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A Predictive Controler for Object Tracking of a Mobile Robot

Research output: Contribution to conference Conference paper

Publication date11/05/2008
Number of pages10
<mark>Original language</mark>English


ConferenceThe Second International Workshop on Intelligent Vehicle Control Systems, IVCS 2008 in the framework of the 5th International Conference on Informatics in Control, Automation, and Modelling, ICINCO 2008
CityFunchal, Madeira, Portugal


In this paper a predictive controller for real-time target tracking in mobile robotics is proposed based on adaptive/evolving Takagi-Sugeno fuzzy systems, eTS. The predictive controller consists of two modules; i) a conventional fuzzy controller for robot motion control, and ii) a modelling tool for estimation of the target movements. The prediction of target movements enables the controller to be aware and to respond to the target movement in advance. Successful prediction will minimise the response delay of the conventional controller and improve the control quality. The model learning using eTS is fully automatic and performed ‘on fly’, ‘from scratch’. Data are processed in ‘one-pass’ manner, therefore it requires very limited computational resource and is suitable for on-board implementation on the mobile robots. Predictions are made in real-time. The same technique also has the potential to be used in the process control. Two reference controllers, a controller based on the Mamdani-Type fuzzy rule-base, and a controller based on the simple linear model, are also implemented in order to verify the proposed predictive controller. Experiments are carried out with a real mobile robot Pioneer 3DX. The performance of the three controllers is analyzed and compared.