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悬浮控制是磁悬浮系统的关键问题之一,其牵引系统必须在稳定悬浮的基础上设计。为了降低悬浮的能量损耗,在本文的悬浮系统中加入了永磁磁极。提出了结合神经控制和传统PID控制的混合悬浮系统的神经元PID控制策略,该策略有很好的在线学习能力,自适应神经元通过自学习和相关搜索方法,用于调节PID控制器的参数,实现实时性能优化。所提出的控制策略经实验验证,在未知数学模型的情况下,可实现快速、精确和稳定的悬浮。
Suspension control is one of the key problems of the magnetic levitation system. Its traction system must be designed on the basis of stable levitation. In order to reduce the suspended energy loss, the permanent magnet poles are added in the suspension system of this paper. A neuron PID control strategy based on hybrid suspension system combining neural control and traditional PID control is proposed. The strategy has good online learning ability. The adaptive neuron is used to adjust the parameters of the PID controller through self-learning and related search methods , To achieve real-time performance optimization. The proposed control strategy is validated experimentally and enables fast, accurate and stable suspension with unknown mathematical models.