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本文研究以人机智能结合的方式实现模糊控制的优化设计.在相平面非线性规划的基础上,采用神经模糊混合网络完成局域的优化设计.前者通过对控制过程的合理分解,实现快速过渡过程与平稳、高精度的稳态性能的统一;后者基于网络学习,实现知识自动获取,消除不合理因素,改善控制效果.从而为模糊控制设计提供通用、简单而有效的方法.针对复杂的电液伺服系统进行控制实验,获得了满意的效果.
In this paper, the optimal design of fuzzy control is realized by the combination of human-machine intelligence and intelligent control.On the basis of phase-plane nonlinear programming, the optimal design of the local area is achieved by using the neural-fuzzy hybrid network.The former achieves the rapid transition through the reasonable decomposition of the control process Process and steady, high-precision steady-state performance of the unity; the latter based on the network learning, knowledge acquisition to eliminate unreasonable factors to improve the control effect. So as to provide a common fuzzy control design, simple and effective method for complex Electro-hydraulic servo system control experiments, obtained satisfactory results.