In this paper, a new model inverse optimal iterative learning control algorithm is practically implemented on an industrial gantry robot. The algorithm has only one tuning parameter which can be adjusted to provide a ...
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In this paper, a new model inverse optimal iterative learning control algorithm is practically implemented on an industrial gantry robot. The algorithm has only one tuning parameter which can be adjusted to provide a balance between convergence speed and robustness. Results show that the algorithm is capable of learning the required trajectory in very few iterations. However at this convergence rate the lack of robustness is a major issue. Appropriate use of the tuning parameter is shown to greatly increase the algorithm robustness as demonstrated by tests which successfully reach 600 iterations.
The paper is devoted to the problem of modeling demand for inventory management of slow-moving items in the case of reporting errors. It is proposed a generalization of the beta-binomial demand model that takes into a...
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The paper is devoted to the problem of modeling demand for inventory management of slow-moving items in the case of reporting errors. It is proposed a generalization of the beta-binomial demand model that takes into account possible reporting errors in the learning sample. For the new model, there are developed identification and forecasting algorithms that provide consistent estimators of the model parameters and mean square optimal forecasts. The efficiency of the proposed approach is illustrated by an application example for slow-moving car parts.
This paper presents the modeling and identification of a real industrial furnace (900 kW, 38 m) used to cure large laminated composite pieces. The system exhibits a multi variable configuration with seven inputs (heat...
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Bidirectional Dijkstra algorithm whose time complexity is 8O(n~2) is proposed. The theory foundation is that the classical Dijkstra algorithm has not any directional feature during searching the shortest path. The alg...
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Bidirectional Dijkstra algorithm whose time complexity is 8O(n~2) is proposed. The theory foundation is that the classical Dijkstra algorithm has not any directional feature during searching the shortest path. The algorithm takes advantage of the adjacent link and the mechanism of bidirectional search, that is, the algorithm processes the positive search from start point to destination point and the negative search from destination point to start point at the same time. Finally, combining with the practical application of route-planning algorithm in embedded real-time vehicle navigation system (ERTVNS), one example of its practical applications is given, analysis in theory and the experimental results show that compared with the Dijkstra algorithm, the new algorithm can reduce time complexity, and guarantee the searching precision, it satisfies the needs of ERTVNS.
This paper represents a new technique for remapping the distributed object-oriented software methods to target architecture. This technique takes into consideration the advantages of the structure inherit in object-or...
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作者：
Klosowski, PiotrDivision of Telecommunication
Institute of Electronics Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 16 Gliwice44-100 Poland
Paper presents results of main research areas on speech communications applications: speech synthesis, speech recognition and speaker verification and identification systems. Research was conducted by Institute of Ele...
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The problem of identification/tracking of quasi-periodically varying processes is considered. Two solutions to this problem are presented, First the global search algorithm is derived. Then its decoupled version. with...
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New developments in computer networks and communications provide new possibilities for control purposes. control systems for highly complex plants are themselves very complex and heterogeneous. A new software infrastr...
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This paper presents the modeling and identification of a real industrial furnace (900 kW, 38 m) used to cure large laminated composite pieces. The system exhibits a multi variable configuration with seven inputs (heat...
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This paper presents the modeling and identification of a real industrial furnace (900 kW, 38 m) used to cure large laminated composite pieces. The system exhibits a multi variable configuration with seven inputs (heat resistors and fans) and seven outputs (temperature sensors). A very complex MIMO dynamic model is carried out by solving the heat transfer equations obtained from analogous electrical circuits that represent the multi-zone heat exchange. A set of experiments have to be designed in the mentioned industrial furnace in order to generate a useful real data collection which reliably allows to identify the parameters of the multivariable model.
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