OUTPUT PREDICTIVE CONTROL FOR ENDOVASCULAR MRI-GUIDED NANOROBOTS WITH CONTROL DELAY

This paper proposes an output predictive control design for the endovascular Magnetic Resonance Imaging (MRI)-guided nanorobots in the presence of control delay. Considering the effects of hydrodynamic drag force, apparent weight, and magnetic motive force, we establish the state-space representation model of nanorobots. The state-feedback control (SFC) is designed by using feedback linearisation approach. The high-gain predictor is constructed to implement the predicted states in the SFC physically. The performance recovery property is proved, namely, the ultimate boundedness, exponential stability, and trajectory closeness of output feedback recovers those of state feedback. The numerical simulation demonstrates the effectiveness of the designed controllers and the performance recovery property of the designed high-gain predictor.