Optimal consensus algorithm integrated with obstacle avoidance

This article proposes a new consensus algorithm for the networked single-integrator systems in an obstacle-laden environment. A novel optimal control approach is utilised to achieve not only multi-agent consensus but also obstacle avoidance capability with minimised control efforts. Three cost functional components are defined to fulfil the respective tasks. In particular, an innovative nonquadratic obstacle avoidance cost function is constructed from an inverse optimal control perspective. The other two components are designed to ensure consensus and constrain the control effort. The asymptotic stability and optimality are proven. In addition, the distributed and analytical optimal control law only requires local information based on the communication topology to guarantee the proposed behaviours, rather than all agents’ information. The consensus and obstacle avoidance are validated through simulations.

[1]  Dusan M. Stipanovic,et al.  Coordination and collision avoidance for Lagrangian systems with disturbances , 2010, Appl. Math. Comput..

[2]  Mehran Mesbahi,et al.  On maximizing the second smallest eigenvalue of a state-dependent graph Laplacian , 2006, IEEE Transactions on Automatic Control.

[3]  Sanjay P. Bhat,et al.  Finite-Time Semistability and Consensus for Nonlinear Dynamical Networks , 2008, IEEE Transactions on Automatic Control.

[4]  Wei Ren On Consensus Algorithms for Double-Integrator Dynamics , 2008, IEEE Trans. Autom. Control..

[5]  M StipanovićDušan,et al.  Formation Control and Collision Avoidance for Multi-agent Non-holonomic Systems , 2008 .

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

[7]  Timothy W. McLain,et al.  Coordination Variables and Consensus Building in Multiple Vehicle Systems , 2004 .

[8]  Yongcan Cao,et al.  Optimal Linear-Consensus Algorithms: An LQR Perspective , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

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

[10]  Randal W. Beard,et al.  Distributed Consensus in Multi-vehicle Cooperative Control - Theory and Applications , 2007, Communications and Control Engineering.

[11]  Dennis S. Bernstein,et al.  Nonquadratic Cost and Nonlinear Feedback Control , 1991, 1991 American Control Conference.

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

[13]  Jean-Charles Delvenne,et al.  Optimal strategies in the average consensus problem , 2007, 2007 46th IEEE Conference on Decision and Control.

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

[15]  W. Haddad,et al.  Nonlinear Dynamical Systems and Control: A Lyapunov-Based Approach , 2008 .

[16]  K. Khorasani,et al.  An LMI approach to optimal consensus seeking in multi-agent systems , 2009, 2009 American Control Conference.

[17]  Long Cheng,et al.  Decentralized Robust Adaptive Control for the Multiagent System Consensus Problem Using Neural Networks , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[18]  Long Cheng,et al.  Neural-Network-Based Adaptive Leader-Following Control for Multiagent Systems With Uncertainties , 2010, IEEE Transactions on Neural Networks.

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

[20]  Vicsek,et al.  Novel type of phase transition in a system of self-driven particles. , 1995, Physical review letters.

[21]  D.M. Stipanovic,et al.  On synchronization and collision avoidance for mechanical systems , 2008, 2008 American Control Conference.

[22]  Prabhakar R. Pagilla,et al.  Formation of a Group of Vehicles With Full Information Using Constraint Forces , 2007 .

[23]  Dusan M. Stipanovic,et al.  Formation Control and Collision Avoidance for Multi-agent Non-holonomic Systems: Theory and Experiments , 2008, Int. J. Robotics Res..

[24]  Mark W. Spong,et al.  Cooperative Avoidance Control for Multiagent Systems , 2007 .

[25]  Stephen P. Boyd,et al.  Fast linear iterations for distributed averaging , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).