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1
Content available remote The load torque influence on time-optimal position control process
EN
The contribution of the paper is the theoretical development and obtaining the time-optimal position control process in conditions of heavy loading of the servo motor as a result of simulation tests. The influence of passive load torque and active load torque on the position controller output signal generation in its active state is described mathematically.
PL
Wkładem pracy jest opracowanie teoretyczne oraz uzyskanie optymalno-czasowego procesu regulacji położenia w warunkach silnego obciążenia silnika serwo w wyniku badań symulacyjnych. Opisano matematycznie wpływ pasywnego momentu obciążenia oraz aktywnego momentu obciążenia na sposób generowania sygnału wyjściowego regulatora położenia w jego stanie aktywnym.
2
Content available remote Time-optimal position control of DC motor servo drive
EN
Time optimal position control method is obtained differently on the basis of position, speed and motor current responses to DC motor voltage steps by applying dynamic programming method. As the result, the position overshoot and chattering is completely eliminated.
PL
Metodę optymalno-czasowej regulacji położenia uzyskano inaczej czyli na podstawie odpowiedzi położenia, prędkości oraz prądu silnika DC po skokowej zmianie napięcia DC zasilającego silnik prądu stałego oraz stosując metodę programowania dynamicznego. W rezultacie całkowicie wyeliminowano przeregulowanie położenia oraz zjawisko zwane „chattering”.
EN
In recent years various approaches for quantified Boolean formula (QBF) solving have been developed, including methods based on expansion, skolemization and search. Here, we present a novel expansion-based solving technique that is motivated by concepts from the area of parameterized complexity. Our approach relies on dynamic programming over the tree decomposition of QBFs in prenex conjunctive normal form (PCNF). Hereby, binary decision diagrams (BDDs) are used for compactly storing partial solutions. Towards efficiency in practice, we integrate dependency schemes and develop dedicated heuristic strategies. Our experimental evaluation reveals that our implementation is competitive to state-of-the-art solvers on instances with one quantifier alternation. Furthermore, it performs particularly well on instances up to a treewidth of approximately 80, even for more quantifier alternations. Results indicate that our approach is orthogonal to existing techniques, with a large number of uniquely solved instances.
EN
In this paper, seven greedy heuristics for construction of association rules are compared from the point of view of the length and coverage of constructed rules. The obtained rules are compared also with optimal ones constructed by dynamic programming algorithms. The average relative difference between length of rules constructed by the best heuristic and minimum length of rules is at most 4%. The same situation is with coverage.
EN
This study presents a practical view of dynamic programming, specifically in the context of the application of finding the optimal solutions for the polygon triangulation problem. The problem of the optimal triangulation of polygon is considered to be as a recursive substructure. The basic idea of the constructed method lies in finding to an adequate way for a rapid generation of optimal triangulations and storing - them in as small as possible memory space. The upgraded method is based on a memoization technique, and its emphasis is in storing the results of the calculated values and returning the cached result when the same values again occur. The significance of the method is in the generation of the optimal triangulation for a large number of n. All the calculated weights in the triangulation process are stored and performed in the same table. Results processing and implementation of the method was carried out in the Java environment and the experimental results were compared with the square matrix and Hurtado-Noy method.
EN
The problem of optimally controlling a Wiener process until it leaves an interval (a, b) for the first time is considered in the case when the infinitesimal parameters of the process are random. When a = -∞, the exact optimal control is derived by solving the appropriate system of differential equations, whereas a very precise approximate solution in the form of a polynomial is obtained in the two-barrier case.
7
Content available remote Parallel cache-efficient code for computing the McCaskill partition functions
EN
We present parallel tiled optimized McCaskill's partition functions computation code. That CPU and memory intensive dynamic programming task is within computational biology. To optimize code, we use the authorial source-to-source TRACO compiler and compare obtained code performance with that generated with the state-of-the-art PluTo compiler based on the affine transformations framework (ATF). For the considered task, PluTo is able to generate only serial highly cache efficient code without any parallelism. A TRACO tiling and parallelizing strategy uses the transitive closure of a dependence graph to avoid affine function calculation. First, for each loop nest statement, rectangular tiles are formed. Then those tiles are corrected to be valid under lexicographical order if necessary. A correction is carried out by means of applying transitive closure. The validity of tiles guarantees that the inter-tile dependence graph is acyclic. So, a valid schedule for target tiles can be derived and applied to generate parallel tiled code. For this purpose, the ISL scheduler is used. An experimental study carried out on a multi-core computer demonstrates considerable speed-up of generated code for the larger number of threads. Generated parallel tiled code overcomes that generated with the PluTo compiler.
