Abstract

The paper proposes the model of a control system based on the controlled object state. The model includes a state observer and a state controller. The reference signal for this control system is the required values of the controlled object state variables. As a state observer of a controlled object in the control system model, the system "extended Kalman filter - adaptive digital filter" (the EKF-ADF system) is used. The structure and operation principle of the control system state controller are described. The adaptive algorithm of the control system state controller is presented.
 The control system state controller with the adaptive algorithm uses the output data of the EKF-ADF system to form the controller output (error) vector. The output data consist of the state estimation vector performed by the EKF of the EKF-ADF system and the vector of the corrected state estimation performed by the ADF of the EKF-ADF system. The adaptive algorithm of the control system state controller takes into account the output data of the EKF-ADF system in such a way as to form the most reliable state controller output vector.
 To confirm the effectiveness of the considered control system, the control process numerical simulation results of a mobile robot with a caterpillar mover are presented: the proposed control system simulation results are compared with the simulation results of the control system that uses the EKF as a state observer.
 The combination of the state observer and the state regulator as part of the proposed control system makes it possible to control dynamic objects with state variables which are inaccessible to direct measurement and have non-periodic external disturbances.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call