首页> 外文OA文献 >PARETO OPTIMAL SOLUTION OF MULTIOBJECTIVE SYNTHESIS OF ROBUST CONTROLLERS OF MULTIMASS ELECTROMECHANICAL SYSTEMS BASED ON MULTISWARM STOCHASTIC MULTIAGENT OPTIMIZATION
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PARETO OPTIMAL SOLUTION OF MULTIOBJECTIVE SYNTHESIS OF ROBUST CONTROLLERS OF MULTIMASS ELECTROMECHANICAL SYSTEMS BASED ON MULTISWARM STOCHASTIC MULTIAGENT OPTIMIZATION

机译:基于MultiSwarm随机多算法优化的多数学机电系统鲁棒控制器多标注综合的Pareto最优解

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摘要

Purpose. Developed the method for solving the problem of multiobjective synthesis of robust control by multimass electromechanical systems based on the construction of the Pareto optimal solutions using multiswarm stochastic multi-agent optimization of particles swarm, which reduces the time of determining the parameters of robust controls multimass electromechanical systems and satisfy a variety of requirements that apply to the work of such systems in different modes. Methodology. Multiobjective synthesis of robust control of multimass electromechanical systems is reduced to the solution of solving the problem of multiobjective optimization. To correct the above problem solving multiobjective optimization in addition to the vector optimization criteria and constraints must also be aware of the binary preference relations of local solutions against each other. The basis for such a formal approach is to build areas of Pareto-optimal solutions. This approach can significantly narrow down the range of possible solutions of the problem of optimal initial multiobjective optimization and, consequently, reduce the complexity of the person making the decision on the selection of a single version of the optimal solution. Results. The results of the synthesis of multi-criteria electromechanical servo system and a comparison of dynamic characteristics, and it is shown that the use of synthesized robust controllers reduced the error guidance working mechanism and reduced the system sensitivity to changes in the control parameters of the object compared to the existing system with standard controls. Originality. For the first time, based on the construction of the Pareto optimal solutions using a multiswarm stochastic multi-agent optimization particle algorithms improved method for solving formulated multiobjective multiextremal nonlinear programming problem with constraints, to which the problem of multiobjective synthesis of robust controls by multimass electromechanical systems that can significantly reduce the time to solve problems and meet a variety of requirements that apply to the multimass electromechanical systems in different modes. Practical value. Practical recommendations on reasonable selection of the target vector of robust control by multimass electromechanical systems. Results of synthesis of electromechanical servo system shown that the use of synthesized robust controllers reduced the error guidance of working mechanism and reduce the system sensitivity to changes of plant parameters compared to a system with standard controls.
机译:目的。开发了解决多数码机电系统基于粒子群的帕累托最优解的构造解决多数码机电系统的多重机电控制问题的方法,这减少了确定鲁棒控制的参数多摩数机电的时间系统并满足各种要求,适用于不同模式的这种系统的工作。方法。多摩贷机电系统鲁棒控制的多标注合成减少到解决多目标优化问题的解决方案。为了纠正上述问题解决多目标优化,除了矢量优化标准之外,还必须了解局部解决方案的二进制偏好关系。这种正式方法的基础是建立帕累托最佳解决方案的领域。这种方法可以显着缩小最佳初始多目标优化问题的可能解决方案的范围,并且因此降低了对选择单个版本的最佳解决方案的决定的人的复杂性。结果。多标准机电伺服系统合成的结果和动态特性的比较,并显示了合成的鲁棒控制器的使用减少了误差引导工作机制,并降低了对物体控制参数的变化的系统敏感性与现有系统相比具有标准控件。独创性。首次基于使用多种速度的多种子型优化粒子算法来构建帕累托最优解的构建方法,改进了由约束解决配制的多目标多觉非线性规划问题的方法,多数制机电耦合鲁棒控制的多标注合成问题可以显着减少解决问题的时间并满足适用于不同模式的多数码机电系统的各种要求的系统。实用价值。关于合理选择多数码机电系统的鲁棒控制目标矢量的实用建议。机电伺服系统的合成结果表明,与具有标准控制的系统相比,使用合成鲁棒控制器的使用减少了工作机制的误差引导,并降低了对工厂参数变化的系统敏感性。

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  • 作者

    T. B. Nikitina;

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  • 年度 2017
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  • 原文格式 PDF
  • 正文语种 eng;rus;ukr
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