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    Wyświetlanie 1-4 z 4
    Tytuł:
    Evolutionary computation approaches to tip position controller design for a two-link flexible manipulator
    Autorzy:
    Subudhi, B.
    Ranasingh, S.
    Swain, A. K.
    Powiązania:
    https://bibliotekanauki.pl/articles/229971.pdf
    Data publikacji:
    2011
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    flexible manipulator
    genetic algorithm
    bacteria foraging
    fitness function
    Opis:
    Controlling multi-link flexible robots is very difficult compared rigid ones due to inter-link coupling, nonlinear dynamics, distributed link flexure and under-actuation. Hence, while designing controllers for such systems the controllers should be equipped with optimal gain parameters. Evolutionary Computing (EC) approaches such as Genetic Algorithm (GA), Bacteria Foraging Optimization (BFO) are popular in achieving global parameter optimizations. In this paper we exploit these EC techniques in achieving optimal PD controller for controlling the tip position of a two-link flexible robot. Performance analysis of the EC tuned PD controllers applied to a two-link flexible robot system has been discussed with number of simulation results.
    Źródło:
    Archives of Control Sciences; 2011, 21, 3; 269-285
    1230-2384
    Pojawia się w:
    Archives of Control Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Hybrid Mesh Adaptive Direct Search and Genetic Algorithms Techniques for industrial production systems
    Autorzy:
    Vasant, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/229988.pdf
    Data publikacji:
    2011
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    mesh adaptive direct search
    genetic algorithms
    fitness function
    degree of possibility
    level of satisfaction
    Opis:
    In this paper, computational and simulation results are presented for the performance of the fitness function, decision variables and CPU time of the proposed hybridization method of Mesh Adaptive Direct Search (MADS) and Genetic Algorithm (GA). MADS is a class of direct search of algorithms for nonlinear optimization. The MADS algorithm is a modification of the Pattern Search (PS) algorithm. The algorithms differ in how the set of points forming the mesh is computed. The PS algorithm uses fixed direction vectors, whereas the MADS algorithm uses random selection of vectors to define the mesh. A key advantage of MADS over PS is that local exploration of the space of variables is not restricted to a finite number of directions (poll directions). This is the primary drawback of PS algorithms, and therefore the main motivation in using MADS to solve the industrial production planning problem is to overcome this restriction. A thorough investigation on hybrid MADS and GA is performed for the quality of the best fitness function, decision variables and computational CPU time.
    Źródło:
    Archives of Control Sciences; 2011, 21, 3; 299-312
    1230-2384
    Pojawia się w:
    Archives of Control Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Optimization of thermo-electric coolers using hybrid genetic algorithm and simulated annealing
    Autorzy:
    Khanh, D. V. K.
    Vasant, P.
    Elamvazuthi, I.
    Dieu, V. N.
    Powiązania:
    https://bibliotekanauki.pl/articles/230105.pdf
    Data publikacji:
    2014
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    thermo-electric coolers
    genetic algorithm
    simulated annealing
    coefficient of performance
    rate of refrigeration
    fitness function
    Opis:
    Thermo-electric Coolers (TECs) nowadays are applied in a wide range of thermal energy systems. This is due to their superior features where no refrigerant and dynamic parts are needed. TECs generate no electrical or acoustical noise and are environmentally friendly. Over the past decades, many researches were employed to improve the efficiency of TECs by enhancing the material parameters and design parameters. The material parameters are restricted by currently available materials and module fabricating technologies. Therefore, the main objective of TECs design is to determine a set of design parameters such as leg area, leg length and the number of legs. Two elements that play an important role when considering the suitability of TECs in applications are rated of refrigeration (ROR) and coefficient of performance (COP). In this paper, the review of some previous researches will be conducted to see the diversity of optimization in the design of TECs in enhancing the performance and efficiency. After that, single-objective optimization problems (SOP) will be tested first by using Genetic Algorithm (GA) and Simulated Annealing (SA) to optimize geometry properties so that TECs will operate at near optimal conditions. Equality constraint and inequality constraint were taken into consideration.
    Źródło:
    Archives of Control Sciences; 2014, 24, 2; 155-176
    1230-2384
    Pojawia się w:
    Archives of Control Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Short-term load prediction model combining FEW and IHS algorithm
    Autorzy:
    Yu, Mingxing
    Zhu, Jiazheng
    Yang, Li
    Powiązania:
    https://bibliotekanauki.pl/articles/141740.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    evaluation criteria
    exponential fuzzy time series
    fitness function
    improved harmony search algorithms
    load forecasting
    optimal interval length
    Opis:
    :Accurate prediction of power load plays a crucial role in the power industry and provides economic operation decisions for the power operation department. Due to the unpredictability and periodicity of power load, an improved method to deal with complex nonlinear relation was adopted, and a short-term load forecasting model combining FEW (fuzzy exponential weighting) and IHS (improved harmonic search) algorithms was proposed. Firstly, the domain space was defined, the harmony memory base was initialized, and the fuzzy logic relation was identified. Then the optimal interval length was calculated using the training sample data, and local and global optimum were updated by optimization criteria and judging criteria. Finally, the optimized parameters obtained by an IHS algorithm were applied to the FEW model and the load data of the Huludao region (2013) in Northeast China in May. The accuracy of the proposed model was verified using an evaluation criterion as the fitness function. The results of error analysis show that the model can effectively predict short-term power load data and has high stability and accuracy, which provides a reference for application of short-term prediction in other industrial fields.
    Źródło:
    Archives of Electrical Engineering; 2019, 68, 4; 907-923
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

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