【作者】 王欣；

【导师】 曹承志；

【作者基本信息】 沈阳工业大学 ， 检测技术与自动化装置， 2004， 硕士

【摘要】 本文提出集成智能算法实现对异步电动机直接转矩控制系统的控制。集成智能算法是各种智能算法的集大成，它利用各自智能算法的优点互相取长补短，发挥整体优势。本文所采用的集成智能算法是模糊理论，神经网络，遗传算法和免疫算法的集成，并且提出了用免疫遗传算法优化模糊神经网络的新控制算法。 模糊理论运用模糊集理论将控制知识和经验以模糊量形式表达，并运用模糊推理方法进行决策、实施控制，其数学理论体系完整，算法明确。神经网络不需要精确的数学模型，能够解决许多复杂的、不确定的和非线性的问题，在大信息处理与复杂的实时控制方面显示出巨大的优势和潜力。遗传算法对许多用传统数学难以解决或明显失效的复杂问题，特别是最优化问题提供了一个有效的途径。免疫算法从生物免疫系统中获得启示，对开发设计新的智能优化模型，具有重要意义和发展前景。 异步电动机直接转矩控制具有控制算法简单、动态响应快，受较少电动机参数影响等特点，是继矢量控制之后出现的另一种高性能的异步电动机控制方法。本课题采用基于免疫系统与遗传算法相结合的免疫遗传算法优化模糊神经网络控制器实现对异步电动机进行直接转矩控制，它进一步解决了直接转矩控制中的参数优化和低速性能不好的问题，提高了该系统的静动态性能。基于免疫遗传算法的模糊神经网络控制器具有比模糊神经网络控制器更好的性能，它使整个控制系统易于稳定，调节速度快，在控制中明显优于其它的控制方式，这将使基于直接转矩控制技术的感应电动机的用途进一步拓展。更多还原

【Abstract】 In the paper, we brought forward using integrated algorithm to realize the control of the DCT system. Integrated intelligent algorithm is the integration of intelligent algorithm. It learns from strong points of the intelligent algorithm to offset their weakness and exert the superiority of entirety. In the paper, the integrated intelligent algorithm we adapted is the integration of fuzzy theory, neural network, genetic algorithm and immune algorithm. And bringing forward the new algorithm of FNN optimized by immune genetic algorithm.Fuzzy theory adapts fuzzy set theory to express control information and experience by fuzzy quantity and manage fuzzy reasoning to decide and control. Its mathematical theory system is integrated and algorithm is clear. Neural network needn’t precise mathematical model. It can settle many complex, uncertain and nonlinear problems. In the information processing and complex real time control, it brought out great dominant and potentiality. Genetic algorithm provides an efficient channel to complex problems that tradition mathematic is difficult to settle or obvious failure, especially optimization problems. Immune algorithm obtains pointer from organism immune system. It has important meaning and long term potential to develop and plan new intelligent optimization model.Induction motor DTC has the performances of control algorithm easy, dynamic response fast and motor parameters affect less. It is a high performance induction motor control method after vector control. The thesis adapted immune genetic algorithm based on combination of immune system and genetic algorithm to optimize FNN and realize DTC of induction motor. It settled the problems of parameter optimization and performance of low velocity. It improved static property and dynamic performance of system. FNN controller based on immune genetic algorithm has better performance than FNN controller. It can make the control system stability and regulating speed faster. In control, it gets an advantage over other methods. It can make the use of induction motor that based on DTC technique further prolongation.更多还原