期刊名称：Proceedings of the Canadian Engineering Education Association
出版年度：2011
语种：English
出版社：The Canadian Engineering Education Association (CEEA)
摘要：The objective herein is to demonstrate the feasibility of a real-time digital control of a 2 DOF magnetic levitation device for modeling and controls education, with emphasis on predictive holographic neural network control. The plant of interest is a magnetic levitation device that is nonlinear and open-loop unstable. In this application, the reference model of the plant is a neural network that has an embedded nominal linear model in the network weights. The control based on the linear model provides initial stability at the beginning of network training. In using a holographic neural network the control laws are nonlinear and online adaptation of the model is possible to capture unmodeled or time-varying dynamics. Such an environment provides for experimentation, data collection, system identification and novel control strategy implementation. The environment is used to implement predictive holographic neural networks with real-time dynamic weight tuning and controller performance comparison under various trajectories input. The educational features of this environment are being tested in a senior control engineering classroom setting.