EN
Abstract interpretation is a well established theory that supports reasoning about the run-time behaviour of programs. It achieves tractable reasoning by considering abstractions of run-time states, rather than the states themselves. The chosen set of abstractions is referred to as the abstract domain. We develop a novel framework for combining (a possibly large number of) abstract domains. It achieves the effect of the so-called reduced product without requiring a quadratic number of functions to translate information among abstract domains. A central notion is a reference domain, a medium for information exchange. Our approach suggests a novel and simpler way to manage the integration of large numbers of abstract domains. We instantiate our framework in the context of string analysis. Browser-embedded dynamic programming languages such as JavaScript and PHP encourage the use of strings as a universal data type for both code and data values. The ensuing vulnerabilities have made string analysis a focus of much recent research. String analysis tends to combine many elementary string abstract domains, each designed to capture a specific aspect of strings. For this instance the set of regular languages, while too expensive to use directly for analysis, provides an attractive reference domain, enabling the efficient simulation of reduced products of multiple string abstract domains.
PL
W pracy pokazano zastosowanie teorii odnowy do wyznaczania optymalnego czasu eksploatacji środków transportu. Rozwiązanie tego typu oparto na programowaniu dynamicznym. Przedstawiono przykład obliczeń dla samochodu marki MAN TGS 18.400.
EN
The use of the regeneration theory to determine the optimal operating time of means of transport is shown in the paper. The solution of this problem is based on dynamic programming. An example of calculations for MAN TGS 18.400.
10
EN
It is discussed the using of dynamic programming method to optimize the parameters of the cascade of ideal mixing reactors, which is held isothermal first order reaction. It is found, that the minimum volume of the cascade of reactors corresponds to the minimum residence time of substance in this cascade. The optimum value of residence time for all reactors are equal and all ratio of input and output concentrations are equal, hence, and all volumes of reactors are also equal. A total volume of the cascade of reactors is less than the amount single. Application of the method of dynamic programming is illustrated with an example of the calculation of the polymerization in a cascade of four reactors according to the literature experimental data.
PL
Artykuł stanowi kontynuację badań dotyczących zmodyfikowanego algorytmu dynamicznego programowania dla optymalizacji reguł decyzyjnych względem pokrycia. Praca przedstawia wyniki eksperymentalne dotyczące regułowego klasyfikatora, dla zbiorów danych umieszczonych w Repozytorium Uczenia Maszynowego.
EN
The article is a continuation of research connected with a modified dy-namic programming algorithm for optimization of decision rules relative to coverage. The paper contains experimental results for rule based classifier using data sets from UCI Machine Learning Repository.
EN
Precise measurement of rail vehicle velocities is an essential prerequisite for the implementation of modern train control systems and the improvement of transportation capacity and logistics. Novel eddy current sensor systems make it possible to estimate velocity by using cross-correlation techniques, which show a decline in precision in areas of high accelerations. This is due to signal distortions within the correlation interval. We propose to overcome these problems by employing algorithms from the field of dynamic programming. In this paper we evaluate the application of correlation optimized warping, an enhanced version of dynamic time warping algorithms, and compare it with the classical algorithm for estimating rail vehicle velocities in areas of high accelerations and decelerations.
EN
Wireless Multimedia Sensor Networks (WMSNs) advances can route multimedia applications from source nodes to a sink. However, they require energy efficiency and network lifetime due to limited power resources in the sensor nodes. This paper proposes an energy-efficient routing optimization for multimedia transmission in WMSNs. The optimization utilizes a routing algorithm based on the dynamic programming. The routing optimization algorithm selects intermediary nodes which have minimum energy above 60%. Then, the priority selection of paths immediately finds neighboring nodes which have the greatest energy minimum. If there is the same minimum energy between the neighboring nodes, then the second priority selection is based on smaller link cost.
