On Event Triggered Tracking for Nonlinear Systems

In this technical note, we study an event-based control algorithm for trajectory tracking in nonlinear systems. The desired trajectory is modelled as the solution of a reference system with an exogenous input and it is assumed that the desired trajectory and the exogenous input to the reference system are uniformly bounded. Given a continuous-time control law that guarantees global uniform asymptotic tracking of the desired trajectory, our algorithm provides an event-based controller that not only guarantees uniform ultimate boundedness of the tracking error, but also ensures non-accumulation of inter-execution times. In the case that the derivative of the exogenous input to the reference system is also uniformly bounded, an arbitrarily small ultimate bound can be designed. If the exogenous input to the reference system is piecewise continuous and not differentiable everywhere then the achievable ultimate bound is constrained and the result is local, though with a known region of attraction. The main ideas in the technical note are illustrated through simulations of trajectory tracking by a nonlinear system.

[1]  Richard M. Murray,et al.  Information flow and cooperative control of vehicle formations , 2004, IEEE Transactions on Automatic Control.

[2]  Pavankumar Tallapragada,et al.  On event triggered trajectory tracking for control affine nonlinear systems , 2011, IEEE Conference on Decision and Control and European Control Conference.

[3]  Karl-Erik Årzén,et al.  A simple event-based PID controller , 1999 .

[4]  K. Åström,et al.  Comparison of Riemann and Lebesgue sampling for first order stochastic systems , 2002, Proceedings of the 41st IEEE Conference on Decision and Control, 2002..

[5]  K. Åström,et al.  Systems with Lebesgue sampling , 2003 .

[6]  Panos J. Antsaklis,et al.  Event-triggered real-time scheduling for stabilization of passive and output feedback passive systems , 2011, Proceedings of the 2011 American Control Conference.

[7]  Jan Lunze,et al.  A state-feedback approach to event-based control , 2010, Autom..

[8]  Victor M. Preciado,et al.  From local measurements to network spectral properties: Beyond degree distributions , 2010, 49th IEEE Conference on Decision and Control (CDC).

[9]  JH Heico Sandee,et al.  Event-driven control in theory and practice : trade-offs in software and control performance , 2006 .

[10]  Paulo Tabuada,et al.  Event-Triggered Real-Time Scheduling of Stabilizing Control Tasks , 2007, IEEE Transactions on Automatic Control.

[11]  Karl Henrik Johansson,et al.  Distributed Event-Triggered Control for Multi-Agent Systems , 2012, IEEE Transactions on Automatic Control.

[12]  Xiaofeng Wang,et al.  Decentralized Event-Triggered Broadcasts over Networked Control Systems , 2008, HSCC.

[13]  P. Olver Nonlinear Systems , 2013 .

[14]  Xiaofeng Wang,et al.  Self-Triggering Under State-Independent Disturbances , 2010, IEEE Transactions on Automatic Control.

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

[16]  Xiaofeng Wang,et al.  Self-Triggered Feedback Control Systems With Finite-Gain ${\cal L}_{2}$ Stability , 2009, IEEE Transactions on Automatic Control.

[17]  N. Abreu Old and new results on algebraic connectivity of graphs , 2007 .

[18]  Reza Olfati-Saber,et al.  Consensus and Cooperation in Networked Multi-Agent Systems , 2007, Proceedings of the IEEE.

[19]  Xiaofeng Wang,et al.  Event-Triggering in Distributed Networked Control Systems , 2011, IEEE Transactions on Automatic Control.

[20]  Manuel Mazo,et al.  Decentralized Event-Triggered Control Over Wireless Sensor/Actuator Networks , 2010, IEEE Transactions on Automatic Control.

[21]  W. P. M. H. Heemels,et al.  Analysis of event-driven controllers for linear systems , 2008, Int. J. Control.

[22]  W. P. M. H. Heemels,et al.  Output-based event-triggered control with Guaranteed ℒ∞-gain and improved event-triggering , 2010, 49th IEEE Conference on Decision and Control (CDC).

[23]  Victor M. Preciado,et al.  Low-Order Spectral Analysis of the Kirchhoff Matrix for a Probabilistic Graph With a Prescribed Expected Degree Sequence , 2008, IEEE Transactions on Circuits and Systems I: Regular Papers.

[24]  J. Lasserre Bounding the support of a measure from its marginal moments , 2010, 1011.0138.