Predictive control of multiple UGVs in a NCS with adaptive bandwidth allocation

In network based path tracking control of systems with multiple unmanned ground vehicles (UGVs), performance can be affected by network constraints including time-varying network delays and bandwidth limitations. Network delay has previously been compensated for using smith predictor based techniques and gain scheduling to limit UGV motion. The predictive gain scheduler introduced in this paper uses the predicted trajectory and future path to maximize allowable travel while considering the network delay. On the other hand, bandwidth management has been approached by optimizing total bandwidth usage under performance constraints. However, by optimizing the performance of the UGVs under bandwidth constraints, the total networked control system performance increases.

[1]  Unnati Ojha.  Delay Tolerant Behavior Control based Adaptive Bandwidth Allocation for Unmanned Ground Vehicles in a Network Control System , 2009 .

[2]  BAI Tao.  Optimal bandwidth scheduling of networked control systems ( NCSs ) in accordance with jitter * , .

[3]  G. Cook,et al.  Use of a preview control scheme with knowledge of future trajectory information for a lane tracking controller on a wheeled mobile robot , 2008, 2008 34th Annual Conference of IEEE Industrial Electronics.

[4]  Wei Zhang,et al.  Scheduling and feedback co-design for networked control systems , 2002, Proceedings of the 41st IEEE Conference on Decision and Control, 2002..

[5]  Upamanyu Madhow,et al.  Fair scheduling with tunable latency: a round robin approach , 1999, Seamless Interconnection for Universal Services. Global Telecommunications Conference. GLOBECOM'99. (Cat. No.99CH37042).

[6]  Hideki Hashimoto,et al.  Path tracking control of mobile robots using a quadratic curve , 1996, Proceedings of Conference on Intelligent Vehicles.

[7]  Behrouz A. Forouzan,et al.  Data Communications and Networking , 2000 .

[8]  Youxian Sun,et al.  Simulation based performance analysis of networked control systems with resource constraints , 2004, 30th Annual Conference of IEEE Industrial Electronics Society, 2004. IECON 2004.

[9]  Y. Tipsuwan,et al.  On the gain scheduling for networked PI controller over IP network , 2003, Proceedings 2003 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM 2003).

[10]  Saïd Mammar,et al.  A new robust control system with optimized use of the lane detection data for vehicle full lateral control under strong curvatures , 2006, 2006 IEEE Intelligent Transportation Systems Conference.

[11]  L. Nouveliere,et al.  Speed Limitation Based on an Advanced Curve Warning System , 2007, 2007 IEEE Intelligent Vehicles Symposium.

[12]  Zheng Li,et al.  Adaptive Multiple Sampling Rate Scheduling of Real-time Networked Supervisory Control System - Part II , 2006, IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics.

[13]  R. Vanijjirattikhan,et al.  Feedback preprocessed unmanned ground vehicle network-based controller characterization , 2004, 30th Annual Conference of IEEE Industrial Electronics Society, 2004. IECON 2004.

[14]  Mo-Yuen Chow,et al.  Adaptive Multiple Sampling Rate Scheduling of Real-time Networked Supervisory Control System - Part I , 2006, IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics.

[15]  Mo-Yuen Chow,et al.  Predictive constrained gain scheduling for UGV path tracking in a networked control system , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[16]  Josep M. Fuertes,et al.  LEF closed-loop scheduling policy for real-time control systems , 2005, 2005 IEEE Conference on Emerging Technologies and Factory Automation.

[17]  Hong Ye,et al.  Scheduling of networked control systems , 2001 .

[18]  Steven C. Peters,et al.  Mobile robot path tracking of aggressive maneuvers on sloped terrain , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[19]  Hideki Hashimoto,et al.  Mobile agent gain scheduler control in inter-continental intelligent space , 2004, SICE 2004 Annual Conference.

[20]  John P. Lehoczky,et al.  The rate monotonic scheduling algorithm: exact characterization and average case behavior , 1989, [1989] Proceedings. Real-Time Systems Symposium.