Terminal sliding mode formation control of uncertain multiple robots

The formation control problem of multiple non-holonomic two-wheeled robots is considered in this paper. Since the terminal sliding mode (TSM) control approach can eliminate the reaching phase, such an approach is characterised as a novel option to cope with the mismatched uncertainties rooted in the robots. Taking the uncertain factors into accounts, such as parameter fluctuations in practice, skidding as well as slipping triggered by hostile environment, a complete dynamic model is established primarily. Combined with the leader-follower-based formation mechanism, a TSM controller is developed to guarantee the system stability in the sliding-mode stage according to the Lyapunov direct method. A sufficient condition is also proven to make the stable tracking errors converge to zero in finite time. To verify the validity and robustness of the presented TSM controller, a simulation platform composed of three robots in the presence of mismatched uncertainties is built up. The simulation results by the platform illustrate the TSM controller can form up and maintain the multi-robot system in a predefined trajectory while resisting the mismatched uncertainties.

[1]  Nathan van de Wouw,et al.  A virtual structure approach to formation control of unicycle mobile robots using mutual coupling , 2011, Int. J. Control.

[2]  Yanyan Dai,et al.  The leader-follower formation control of nonholonomic mobile robots , 2012 .

[3]  Xiangjie Liu,et al.  Neural sliding-mode load frequency controller design of power systems , 2011, Neural Computing and Applications.

[4]  Patric Jensfelt,et al.  Distributed control of triangular formations with angle-only constraints , 2010, Syst. Control. Lett..

[5]  Dimos V. Dimarogonas,et al.  Connectedness Preserving Distributed Swarm Aggregation for Multiple Kinematic Robots , 2008, IEEE Transactions on Robotics.

[6]  Farbod Fahimi,et al.  Sliding-Mode Formation Control for Underactuated Surface Vessels , 2007, IEEE Transactions on Robotics.

[7]  Gang Feng,et al.  A Synchronization Approach to Trajectory Tracking of Multiple Mobile Robots While Maintaining Time-Varying Formations , 2009, IEEE Transactions on Robotics.

[8]  Mingcong Deng,et al.  Robust Control for Nonlinear Systems Using Passivity-Based Robust Right Coprime Factorization , 2012, IEEE Transactions on Automatic Control.

[9]  George York,et al.  Cooperative Control of UAVs for Localization of Intermittently Emitting Mobile Targets , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[10]  Kimon P. Valavanis,et al.  Swarm Formation Control Utilizing Elliptical Surfaces and Limiting Functions , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[11]  Vadim I. Utkin,et al.  Sliding Modes in Control and Optimization , 1992, Communications and Control Engineering Series.

[12]  Dongkyoung Chwa,et al.  Tracking Control of Differential-Drive Wheeled Mobile Robots Using a Backstepping-Like Feedback Linearization , 2010, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[13]  Domenico Prattichizzo,et al.  Discussion of paper by , 2003 .

[14]  Xiangjie Liu,et al.  Adaptive hierarchical sliding mode control for ball-beam systems , 2012 .

[15]  Shuhui Bi,et al.  Robust Stability and Tracking for Operator-Based Nonlinear Uncertain Systems , 2015, IEEE Transactions on Automation Science and Engineering.

[16]  Plamen Petrov A Mathematical Model for Control of an Autonomous Vehicle Convoy , 2008 .

[17]  Hung-Wei Lin,et al.  Type-2 Fuzzy Formation Control for Collision-Free Multi-Robot Systems , 2013 .

[18]  Fumio Miyazaki,et al.  A stable tracking control method for an autonomous mobile robot , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[19]  Karsten Berns,et al.  Development of complex robotic systems using the behavior-based control architecture iB2C , 2010, Robotics Auton. Syst..

[20]  Naira Hovakimyan,et al.  Vision-based target tracking and motion estimation using a small UAV , 2010, 49th IEEE Conference on Decision and Control (CDC).

[21]  Michael Defoort,et al.  Sliding-Mode Formation Control for Cooperative Autonomous Mobile Robots , 2008, IEEE Transactions on Industrial Electronics.

[22]  Mohammad Biglarbegian,et al.  A Novel Robust Leader-Following Control Design for Mobile Robots , 2013, J. Intell. Robotic Syst..

[23]  Gianluca Antonelli,et al.  Experiments of Formation Control With Multirobot Systems Using the Null-Space-Based Behavioral Control , 2009, IEEE Transactions on Control Systems Technology.

[24]  Weizhong Zhang,et al.  An Autonomous Mobile Robotics Testbed: Construction, Validation, and Experiments , 2010, IEEE Transactions on Control Systems Technology.

[25]  Chien Chern Cheah,et al.  Can a Simple Control Scheme Work for a Formation Control of Multiple Autonomous Underwater Vehicles? , 2011, IEEE Transactions on Control Systems Technology.

[26]  Xinghuo Yu,et al.  Hybrid Terminal Sliding-Mode Observer Design Method for a Permanent-Magnet Synchronous Motor Control System , 2009, IEEE Transactions on Industrial Electronics.

[27]  Wenjie Dong,et al.  Flocking of Multiple Mobile Robots Based on Backstepping , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[28]  Jianqiang Yi,et al.  Control of a class of under-actuated systems with saturation using hierarchical sliding mode , 2008, 2008 IEEE International Conference on Robotics and Automation.

[29]  S. Jagannathan,et al.  Neural Network-Based Optimal Control of Mobile Robot Formations With Reduced Information Exchange , 2013, IEEE Transactions on Control Systems Technology.

[30]  Sergiu-Dan Stan,et al.  A Novel Robust Decentralized Adaptive Fuzzy Control for Swarm Formation of Multiagent Systems , 2012, IEEE Transactions on Industrial Electronics.

[31]  Timothy W. McLain,et al.  Cooperative forest fire surveillance using a team of small unmanned air vehicles , 2006, Int. J. Syst. Sci..