A Dynamic Target Tracking of Car-Like Wheeled Robot in a Sensor-Network Environment via Fuzzy Decentralized Sliding-Mode Grey Prediction Control

For implementing dynamic target tracking, two distributed CCD (charge-coupled device) cameras are set up to capture the poses of the tracking and target cars, which have the front-wheel for the steering orientation and the rear-wheel for the forward-backward motion. Based on the control authority of these two CCD cameras, a suitable reference command for the proposed controller of the tracking car is planned on a personal computer and then transmitted to the tracking car by a wireless device. Only the information of the upper bound of system knowledge is required to select the suitable scaling factors and coefficients of sliding surface for the proposed controller so that an acceptable performance is achieved. Since the target car is dynamic and the tracking car possesses dynamics, a grey prediction for the pose of the target car is employed to plan an effective reference command for the tracking car to enhance the performance of target tracking. Finally, a sequence of experiments is carried out to confirm the usefulness of the proposed control system.