Magnetic Levitation Hardware-in-the-Loop and MATLAB-Based Experiments for Reinforcement of Neural Network Control Concepts

Abstract

This paper discusses the use of a real-time digital control environment with a hardware-in-the-loop (HIL) magnetic levitation (Maglev) device for modeling and controls education, with emphasis on neural network (NN) feedforward control. Many educational advantages are realized for the students if a single environment is used for simulation, hardware implementation, and verification as compared with multienvironment settings. This real-time environment requires two personal computers (host and target) employed to control an HIL system. It requires software tools by MathWorks, Inc., a C++ compiler, an off-the-shelf data acquisition card, and the HIL (a nonlinear, open-loop, unstable, and time-varying, custom-built Maglev device) to be controlled. This environment provides for experimentation, such as data collection for system identification using NNs and their implementation as static nonlinear feedforward controllers. In addition, this environment was used to implement and demonstrate NNs with real-time dynamic weight tuning and controller performance comparison under various inputs or changes in the HIL device dynamics, as shown in the presented examples. The educational features of this environment were verified in a classroom setting in a graduate-level NN class. The presented environment is applicable to senior or graduate level (introductory intelligent and digital control) or a general introductory course on NNs with applications.