The paper deals with a general form of a mathematical model of a three-phase electric circuit characteristics. A form of the model with using dimensionless variables is discussed. In general form of the linear AC circ...
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The paper deals with a general form of a mathematical model of a three-phase electric circuit characteristics. A form of the model with using dimensionless variables is discussed. In general form of the linear AC circuit, the steady-state circuit characteristics are nonlinear functions of circuit elements and signals parameters. The linearized model of the asymmetrical circuit with linear loads is derived in matrix-vector notation. The model consists of sensivity function of the circuit-phase currents versus load voltages, supply voltages, phase inductances and supply voltages frequency described analytically in form of matrices or vector. As reference the symmetric (balanced) three-phase circuit was used. An example of application of this model to the determination of the inductances of the circuit is given.
This paper outlines further research possibilities in the field of Real-Time Database Systems. It is based on the previous research accomplished at the Technical University of Ostrava, including the V4DB Real-Time Dat...
This paper outlines further research possibilities in the field of Real-Time Database Systems. It is based on the previous research accomplished at the Technical University of Ostrava, including the V4DB Real-Time Database System design and verification.
For the alarm flooding problem, a hierarchical alarm processing model is studied to filter, reduce and correlate alarms. In filtering, false alarms are eliminated with repository. In reduction, a reduction algorithm i...
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We apply nonparametric techniques to identify nonlinear dynamic block-oriented systems of Hammerstein type. Hammerstein system consists of a memoryless nonlinear system followed by a dynamic, linear system. We introdu...
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ISBN:
(纸本)9783902661555
We apply nonparametric techniques to identify nonlinear dynamic block-oriented systems of Hammerstein type. Hammerstein system consists of a memoryless nonlinear system followed by a dynamic, linear system. We introduce identification algorithms based on inputoutput observations for both systems and study their convergence and the rates. The performance of identification algorithms is validated in simulation studies. We apply Hammerstein system identification algorithms to identification of nonlinearities in a flexible robot manipulator.
Recently, many researchers have demonstrated that computation by DNA tile self-assembly may be scalable and it is considered as a promising technique in nanotechnology. In this paper, we show how the tile self-assembl...
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Recently, many researchers have demonstrated that computation by DNA tile self-assembly may be scalable and it is considered as a promising technique in nanotechnology. In this paper, we show how the tile self-assembly process can be used for solving the 0-1 multi-objective knapsack problem by mainly constructing four small systems which are nondeterministic guess system, multiplication system, addition system and comparing system, by which we can probabilistically get the feasible solution of the problem. Our model can successfully perform the 0-1 multi-objective knapsack problem in polynomial time with optimal Theta(1) distinct tile types, parallely and at very low cost.
Ant colony optimization (ACO) is a population-based meta-heuristic for combinatorial optimization problems such as communication network routing problem (CNRP). This paper proposes an improved ant colony optimization ...
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Ant colony optimization (ACO) is a population-based meta-heuristic for combinatorial optimization problems such as communication network routing problem (CNRP). This paper proposes an improved ant colony optimization (IACO), which adapts a new strategy to update the increased pheromone, called ant-weight strategy, and a mutation operation, to solve CNRP. The simulation result for a benchmark problem is reported and compared to the simple ant colony optimization (ACO).
Industrial process control IP networks support communications between process control applications and devices. Communication faults in any stage of these control networks can cause delays or even shutdown of the enti...
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Industrial process control IP networks support communications between process control applications and devices. Communication faults in any stage of these control networks can cause delays or even shutdown of the entire manufacturing process. The current process of detecting and diagnosing communication faults is mostly manual, cumbersome, and inefficient. Detecting early symptoms of potential problems is very important but automated solutions do not yet exist. Our research goal is to automate the process of detecting and diagnosing the communication faults as well as to prevent problems by detecting early symptoms of potential problems. To achieve our goal, we have first investigated real-world fault cases and summarized control network failures. We have also defined network metrics and their alarm conditions to detect early symptoms for communication failures between process control servers and devices. In particular, we leverage data mining techniques to train the system to learn the rules of network faults in control networks and our testing results show that these rules are very effective. In our earlier work, we presented a design of a process control network monitoring and fault diagnosis system. In this paper, we focus on how the fault detection part of this system can be improved using data mining techniques.
A novel method is proposed for the digital redesign of analogue controllers with account for the closed-loop system performance in continuous *** method,which is based on a two-level optimization algorithm,makes it po...
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A novel method is proposed for the digital redesign of analogue controllers with account for the closed-loop system performance in continuous *** method,which is based on a two-level optimization algorithm,makes it possible to place the closed-loop poles inside a specified region of the complex plane and provides for reduced-order *** effectiveness of the proposed technique is demonstrated by some well-known redesign examples.
In this paper Principal Components Analysis (PCA) is used for detecting faults in a plant with multiple operation modes. PCA reduces the dimensionality of the original historical data by projecting it onto a lower dim...
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In this paper Principal Components Analysis (PCA) is used for detecting faults in a plant with multiple operation modes. PCA reduces the dimensionality of the original historical data by projecting it onto a lower dimensionality space. It obtains the principal causes of variability in a process. If some of these causes change, it can be due to a fault in the process. The classical PCA approach confuses changes in operation mode with faults. This paper deals with this problem using a switching structure to deal with different operation modes. The transitory states between the operation modes are dealt with using a PCA approach used in batch processes. The implemented method has been proved in a simulated two-communicated-tanks plant.
In recent, due to convenient and inexpensive installations, flexibility, and scalability, the interests in wireless AMR are being increased more and more. However, the wireless AMR network, which generally covers larg...
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In recent, due to convenient and inexpensive installations, flexibility, and scalability, the interests in wireless AMR are being increased more and more. However, the wireless AMR network, which generally covers large areas, may create energy wastage problem and high interference hazard due to a large amount of concurrent-intensive metering data in the network. In this paper, in order to improve energy efficiency and reduce the possibility of interferences by minimizing data traffic in the wireless-based AMR network, specifically in large scale, a novel energy-efficient meter data aggregation method is proposed, which is inspired from the data-centric routing in wireless sensor networks. Through theoretical analysis and simulations, it is demonstrated that the EMDA can gather data with the minimum number of transmissions in the network even though the number of nodes is increased.
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