Direct Adaptive Fuzzy Control with Less Restrictions on the Control Gain

In the adaptive fuzzy and neural network control field, there are two basic configurations: direct and indirect. It is well known that the direct configuration needs more restrictions on the control gain than the indirect configuration. In this paper, we propose a direct adaptive fuzzy controller with less restrictions on the control gain. Using an extension of the universal approximation theorem, we show that the only required constraint on the control gain is that its sign is known. We also show that using the approximation error estimator enhances performance. Finally, application to an inverted pendulum demonstrates the effectiveness of the proposed controller.