Search results for: Non-deterministic

Authors: Nazir Ahmad Zafar, Nabeel Sabir, Amir Ali

Abstract:

Functionalities and control behavior are both primary requirements in design of a complex system. Automata theory plays an important role in modeling behavior of a system. Z is an ideal notation which is used for describing state space of a system and then defining operations over it. Consequently, an integration of automata and Z will be an effective tool for increasing modeling power for a complex system. Further, nondeterministic finite automata (NFA) may have different implementations and therefore it is needed to verify the transformation from diagrams to a code. If we describe formal specification of an NFA before implementing it, then confidence over transformation can be increased. In this paper, we have given a procedure for integrating NFA and Z. Complement of a special type of NFA is defined. Then union of two NFAs is formalized after defining their complements. Finally, formal construction of intersection of NFAs is described. The specification of this relationship is analyzed and validated using Z/EVES tool.

Keywords: Modeling, Nondeterministic finite automata, Znotation, Integration of approaches, Validation.

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Authors: Abdulmajid Mukhtar Afat

Abstract:

This paper aims at introducing nondeterministic finite automata with ε value which is used to perform some operations on languages. a program is created to implement the algorithm that converts nondeterministic finite automata with ε value (ε-NFA) to deterministic finite automata (DFA).The program is written in c++ programming language. The program inputs are FA 5-tuples from text file and then classifies it into either DFA/NFA or ε -NFA. For DFA, the program will get the string w and decide whether it is accepted or rejected. The tracking path for an accepted string is saved by the program. In case of NFA or ε-NFA automation, the program changes the automation to DFA to enable tracking and to decide if the string w exists in the regular language or not.

Keywords: Finite automata, DFA, NFA, ε-NFA, Eclose, operations on languages.

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Authors: Abdulmajid Mukhtar Afat

Abstract:

This paper aims at introducing finite automata theory, the different ways to describe regular languages and create a program to implement the subset construction algorithms to convert nondeterministic finite automata (NFA) to deterministic finite automata (DFA). This program is written in c++ programming language. The program reads FA 5tuples from text file and then classifies it into either DFA or NFA. For DFA, the program will read the string w and decide whether it is acceptable or not. If accepted, the program will save the tracking path and point it out. On the other hand, when the automation is NFA, the program will change the Automation to DFA so that it is easy to track and it can decide whether the w exists in the regular language or not.

Keywords: Finite Automata, subset construction DFA, NFA.

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Authors: A. A. Hossam-Eldin, E. N. Abdallah, M. S. El-Nozahy

Abstract:

Power system state estimation is the process of calculating a reliable estimate of the power system state vector composed of bus voltages' angles and magnitudes from telemetered measurements on the system. This estimate of the state vector provides the description of the system necessary for the operation and security monitoring. Many methods are described in the literature for solving the state estimation problem, the most important of which are the classical weighted least squares method and the nondeterministic genetic based method; however both showed drawbacks. In this paper a modified version of the genetic algorithm power system state estimation is introduced, Sensitivity of the proposed algorithm to genetic operators is discussed, the algorithm is applied to case studies and finally it is compared with the classical weighted least squares method formulation.

Keywords: Genetic algorithms, ill-conditioning, state estimation, weighted least squares.

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Authors: Makoto Nagatomo, Yasuo Uchida, Makoto Sakamoto, Tuo Zhang, Tatsuma Kurogi, Takao Ito, Tsunehiro Yoshinaga, Satoshi Ikeda, Masahiro Yokomichi, Hiroshi Furutani

Abstract:

This paper presents a four-dimensional computational model, k-neighborhood template A-type three-dimensional bounded cellular acceptor (abbreviated as A-3BCA(k)), and discusses the hierarchical properties. An A-3BCA(k) is a four-dimensional automaton which consists of a pair of a converter and a configuration-reader. The former converts the given four-dimensional tape to the three- and two- dimensional configuration and the latter determines the acceptance or nonacceptance of given four-dimensional tape whether or not the derived two-dimensional configuration is accepted. We mainly investigate the difference of the accepting power based on the difference of the configuration-reader. It is shown that the difference of the accepting power of the configuration-reader tends to affect directly that of the A-3BCA(k) for the case when the converter is deterministic. On the other hand, results are not analogous for the nondeterministic case.

Keywords: Cellular acceptor, configuration-reader, converter, finite automaton, four-dimension, on-line tessellation acceptor, parallel/sequential array acceptor, turing machine.

