Constrained Sampled-Data ARC for a Class of Cascaded Nonlinear Systems With Applications to Motor-Servo Systems

In this paper, sampled-data adaptive robust control is proposed for a class of uncertain cascaded nonlinear system with states and inputs constraints. The systematic design procedure can be divided into two steps: i) design a sampled-data adaptive robust controller for the plant to not only stabilize the closed-loop system but also track the desired command although there are a variety of uncertainties and disturbances in the system; ii) design a reference governor for the control system to avoid the states and inputs violating their limits. Finally, the proposed method is employed in Motor-servo system to demonstrate the effectiveness.