Adaptive extremum-seeking receding horizon control of nonlinear systems

We present a control algorithm that incorporates real time optimization and receding horizon control technique to solve an extremum seeking control problem for a class of nonlinear systems with parametric uncertainties. A Lyapunov-based technique is employed to develop a receding horizon controller that drives the system states to the desired unknown extremum points when it can be shown that a persistency of excitation condition is satisfied. A simulation example is provided to illustrate the effectiveness of the proposed method.