模型预测控制下多移动机器人的跟踪与避障

提出了一种基于距离和速度的机器人之间的避障方法，通过与机器人避开障碍物的人工势场法相结合，建立一致性控制编队控制协议。首先，建立机器人之间的通信拓扑关系，以便机器人之间的信息交流。在编队控制层面上，设计具有避碰的编队控制律。然后，在编队跟踪层面上，运用模型预测控制方法，将编队误差运动问题按代价函数转化为最小优化问题。为了在线高效地求解该优化问题，运用了一种广义投影神经网络优化的方法，以便最优解作为控制输入。最后，对多移动机器人编队进行了仿真，验证了所提出策略的有效性。

Tracking and Obstacle Avoidance of Multi-mobile Robots Under Model Predictive Control

Aiming to control the formation tracking and obstacle avoidance system of multi-mobile robots under the changing topology, an obstacle avoidance method based on distance and speed between robots and an artificial potential field method to avoid obstacles are proposed to establish a consistent control formation control protocol. Firstly, the communication topology between robots is established to facilitate the information exchange between robots. At the level of formation control, a formation control law with collision avoidance is designed. Then, at the level of formation tracking, the formation error motion problem is transformed into a minimum optimization problem according to the cost function by using model predictive control method. In order to efficiently solve the optimization problem online, a generalized projection neural network optimization method is used, in which the optimal solution is used as the control input. Finally, the simulation of multi-mobile robot formation verifies the effectiveness of the proposed strategy.