...
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A likelihood ratio test is used to detect the portion of the prediction error variance caused by changes in parameters. It results in a simple rule for adjusting the dispersion factor in the parameter covariance matrix. The adaptation rule given by Jazwinski (1970) is shown to be a special case of one derived
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