Event-based model-free adaptive control for discrete-time non-linear processes
In this study, a novel event-based model-free adaptive control (MFAC) algorithm for discrete-time non-linear systems is presented. Different from the traditional MFAC scheme which calculates the control signal at fixed sampling instants, an event-based sampling scheme is given to calculate the new control signal only when the input/output (I/O) data sufficiently changes. The event-triggered MFAC can obviously reduce the computational load and network communication. The closed-loop system is proven to be ultimately bounded by using the Lyapunov technique. Finally, the simulation examples indicate the effectiveness and applicability of the proposed event-trigger model-free adaptive control algorithm.