Adaptive Backstepping Control Using RBF Networks for Magnetic Levitation Systems

For a class of magnetic levitation systems, the problem of the design and analysis for adaptive backstepping controller based on RBF networks is studied. Firstly, under the weaker assumptions, the states of closed-loop system lying in a compact set is guaranteed by introducing a supervisory control. Then by the approximation property of RBF networks and backstepping design technique, the design of robust adaptive controller is given. By Lyapunov stability theory, the stability and tracking performance of the adaptive control system are analyzed rigorously.