Composite dynamic surface control of hypersonic flight dynamics using neural networks

This paper addresses the composite neural tracking control for the longitudinal dynamics of hypersonicflight dynamics. The dynamics is decoupled into velocity subsystem, altitude subsystem, and attitudesubsystem. For the altitude subsystem, the reference command of flight path angle is derived for the attitudesubsystem. To deal with the system uncertainty and provide efficient neural learning, the composite law forneural weights updating is studied with both tracking error and modeling error. The uniformly ultimate boundednessstability is guaranteed via Lyapunov approach. Under the dynamic surface control with novel neuraldesign, the neural system converges in a faster mode and better tracking performance is obtained. Simulationresults are presented to show the effectiveness of the design.

[1]  Cui Ya-Long,et al.  Control-oriented modeling and characteristic analysis of an airbreathing hypersonic vehicle , 2014, Proceedings of 2014 IEEE Chinese Guidance, Navigation and Control Conference.

[2]  Bin Xu,et al.  Reinforcement Learning Output Feedback NN Control Using Deterministic Learning Technique , 2017 .

[3]  David K. Schmidt.  Optimum Mission Performance and Multivariable Flight Guidance for Airbreathing Launch Vehicles , 1997 .

[4]  David B. Doman,et al.  Control-Oriented Modeling of an Air-Breathing Hypersonic Vehicle , 2007 .

[5]  Danwei W. Wang,et al.  Dynamic Surface Control of Constrained Hypersonic Flight Models with Parameter Estimation and Actuator Compensation , 2014 .

[6]  Anuradha M. Annaswamy,et al.  Adaptive control of hypersonic vehicles in the presence of modeling uncertainties , 2009, 2009 American Control Conference.

[7]  DaoXiang Gao,et al.  Dynamic Surface Control for Hypersonic Aircraft Using Fuzzy Logic System , 2007, 2007 IEEE International Conference on Automation and Logistics.

[8]  Zhongke Shi,et al.  An overview on flight dynamics and control approaches for hypersonic vehicles , 2015, Science China Information Sciences.

[9]  Zhongke Shi,et al.  Composite Neural Dynamic Surface Control of a Class of Uncertain Nonlinear Systems in Strict-Feedback Form , 2014, IEEE Transactions on Cybernetics.

[10]  Robert F. Stengel,et al.  Robust Nonlinear Control of a Hypersonic Aircraft , 1999 .

[11]  Marios M. Polycarpou,et al.  Backstepping-Based Flight Control with Adaptive Function Approximation , 2005 .

[12]  Bin Xu,et al.  Robust adaptive neural control of flexible hypersonic flight vehicle with dead-zone input nonlinearity , 2015 .

[13]  Kumpati S. Narendra,et al.  Identification and control of dynamical systems using neural networks , 1990, IEEE Trans. Neural Networks.

[14]  David K. Schmidt,et al.  Analytical aeropropulsive-aeroelastic hypersonic-vehicle model with dynamic analysis , 1994 .

[15]  Zengqi Sun,et al.  Fuzzy tracking control design for hypersonic vehicles via T-S model , 2011, Science China Information Sciences.

[16]  Shixing Wang,et al.  Adaptive neural control based on HGO for hypersonic flight vehicles , 2011, Science China Information Sciences.

[17]  Li-Xin Wang.  Design and analysis of fuzzy identifiers of nonlinear dynamic systems , 1995, IEEE Trans. Autom. Control..

[18]  Shuzhi Sam Ge,et al.  Robust Adaptive Neural Network Control for a Class of Uncertain MIMO Nonlinear Systems With Input Nonlinearities , 2010, IEEE Transactions on Neural Networks.

[19]  Petros A. Ioannou,et al.  Adaptive Sliding Mode Control Design fo ra Hypersonic Flight Vehicle , 2004 .

[20]  Zhongke Shi,et al.  Reinforcement Learning Output Feedback NN Control Using Deterministic Learning Technique , 2014, IEEE Transactions on Neural Networks and Learning Systems.

[21]  Youdan Kim,et al.  Nonlinear Adaptive Flight Control Using Backstepping and Neural Networks Controller , 2001 .

[22]  Qun Zong,et al.  Output feedback back-stepping control for a generic Hypersonic Vehicle via small-gain theorem , 2012 .

[23]  Wei Xing Zheng,et al.  Composite predictive flight control for airbreathing hypersonic vehicles , 2014, Int. J. Control.

[24]  Tao Zhang,et al.  Stable Adaptive Neural Network Control , 2001, The Springer International Series on Asian Studies in Computer and Information Science.

[25]  Eugene Lavretsky,et al.  Adaptive Control and the NASA X-15-3 Flight Revisited , 2010, IEEE Control Systems.

[26]  Lei Guo,et al.  Nonlinear-Disturbance-Observer-Based Robust Flight Control for Airbreathing Hypersonic Vehicles , 2013, IEEE Transactions on Aerospace and Electronic Systems.

[27]  Xu Bin,et al.  Adaptive neural control based on HGO for hypersonic flight vehicles , 2011 .

[28]  Fuchun Sun,et al.  Adaptive discrete-time controller design with neural network for hypersonic flight vehicle via back-stepping , 2011, Int. J. Control.

[29]  A. Serrani,et al.  Nonlinear Robust Adaptive Control of Flexible Air-Breathing Hypersonic Vehicles , 2009 .