【摘要】 针对环境试验箱具有非线性、时变性、强耦合性使得经典控制理论难以对其进行有效控制的问题,提出了以模糊神经网络构成间接模型参考自适应控制方案,以满足系统稳定性、实时性的设计要求。阐述了如何运用模糊神经网络构造间接模型参考自适应控制系统及如何对模糊神经网络构造的辩识器和控制器进行学习和训练。仿真结果表明,该智能控制系统具有很强的鲁棒性和控制复杂被控对象的优越性。更多还原

【Abstract】 In view of the problem of the nonlinearity,time-varying and the strong coupling about Environment-Testing Case and the classical control theory can’t Control the Environment-Testing Case effectively, we put forward the model reference adaptive control project made up of fuzzy neural network to meet with the requirement of the stablity and rapidity about system. we explain how to configurate of the model reference adaptive control system using fuzzy neural network and how to train fuzzy neural network recognizer and controller. The result of emulation manifest the well compatibility of the system and the superiority of controlling complicated object.更多还原