Improved Sliding Mode Control for Finite-Time Synchronization of Nonidentical Delayed Recurrent Neural Networks

This brief further explores the problem of finite-time synchronization of delayed recurrent neural networks with the mismatched parameters and neuron activation functions. An improved sliding mode control approach is presented for addressing the finite-time synchronization problem. First, by employing the drive-response concept and the synchronization error of drive-response systems, a novel integral sliding mode surface is constructed such that the synchronization error can converge to zero in finite time along the constructed integral sliding mode surface. Second, a suitable sliding mode controller is designed by relying on Lyapunov stability theory such that all system state trajectories can be driven onto the predefined sliding mode surface in finite time. Moreover, it is found that the presented control approach can be conveniently verified and does not need to solve any linear matrix inequality (LMI) to guarantee the finite-time synchronization of delayed recurrent neural networks. Finally, three numerical examples are exploited to demonstrate the effectiveness of the presented control approach.

[1]  Wei Xing Zheng,et al.  Impulsive Synchronization of Reaction–Diffusion Neural Networks With Mixed Delays and Its Application to Image Encryption , 2016, IEEE Transactions on Neural Networks and Learning Systems.

[2]  José de Jesús Rubio,et al.  Discrete time control based in neural networks for pendulums , 2017, Appl. Soft Comput..

[3]  Jinde Cao,et al.  Finite-time synchronization of uncertain coupled switched neural networks under asynchronous switching , 2017, Neural Networks.

[4]  Yugang Niu,et al.  Finite-time sliding mode control synthesis under explicit output constraint , 2016, Autom..

[5]  Guobao Zhang,et al.  Improved Stability Criterion for Recurrent Neural Networks With Time-Varying Delays , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[6]  Shuai Li,et al.  Kinematic Control of Redundant Manipulators Using Neural Networks , 2017, IEEE Transactions on Neural Networks and Learning Systems.

[7]  Changyin Sun,et al.  Neural Network Control of a Two-Link Flexible Robotic Manipulator Using Assumed Mode Method , 2019, IEEE Transactions on Industrial Informatics.

[8]  Huaguang Zhang,et al.  Stability Analysis of Neural Networks With Two Delay Components Based on Dynamic Delay Interval Method , 2017, IEEE Transactions on Neural Networks and Learning Systems.

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

[10]  Jinde Cao,et al.  Exponential Synchronization of Memristive Neural Networks With Delays: Interval Matrix Method , 2017, IEEE Transactions on Neural Networks and Learning Systems.

[11]  Jinde Cao,et al.  Synchronization of fractional-order complex-valued neural networks with time delay , 2016, Neural Networks.

[12]  Zongxuan Sun,et al.  Design and Implementation of Clutch Control for Automotive Transmissions Using Terminal-Sliding-Mode Control and Uncertainty Observer , 2016, IEEE Transactions on Vehicular Technology.

[13]  Louis M Pecora,et al.  Synchronization of chaotic systems. , 2015, Chaos.

[14]  Rui Xu,et al.  Synchronization of non-identical chaotic delayed fuzzy cellular neural networks based on sliding mode control☆ , 2012 .

[15]  Huaguang Zhang,et al.  Stability Criteria for Recurrent Neural Networks With Time-Varying Delay Based on Secondary Delay Partitioning Method , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[16]  Chuandong Li,et al.  Complete synchronization of delayed chaotic neural networks by intermittent control with two switches in a control period , 2016, Neurocomputing.

[17]  Jing-Jing Xiong,et al.  Global fast dynamic terminal sliding mode control for a quadrotor UAV. , 2017, ISA transactions.

[18]  Gang Feng,et al.  Synchronization of nonidentical chaotic neural networks with time delays , 2009, Neural Networks.

[19]  Carlos Aguilar-Ibanez,et al.  Stabilization of the PVTOL aircraft based on a sliding mode and a saturation function , 2017 .

[20]  Xinghuo Yu,et al.  Design and Implementation of Terminal Sliding Mode Control Method for PMSM Speed Regulation System , 2013, IEEE Transactions on Industrial Informatics.

[21]  Jinde Cao,et al.  Exponential Synchronization of Delayed Neural Networks With Discontinuous Activations , 2013, IEEE Transactions on Circuits and Systems I: Regular Papers.

[22]  R. Rakkiyappan,et al.  Impulsive controller design for exponential synchronization of chaotic neural networks with mixed delays , 2013, Commun. Nonlinear Sci. Numer. Simul..

[23]  Huaguang Zhang,et al.  Robust Global Exponential Synchronization of Uncertain Chaotic Delayed Neural Networks via Dual-Stage Impulsive Control , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[24]  Meiqin Liu,et al.  Optimal exponential synchronization of general chaotic delayed neural networks: An LMI approach , 2009, Neural Networks.

[25]  Zhihong Man,et al.  Non-singular terminal sliding mode control of rigid manipulators , 2002, Autom..

[26]  Huaguang Zhang,et al.  Stability of Recurrent Neural Networks With Time-Varying Delay via Flexible Terminal Method , 2017, IEEE Transactions on Neural Networks and Learning Systems.

[27]  En-Hui Zheng,et al.  Position and attitude tracking control for a quadrotor UAV. , 2014, ISA transactions.

