Observer control in a tracking problem via model predictive control

The paper describes a model predictive control (MPC) approach for optimally (in a receding horizon sense) controlling the trajectory of a mobile tracker to minimize errors in estimating the state of another, moving object. With the use of the MPC approach, pointwise-in-time state and control constraints can be enforced for the mobile tracker, and its control system can react dynamically to changing operating conditions (such as new obstacles appearing or disappearing). After a discussion of this problem in a general setting, the paper focuses on a case study of the mobile tracker and moving object on a plane. The mobile tracker can measure the distance to the moving object and this measurement is affected by noise. The effect of the noise may increase if the line of sight from the mobile tracker to the moving object deviates from the orientation of the moving tracker or it passes through interference zones and, in addition, the mobile tracker has to stay clear of the obstacles.