Control of nonlinear systems with symmetries using chaos

We present a method that exploits chaos for the control of systems composed of subsystems with identical nonlinear dynamics and a shared, common control input. Due to symmetry, these systems are uncontrollable in a deterministic sense. However, the systems may be controllable in a stochastic sense when they are driven by process noise. We present a control strategy that exploits the sensitivity of chaotic motion to process noise. The chaotic subsystem trajectories evolve independently on the strange attractor, which enlarges the reachable set of the system. Specifically, we consider the control of a juggling machine bouncing multiple balls on a single, actuated paddle. The goal is to control the balls to a combination of stable periodic orbits. First, a paddle motion is applied that induces chaotic ball trajectories. Then, when the ball states reach the basins of attraction of the desired periodic orbits, the paddle motion is switched to the motion that stabilizes the orbits. Both simulation and preliminary experimental results are presented.

[1]  Philippe Lefèvre,et al.  Rhythmic Feedback Control of a Blind Planar Juggler , 2007, IEEE Transactions on Robotics.

[2]  T. Vincent Control using chaos , 1997 .

[3]  Remco I. Leine,et al.  Global uniform symptotic attractive stability of the non-autonomous bouncing ball system , 2012 .

[4]  Emanuel Todorov,et al.  First-exit model predictive control of fast discontinuous dynamics: Application to ball bouncing , 2011, 2011 IEEE International Conference on Robotics and Automation.

[5]  Edward Ott,et al.  Controlling chaos , 2006, Scholarpedia.

[6]  Jerzy Zabczyk,et al.  Controllability of stochastic linear systems , 1981 .

[7]  P. J. Holmes The dynamics of repeated impacts with a sinusoidally vibrating table , 1982 .

[8]  Paul Umbanhowar,et al.  Toward the set of frictional velocity fields generable by 6-degree-of-freedom oscillatory motion of a rigid plate , 2010, 2010 IEEE International Conference on Robotics and Automation.

[9]  Pablo A. Parrilo,et al.  Semidefinite programming relaxations for semialgebraic problems , 2003, Math. Program..

[10]  Celso Grebogi,et al.  Using small perturbations to control chaos , 1993, Nature.

[11]  Yoshifumi Sunahara,et al.  On stochastic controllability for nonlinear systems , 1974 .

[12]  Daniel E. Koditschek,et al.  Global asymptotic stability of a passive juggler: a parts feeding strategy , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.

[13]  Daniel E. Koditschek,et al.  Sequential Composition of Dynamically Dexterous Robot Behaviors , 1999, Int. J. Robotics Res..

[14]  John Baillieul Self-organizing behavior in a simple controlled dynamical system , 1992 .

[15]  Dominic R. Frutiger,et al.  Small, Fast, and Under Control: Wireless Resonant Magnetic Micro-agents , 2010, Int. J. Robotics Res..

[16]  Ying-Cheng Lai,et al.  Controlling chaos , 1994 .

[17]  Raffaello D'Andrea,et al.  Design and Analysis of a Blind Juggling Robot , 2012, IEEE Transactions on Robotics.