Adaptive distributed BLS-FONTSM formation control for uncertain networking heterogeneous omnidirectional mobile multirobots

ABSTRACT In this paper, an adaptive distributed fractional-order nonsingular terminal sliding-mode (FONTSM) control method using broad learning system (BLS), is proposed for cooperative formation control of networking heterogeneous omnidirectional mobile multi-robots (HOMRs) with dynamic effects and uncertainties. The dynamic behavior of each uncertain HOMR is modeled by a reduced three-input-three-output second-order state equation with uncertainties, and the multi-robot system is modeled by directed graph theory. By using the Lyapunov-based sliding-mode theory and online learning of the system uncertainties via BLS, an adaptive-distributed BLS-FONTSM formation control approach is presented to carry out asymptotical formation control in the presence of uncertainties. The effectiveness and superiority of the proposed method are well exemplified by conducting three simulations. Experimental results are provided for illustration of the applicability of the proposed control method.

[1]  Ching-Chih Tsai,et al.  Intelligent sliding-mode formation control for uncertain networked heterogeneous Mecanum-wheeled omnidirectional platforms , 2016, 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[2]  K. B. Oldham,et al.  The Fractional Calculus: Theory and Applications of Differentiation and Integration to Arbitrary Order , 1974 .

[3]  P. Olver Nonlinear Systems , 2013 .

[4]  C. L. Chen,et al.  Sliding mode leader-following consensus controllers for second-order non-linear multi-agent systems , 2015 .

[5]  Ching-Chih Tsai,et al.  Intelligent adaptive distributed consensus formation control for uncertain networked heterogeneous swedish-wheeled omnidirectional multi-robots , 2016, 2016 55th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE).

[7]  Mircea Dulău,et al.  Fractional Order Controllers Versus Integer Order Controllers , 2017 .

[8]  Ching-Chih Tsai,et al.  Adaptive nonsingular terminal sliding-mode formation control using ORFWNN for uncertain networked heterogeneous mecanum-wheeled omnidirectional robots , 2017, 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[9]  Syuan-Yi Chen,et al.  Digital signal processor based intelligent fractional-order sliding-mode control for a linear voice coil actuator , 2017 .

[10]  C. L. Philip Chen,et al.  Fuzzy Observed-Based Adaptive Consensus Tracking Control for Second-Order Multiagent Systems With Heterogeneous Nonlinear Dynamics , 2016, IEEE Transactions on Fuzzy Systems.

[11]  Dejan J. Sobajic,et al.  Learning and generalization characteristics of the random vector Functional-link net , 1994, Neurocomputing.

[12]  Lynne E. Parker,et al.  Distributed Intelligence: Overview of the Field and Its Application in Multi-Robot Systems , 2008, AAAI Fall Symposium: Regarding the Intelligence in Distributed Intelligent Systems.

[13]  Wei Ren,et al.  Information consensus in multivehicle cooperative control , 2007, IEEE Control Systems.

[14]  Ching-Chih Tsai,et al.  Cooperative Localization Using Fuzzy Decentralized Extended Information Filtering for Homogenous Omnidirectional Mobile Multi-robot System , 2015, ICSSE.

[15]  Hong Ren Wu,et al.  A robust MIMO terminal sliding mode control scheme for rigid robotic manipulators , 1994, IEEE Trans. Autom. Control..

[16]  Ching-Chih Tsai,et al.  Distributed Consensus Formation Control with Collision and Obstacle Avoidance for Uncertain Networked Omnidirectional Multi-robot Systems Using Fuzzy Wavelet Neural Networks , 2017, Int. J. Fuzzy Syst..

[17]  J. A. Tenreiro Machado,et al.  Chaotic Phenomena and Fractional-Order Dynamics in the Trajectory Control of Redundant Manipulators , 2002 .

[18]  Yeong-Hwa Chang,et al.  Fuzzy Sliding-Mode Formation Control for Multirobot Systems: Design and Implementation , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[19]  Saleh Mobayen,et al.  Finite-time tracking control of chained-form nonholonomic systems with external disturbances based on recursive terminal sliding mode method , 2015 .

[20]  Taous-Meriem Laleg-Kirati,et al.  Fractional-order adaptive fault estimation for a class of nonlinear fractional-order systems , 2015, 2015 American Control Conference (ACC).

[21]  C. L. Philip Chen,et al.  Broad Learning System: An Effective and Efficient Incremental Learning System Without the Need for Deep Architecture , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[22]  Fairouz Tchier,et al.  Design of an adaptive chattering avoidance global sliding mode tracker for uncertain non-linear time-varying systems , 2017 .

[23]  C. L. Philip Chen,et al.  Universal Approximation Capability of Broad Learning System and Its Structural Variations , 2019, IEEE Transactions on Neural Networks and Learning Systems.

[24]  Mohammad Saleh Tavazoei,et al.  Chaos control via a simple fractional-order controller , 2008 .

[25]  Abhijit Das,et al.  Cooperative Control of Multi-Agent Systems , 2014 .

[26]  Shihua Li,et al.  Finite-time tracking control of multiple nonholonomic mobile robots , 2012, J. Frankl. Inst..

[27]  Wei Zhang,et al.  Sliding mode control for chaotic systems based on LMI , 2009 .

[28]  Sara Dadras,et al.  Fractional‐Order Dynamic Output Feedback Sliding Mode Control Design for Robust Stabilization of Uncertain Fractional‐Order Nonlinear Systems , 2014 .

[29]  Ziyang Meng,et al.  Leaderless and Leader-Following Consensus With Communication and Input Delays Under a Directed Network Topology , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[30]  Yaoyao Wang,et al.  Practical Tracking Control of Robot Manipulators With Continuous Fractional-Order Nonsingular Terminal Sliding Mode , 2016, IEEE Transactions on Industrial Electronics.

[31]  Xikui Ma,et al.  Synchronization of chaotic systems with parametric uncertainty using active sliding mode control , 2004 .

[32]  Guo Jianguo,et al.  Integral terminal sliding mode control for nonlinear systems , 2018 .

[33]  S LiTzuu-Hseng,et al.  MIMO adaptive fuzzy terminal sliding-mode controller for robotic manipulators , 2010 .