Flocking with obstacle avoidance based on fuzzy logic

In this study, flocking with obstacle avoidance control algorithm for multi-agent dynamical network is studied. Fuzzy logic is used to design the attractive/repulsive function. Cooperative control algorithm is proposed for a group of autonomous agents to achieve flocking formations following a virtual agent and avoiding obstacles. The control law consists of three terms. The first term is designed using fuzzy logic for collision avoidance and velocity consensus; The second one is also designed using fuzzy logic for obstacle avoidance; The third one is for tracking purposes. Smooth graph Laplacian and Smooth attractive/repulsive potential designed using fuzzy logic are used to overcome the difficulties in stability analysis. The theoretical result is presented to indicate the achievement of flocking motion (cohesiveness, collision avoidance and velocity matching). Finally, simulation examples are given to validate the theoretical analysis.

[1]  George J. Pappas,et al.  Stable flocking of mobile agents, part I: fixed topology , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[2]  Richard M. Murray,et al.  Consensus problems in networks of agents with switching topology and time-delays , 2004, IEEE Transactions on Automatic Control.

[3]  Marios M. Polycarpou,et al.  Stability analysis of M-dimensional asynchronous swarms with a fixed communication topology , 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).

[4]  George J. Pappas,et al.  Stable flocking of mobile agents part I: dynamic topology , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[5]  Randal W. Beard,et al.  Consensus seeking in multiagent systems under dynamically changing interaction topologies , 2005, IEEE Transactions on Automatic Control.

[6]  Yang Liu,et al.  Stability analysis of one-dimensional asynchronous swarms , 2003, IEEE Trans. Autom. Control..

[7]  Dongbing Gu,et al.  Using Fuzzy Logic to Design Separation Function in Flocking Algorithms , 2008, IEEE Transactions on Fuzzy Systems.

[8]  Jie Lin,et al.  Coordination of groups of mobile autonomous agents using nearest neighbor rules , 2003, IEEE Trans. Autom. Control..

[9]  Kevin M. Passino,et al.  Stability analysis of swarms , 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).

[10]  Luc Moreau,et al.  Stability of multiagent systems with time-dependent communication links , 2005, IEEE Transactions on Automatic Control.

[11]  Reza Olfati-Saber,et al.  Flocking for multi-agent dynamic systems: algorithms and theory , 2006, IEEE Transactions on Automatic Control.

[12]  Gordon F. Royle,et al.  Algebraic Graph Theory , 2001, Graduate texts in mathematics.

[13]  Craig W. Reynolds Flocks, herds, and schools: a distributed behavioral model , 1987, SIGGRAPH.