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A Novel Control-Navigation System- Based Adaptive Optimal Controller & EKF Localization of DDMR

Dalia Kass, Abdulkader Joukhadar

发表年份
2015
引用次数
6
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摘要

This paper presents a newly developed approach for Differential Drive Mobile Robot (DDMR). The main goal is to provide a high dynamic system response in the joint space level, the low level control, as well as to enhance the DDMR localization. The proposed approach depends on a Linear Quadratic Regulator (LQR) for the low level control and an Adaptive LQR for the high level control. The investigated DDMR is considered highly nonlinear system due to uncertainty exhibited by the mobile robot incorporated with actuators nonlinearity. DDMR’s uncertainty leads to erroneous localization. An Extended Kalman Filter (EKF) -based approach with fusion sensors is used to enhance the robot degree of belief for its posture. Intensive simulation results obtained from the developed uncertain model and the proposed approach have shown very good dynamic performance on the low level control and very good convergence to the desired posture of the mobile robot path with the presence of robot uncertainty.

关键词

Control theory (sociology)Linear-quadratic regulatorExtended Kalman filterComputer scienceMobile robotController (irrigation)RobotConvergence (economics)Nonlinear systemKalman filter

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