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Authors: Liu Ning, Zhong Chongquan, Teng Hongfei

Abstract:

EPA (Ethernet for Plant Automation) resolves the nondeterministic problem of standard Ethernet and accomplishes real-time communication by means of micro-segment topology and deterministic scheduling mechanism. This paper studies the real-time performance of EPA periodic data transmission from theoretical and experimental perspective. By analyzing information transmission characteristics and EPA deterministic scheduling mechanism, 5 indicators including delivery time, time synchronization accuracy, data-sending time offset accuracy, utilization percentage of configured timeslice and non-RTE bandwidth that can be used to specify the real-time performance of EPA periodic data transmission are presented and investigated. On this basis, the test principles and test methods of the indicators are respectively studied and some formulas for real-time performance of EPA system are derived. Furthermore, an experiment platform is developed to test the indicators of EPA periodic data transmission in a micro-segment. According to the analysis and the experiment, the methods to improve the real-time performance of EPA periodic data transmission including optimizing network structure, studying self-adaptive adjustment method of timeslice and providing data-sending time offset accuracy for configuration are proposed.

Keywords: EPA system, Industrial Ethernet, Periodic data, Real-time performance

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Authors: Johan Wall, Johan Fredin, Anders Jönsson, Göran Broman

Abstract:

Designing modern machine tools is a complex task. A simulation tool to aid the design work, a virtual machine, has therefore been developed in earlier work. The virtual machine considers the interaction between the mechanics of the machine (including structural flexibility) and the control system. This paper exemplifies the usefulness of the virtual machine as a tool for product development. An optimisation study is conducted aiming at improving the existing design of a machine tool regarding weight and manufacturing accuracy at maintained manufacturing speed. The problem can be categorised as constrained multidisciplinary multiobjective multivariable optimisation. Parameters of the control and geometric quantities of the machine are used as design variables. This results in a mix of continuous and discrete variables and an optimisation approach using a genetic algorithm is therefore deployed. The accuracy objective is evaluated according to international standards. The complete systems model shows nondeterministic behaviour. A strategy to handle this based on statistical analysis is suggested. The weight of the main moving parts is reduced by more than 30 per cent and the manufacturing accuracy is improvement by more than 60 per cent compared to the original design, with no reduction in manufacturing speed. It is also shown that interaction effects exist between the mechanics and the control, i.e. this improvement would most likely not been possible with a conventional sequential design approach within the same time, cost and general resource frame. This indicates the potential of the virtual machine concept for contributing to improved efficiency of both complex products and the development process for such products. Companies incorporating such advanced simulation tools in their product development could thus improve its own competitiveness as well as contribute to improved resource efficiency of society at large.

Keywords: Machine tools, Mechatronics, Non-deterministic, Optimisation, Product development, Virtual machine

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Authors: Hadi Firouzi, Majid Nili Ahmadabadi, Babak N. Araabi

Abstract:

Conceptualization strengthens intelligent systems in generalization skill, effective knowledge representation, real-time inference, and managing uncertain and indefinite situations in addition to facilitating knowledge communication for learning agents situated in real world. Concept learning introduces a way of abstraction by which the continuous state is formed as entities called concepts which are connected to the action space and thus, they illustrate somehow the complex action space. Of computational concept learning approaches, action-based conceptualization is favored because of its simplicity and mirror neuron foundations in neuroscience. In this paper, a new biologically inspired concept learning approach based on the probabilistic framework is proposed. This approach exploits and extends the mirror neuron-s role in conceptualization for a reinforcement learning agent in nondeterministic environments. In the proposed method, instead of building a huge numerical knowledge, the concepts are learnt gradually from rewards through interaction with the environment. Moreover the probabilistic formation of the concepts is employed to deal with uncertain and dynamic nature of real problems in addition to the ability of generalization. These characteristics as a whole distinguish the proposed learning algorithm from both a pure classification algorithm and typical reinforcement learning. Simulation results show advantages of the proposed framework in terms of convergence speed as well as generalization and asymptotic behavior because of utilizing both success and failures attempts through received rewards. Experimental results, on the other hand, show the applicability and effectiveness of the proposed method in continuous and noisy environments for a real robotic task such as maze as well as the benefits of implementing an incremental learning scenario in artificial agents.

Keywords: Concept learning, probabilistic decision making, reinforcement learning.

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