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This paper proposes an output predictive control design for the endovascular magnetic resonance imaging (MRI)-guided nanorobots in the presence of actuator and sensor delays. The nanorobot is modeled considering the effects of hydrodynamic drag force, apparent weight, and magnetic motive force. Using feedback linearization approach, the state feedback control is designed. To physically implement the predicted states in the state feedback control, the high-gain predictor is constructed. The performance recovery property of the output feedback using the high-gain predictor is achieved. The numerical simulation demonstrates the effectiveness of the designed controllers and the performance recovery property of the designed high-gain predictor. [ABSTRACT FROM AUTHOR]

This paper presents tracking control method for wheeled mobile robots (WMRs) with state, sensor and control delays. The differential equations are obtained from the kinematic model of WMR with Pfaffian constraint. Thus, the state-space representations of WMR motion system and the target path system can be achieved. And the tracking error system with state, sensor and control delays is got. A nonlinear tracking control is designed with not only the state of future time but also that of past time. The exponential stability of the closed-loop system under the tracking control is proved. Since the control has the predictive states, it cannot be physically implemented. A high-gain observer (HGO) is constructed to solve this physical implement problem. Moreover, the exponential stability of the errors between the original states and the generated states from HGO is demonstrated. The simulation experiments verified the effectiveness, convenience and simplicity of the designed state-feedback control (SFC) and the output feedback control (OFC) via HGO, which illustrates that the target paths of a circle and a figure-of-8 can be successfully tracked by WMR under the proposed controllers by this paper. [ABSTRACT FROM AUTHOR]