[28]  Lihong Huang,et al.  Finite-time synchronization of master-slave neural networks with time-delays and discontinuous activations , 2017 .

[29]  Zhigang Zeng,et al.  New results on anti-synchronization of switched neural networks with time-varying delays and lag signals , 2016, Neural Networks.

[30]  Jinde Cao,et al.  Synchronization of Neural Networks With Control Packet Loss and Time-Varying Delay via Stochastic Sampled-Data Controller , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[31]  Quan Yin,et al.  Adaptive Synchronization of Memristor-Based Neural Networks with Time-Varying Delays , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[32]  Yong He,et al.  Stability analysis of neural networks with time-varying delay: Enhanced stability criteria and conservatism comparisons , 2018, Commun. Nonlinear Sci. Numer. Simul..

[33]  Jinde Cao,et al.  Lag Synchronization of Memristor-Based Coupled Neural Networks via $\omega $ -Measure , 2016, IEEE Transactions on Neural Networks and Learning Systems.

[34]  Yong He,et al.  Global exponential stability of neural networks with time-varying delay based on free-matrix-based integral inequality , 2016, Neural Networks.

[35]  Qing-Long Han,et al.  Network-Based Synchronization of Delayed Neural Networks , 2013, IEEE Transactions on Circuits and Systems I: Regular Papers.

[36]  José de Jesús Rubio,et al.  Robust feedback linearization for nonlinear processes control. , 2018, ISA transactions.

[37]  Kelin Li,et al.  Synchronization of Chaotic Delayed Neural Networks via Impulsive Control , 2014, J. Appl. Math..

[38]  Huaguang Zhang,et al.  Mode-Dependent Stochastic Synchronization for Markovian Coupled Neural Networks With Time-Varying Mode-Delays , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[39]  Min Wu,et al.  Delay-dependent stability analysis of neural networks with time-varying delay: A generalized free-weighting-matrix approach , 2017, Appl. Math. Comput..

[40]  Shuai Li,et al.  Distributed Recurrent Neural Networks for Cooperative Control of Manipulators: A Game-Theoretic Perspective , 2017, IEEE Transactions on Neural Networks and Learning Systems.

[41]  Changyin Sun,et al.  Neural Network Control of a Flexible Robotic Manipulator Using the Lumped Spring-Mass Model , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[42]  Changyin Sun,et al.  Adaptive Neural Network Control of a Flapping Wing Micro Aerial Vehicle With Disturbance Observer , 2017, IEEE Transactions on Cybernetics.

[43]  Jun Wang,et al.  Global Exponential Synchronization of Two Memristor-Based Recurrent Neural Networks With Time Delays via Static or Dynamic Coupling , 2015, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[44]  Ke Qin,et al.  Projective synchronization of different chaotic neural networks with mixed time delays based on an integral sliding mode controller , 2014, Neurocomputing.

[45]  Ju H. Park,et al.  Stability and dissipativity analysis of static neural networks with interval time-varying delay , 2015, J. Frankl. Inst..

[46]  Q. Gan Synchronisation of chaotic neural networks with unknown parameters and random time-varying delays based on adaptive sampled-data control and parameter identification , 2012 .

[47]  Shiji Song,et al.  Research on synchronization of chaotic delayed neural networks with stochastic perturbation using impulsive control method , 2014, Commun. Nonlinear Sci. Numer. Simul..

[48]  Yuehua Huang,et al.  Uniformly Observable and Globally Lipschitzian Nonlinear Systems Admit Global Finite-Time Observers , 2009, IEEE Transactions on Automatic Control.

[49]  MengChu Zhou,et al.  Distributed Winner-Take-All in Dynamic Networks , 2017, IEEE Transactions on Automatic Control.

[50]  Guobao Zhang,et al.  Finite-time synchronization of delayed neural networks , 2017, 2017 Chinese Automation Congress (CAC).

[51]  Lihong Huang,et al.  Improved switching controllers for finite-time synchronization of delayed neural networks with discontinuous activations , 2017, J. Frankl. Inst..

[52]  Haijun Jiang,et al.  New results on exponential synchronization of memristor-based neural networks with discontinuous neuron activations , 2016, Neural Networks.

[53]  Guodong Zhang,et al.  Exponential synchronization of delayed memristor-based chaotic neural networks via periodically intermittent control , 2014, Neural Networks.

[54]  Jinde Cao,et al.  Exponential Synchronization of Coupled Stochastic Memristor-Based Neural Networks With Time-Varying Probabilistic Delay Coupling and Impulsive Delay , 2016, IEEE Transactions on Neural Networks and Learning Systems.

[55]  Xinghuo Yu,et al.  Discrete-Time Terminal Sliding Mode Control Systems Based on Euler's Discretization , 2014, IEEE Transactions on Automatic Control.

[56]  Jian Xu,et al.  Projective synchronization of different chaotic time-delayed neural networks based on integral sliding mode controller , 2010, Appl. Math. Comput..

[57]  Shihua Li,et al.  Prescribed-Time Second-Order Sliding Mode Controller Design Subject to Mismatched Term , 2017, IEEE Transactions on Circuits and Systems II: Express Briefs.

[58]  Shuai Li,et al.  A Novel Recurrent Neural Network for Manipulator Control With Improved Noise Tolerance , 2018, IEEE Transactions on Neural Networks and Learning Systems.