EN
In contrast to road-based traffic, the track as well as the corresponding duty cycle for railways are known beforehand, which represents a great advantage during the development of operating strategies for hybrid vehicles. Hence the benefits of hybrid vehicles regarding the fuel consumption can be exploited by means of an off-line optimisation. In this article, the fuel-optimal operating strategy is calculated for one specified track using two hybrid railway vehicles with different kinds of energy storage systems: on the one hand, a lithium-ion battery (high-energy storage) and, on the other, a double layer capacitor (high-power storage). For this purpose, control-oriented simulation models are developed for each architecture addressing the main effects contributing to the longitudinal dynamics of the power train. Based on these simulation models, the fuel-optimal operating strategy is calculated by two different approaches: Bellman’s dynamic programming, a well-known approach in this field, and an innovative sensitivity-based optimisation.
EN
A new dynamic programming based parallel algorithm adapted to on-board heterogeneous computers for simulation based trajectory optimization is studied in the context of “high-performance sailing”. The algorithm uses a new discrete space of continuously differentiable functions called the multi-splines as its search space representation. A basic version of the algorithm is presented in detail (pseudo-code, time and space complexity, search space auto-adaptation properties). Possible extensions of the basic algorithm are also described. The presented experimental results show that contemporary heterogeneous on-board computers can be effectively used for solving simulation based trajectory optimization problems. These computers can be considered micro high performance computing (HPC) platforms—they offer high performance while remaining energy and cost efficient. The simulation based approach can potentially give highly accurate results since the mathematical model that the simulator is built upon may be as complex as required. The approach described is applicable to many trajectory optimization problems due to its black-box represented performance measure and use of OpenCL.
EN
In the paper, an application of dynamic programming approach for optimization of association rules from the point of view of knowledge representation is considered. The association rule set is optimized in two stages, first for minimum cardinality and then for minimum length of rules. Experimental results present cardinality of the set of association rules constructed for information system and lower bound on minimum possible cardinality of rule set based on the information obtained during algorithm work as well as obtained results for length.
EN
Many problems from the area of AI have been shown tractable for bounded treewidth. In order to put such results into practice, quite involved dynamic programming (DP) algorithms on tree decompositions have to be designed and implemented. These algorithms typically show recurring patterns that call for tasks like subset minimization. In this paper we present a novel approach to obtain such DP algorithms from simpler principles, where the DP formalization of subset minimization is performed automatically. We first give a theoretical account of our novel method, and then present D-FLAT^2, a system that allows one to specify the core DP algorithm via answer set programming (ASP). We illustrate the approach at work by providing several DP algorithms that are more space-efficient than existing solutions, while featuring improved readability, reuse and therefore maintainability of ASP code. Experiments show that our approach also yields a significant improvement in runtime performance.
EN
In the paper, an application of dynamic programming approach to global optimization of approximate association rules relative to coverage and length is presented. It is an extension of the dynamic programming approach to optimization of decision rules to inconsistent tables. Experimental results with data sets from UCI Machine Learning Repository are included.
EN
In this paper, we develop a novel graph theoretic approach for protein threading. In order to perform the protein sequence-structure alignment in threading both efficiently and accurately, we develop a graph model to describe the tertiary structure of a protein family and the alignment between a sequence and a family can be efficiently computed with a dynamic programming algorithm when the tree width of the graph model is a small integer. Our experiments show that this new approach is significantly faster than existing tools for threading and can achieve comparable prediction accuracy.
EN
A dynamic programming-based algorithm adapted to on-board heterogeneous computers for simulation-based trajectory optimization was studied in the context of high-performance sailing. The algorithm can efficiently utilize all OpenCL-capable devices, starting the computation (if necessary, in single precision) on a GPU and finalizing it (if necessary, in double-precision) with the use of a CPU. The serial and parallel versions of the algorithm are presented in detail. Possible extensions of the basic algorithm are also described. The experimental results show that contemporary heterogeneous on-board/mobile computers can be treated as micro HPC platforms. They offer high performance (the OpenCL-capable GPU was found to accelerate the optimization routine 41 fold) while remaining energy and cost efficient. The simulation-based approach has the potential to give very accurate results, as the mathematical model upon which the simulator is based may be as complex as required. The black-box represented performance measure and the use of OpenCL make the presented approach applicable to many trajectory optimization problems.
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