基于动态T－S模糊控制的视觉目标跟随

针对基于传统线性控制律的移动机器人视觉目标跟随系统的角度误差控制无法满足高效和快速的要求,进而容易丢失目标的问题,提出基于动态T-S模糊控制的视觉跟随方法.利用HOG算法检测目标,并结合摄像机模型获取目标位置向量,在T-S模糊控制律的基础上进行动态化处理,进一步提高角度误差收敛的响应速度. MATLAB仿真表明:角度误差的收敛时间小于0.4 s,改进的模糊控制可以有效提高角度误差的响应速度,缩短角度误差收敛的时间,使得跟随系统具有较好的快速性和适应性.在移动机器人平台上进行跟随实验,得到的角度误差收敛时间也小于0.5 s.基于动态T-S模糊控制的移动机器人视觉跟随系统对角度误差能够快速响应并达到收敛,进而有效防止跟随目标的丢失.

Visual target tracking based on dynamic fuzzy-model control

The problem, that the angle control of the mobile robot''s visual target following system based on the traditional linear control law cannot satisfy the need of high efficiency and fastness so that the target is easy missed, is focused in this paper. A visual following method based on dynamic T-S fuzzy control is proposed. The HOG algorithm is used to detect the target and the target position vector is obtained by the camera model. Based on the T-S fuzzy control, dynamic processing is performed to further improve the response speed of angular error convergence. The simulation by MATLAB shows that the convergence time of the angle error is less than 0.4 second. Therefore, the improved fuzzy control method can effectively improve the response speed of the angle error, shorten the time of the angle error convergence, and make the follow-up system have better rapidity and adaptability. By experiment on the mobile robot platform, the convergence time of the angle error is less than 0.5 second.