Model free adaptive control with pseudo partial derivative based on fuzzy rule emulated network

In this article, a model free adaptive control with the estimated pseudo partial derivative (PPD) is introduced by multi-input fuzzy rules emulated network (MiFREN) for a class of discrete-time systems. The resetting mechanism can be relaxed in this adaptation scheme. Human knowledge about the controlled plant is rearranged to define the IF-THEN rules directly. Those fixed parameters are designed according to guarantee the convergence related on the controller performance. All adjustable parameters inside MiFREN are tuned by the proposed on-line learning algorithm. The design example and simulation results demonstrate the performance of the proposed controller under the nominal system and system with disturbances.