Finite-time multi-agent deployment: A nonlinear PDE motion planning approach

The systematic flatness-based motion planning using formal power series and suitable summability methods is considered for the finite-time deployment of multi-agent systems into planar formation profiles along predefined spatial-temporal paths. Thereby, a distributed-parameter setting is proposed, where the collective leader-follower agent dynamics is modeled by two boundary controlled nonlinear time-varying PDEs governing the motion of an agent continuum in the plane. The discretization of the PDE model directly induces a decentralized communication and interconnection structure for the multi-agent system, which is required to achieve the desired spatial-temporal paths and deployment formations.

[1]  Joseph Bentsman,et al.  PdE-based model reference adaptive control of uncertain heterogeneous multiagent networks , 2008 .

[2]  M MurrayRichard,et al.  Distributed receding horizon control for multi-vehicle formation stabilization , 2006 .

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

[4]  M. Fliess,et al.  Flatness and defect of non-linear systems: introductory theory and examples , 1995 .

[5]  William B. Dunbar,et al.  Distributed receding horizon control for multi-vehicle formation stabilization , 2006, Autom..

[6]  Roberto Horowitz,et al.  Traffic Flow Control in Automated Highway Systems , 1997 .

[7]  Pierre Rouchon,et al.  Dynamics and solutions to some control problems for water-tank systems , 2002, IEEE Trans. Autom. Control..

[8]  Thomas Meurer Feedforward and Feedback Tracking Control of Diffusion-Convection-Reaction Systems using Summability Methods , 2006 .

[9]  J. Rudolph,et al.  Flatness-based boundary control of a class of quasilinear parabolic distributed parameter systems , 2002 .

[10]  Michael Zeitz,et al.  Model inversion of boundary controlled parabolic partial differential equations using summability methods , 2008 .

[11]  L. Rodino Linear Partial Differential Operators in Gevrey Spaces , 1993 .

[12]  Michael Zeitz,et al.  Feedforward and Feedback Tracking Control of Nonlinear Diffusion-Convection-Reaction Systems Using Summability Methods , 2005 .

[13]  Miroslav Krstic,et al.  Nonlinear Stabilization of Shock-Like Unstable Equilibria in the Viscous Burgers PDE , 2008, IEEE Transactions on Automatic Control.

[14]  Werner Balser,et al.  Formal Power Series and Linear Systems of Meromorphic Ordinary Differential Equations , 1999 .

[15]  Ernst Joachim Weniger,et al.  Nonlinear sequence transformations for the acceleration of convergence and the summation of divergent series , 1989 .

[16]  William B. Dunbar,et al.  DistributedRecedingHorizonControlfor Multi-VehicleFormationStabilization ? , 2005 .

[17]  Max Donath,et al.  American Control Conference , 1993 .

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

[19]  R. Beard,et al.  Formation feedback control for multiple spacecraft via virtual structures , 2004 .

[20]  Tucker R. Balch,et al.  Behavior-based formation control for multirobot teams , 1998, IEEE Trans. Robotics Autom..

[21]  Andreas Kugi,et al.  Trajectory Planning for Boundary Controlled Parabolic PDEs With Varying Parameters on Higher-Dimensional Spatial Domains , 2009, IEEE Transactions on Automatic Control.

[22]  Giancarlo Ferrari-Trecate,et al.  Analysis of coordination in multi-agent systems through partial difference equations , 2006, IEEE Transactions on Automatic Control.

[23]  Richard M. Murray,et al.  Recent Research in Cooperative Control of Multivehicle Systems , 2007 .

[24]  Miroslav Krstic,et al.  Nonlinear Control of the Viscous Burgers Equation: Trajectory Generation, Tracking, and Observer Design , 2009 .

[25]  W. Balser Summability of Formal Power Series of Ordinary and Partial Differential Equations , 2004 .

[26]  Jorge Cortes,et al.  Distributed Control of Robotic Networks: A Mathematical Approach to Motion Coordination Algorithms , 2009 .

[27]  João Pedro Hespanha,et al.  Mistuning-Based Control Design to Improve Closed-Loop Stability Margin of Vehicular Platoons , 2008, IEEE Transactions on Automatic Control.

[28]  Jianghai Hu,et al.  Optimal Multi-Agent Coordination Under Tree Formation Constraints , 2008, IEEE Transactions on Automatic Control.

[29]  Andreas Kugi,et al.  TRACKING CONTROL FOR A DIFFUSION–CONVECTION–REACTION SYSTEM: COMBINING FLATNESS AND BACKSTEPPING , 2007 .

[30]  Maurice Gevrey,et al.  Sur la nature analytique des solutions des équations aux dérivées partielles. Premier mémoire , 1918 .

[31]  Alain Sarlette,et al.  A PDE viewpoint on basic properties of coordination algorithms with symmetries , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

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

[33]  Miroslav Krstic,et al.  Backstepping boundary control for first order hyperbolic PDEs and application to systems with actuator and sensor delays , 2007, 2007 46th IEEE Conference on Decision and Control.

[34]  Werner Balser,et al.  Power Series Methods and Multisummability , 2000 .

[35]  Miroslav Krstic,et al.  Rapidly convergent leader-enabled multi-agent deployment into planar curves , 2009, 2009 American Control Conference.

[36]  M. Krstić Boundary Control of PDEs: A Course on Backstepping Designs , 2008 .