Prediction governor for nonlinear affine systems and its application to automatic cruise control

This paper focuses on the control of dynamical systems under the case that actual reference signals can not be available in real time. In such case, although predicted values are used as reference signals, the prediction errors degrade the control performance of the systems. To overcome this problem, the previous work presented the prediction governor which shapes predicted values. However, the previous result can not be applied to nonlinear systems. Motivated by this, this paper addresses the design problem of prediction governors for input affine nonlinear systems. Then, we analytically derive an optimal prediction governor which is characterized by plant models. Furthermore, we apply it to the automatic cruise control problem, and its usefulness is illustrated by a numerical example.