Adaptive Kriging controller design for hypersonic flight vehicle via back-stepping

In this study, the adaptive Kriging controller is investigated for the longitudinal dynamics of a generic hypersonic flight vehicle. For the altitude subsystem, the dynamics are transformed into the strict-feedback form where the back-stepping scheme is used. The velocity subsystem is transformed into the output-feedback form. Considering the non-linearity of the dynamics, the nominal feedback is included in the controller while Kriging system is used to estimate the uncertainty, which is described as the realisations of Gaussian random functions. To eliminate the infinite increase of the data size, the recursive Kriging algorithm is adopted in this study. Under the proposed controller, the almost surely bounded stability analysis is presented. The simulation study compared with neural back-stepping control is presented to show the effectiveness of the proposed control approach.

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

[2]  T. Tarn,et al.  Observers for nonlinear stochastic systems , 1975, 1975 IEEE Conference on Decision and Control including the 14th Symposium on Adaptive Processes.

[3]  Roland Siegwart,et al.  Composite control based on optimal torque control and adaptive Kriging control for the CRAB rover , 2011, 2011 IEEE International Conference on Robotics and Automation.

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

[5]  W. M ac,et al.  Robust Nonlinear Control of a Hypersonic Aircraft in the Presence of Aerothermoelastic Effects , 2009 .

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

[7]  Fuchun Sun,et al.  Neural network-based robust control for hypersonic flight vehicle with uncertainty modelling , 2010, Int. J. Model. Identif. Control..

[8]  T. Simpson,et al.  Use of Kriging Models to Approximate Deterministic Computer Models , 2005 .

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

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

[11]  E. Jury,et al.  ALMOST SURE BOUNDEDNESS OF RANDOMLY SAMPLED SYSTEMS , 1971 .

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

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

[14]  Kumpati S. Narendra,et al.  Nonlinear adaptive control using neural networks and multiple models , 2001, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).

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

[16]  Kazuomi Yamamoto,et al.  Efficient Optimization Design Method Using Kriging Model , 2005 .

[17]  Shuzhi Sam Ge,et al.  Output Feedback NN Control for Two Classes of Discrete-Time Systems With Unknown Control Directions in a Unified Approach , 2008, IEEE Transactions on Neural Networks.

[18]  D.B. Doman,et al.  Robust nonlinear sequential loop closure control design for an air-breathing hypersonic vehicle model , 2008, 2008 American Control Conference.

[19]  J. Chilès,et al.  Geostatistics: Modeling Spatial Uncertainty , 1999 .

[20]  Farrokh Mistree,et al.  Kriging Models for Global Approximation in Simulation-Based Multidisciplinary Design Optimization , 2001 .

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

[22]  C. Wen,et al.  Robust adaptive control of nonlinear discrete-time systems by backstepping without overparameterization , 2001, Autom..

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

[24]  Andrea Serrani,et al.  Integrated adaptive guidance and control of constrained nonlinear air-breathing hypersonic vehicle models , 2009, 2009 American Control Conference.

[25]  M. Farsi,et al.  Self-tuning control of nonlinear systems , 1994, Proceedings of 1994 American Control Conference - ACC '94.

[26]  Du Tian-rong.  Discrete-time controller design for hypersonic vehicle via back-stepping , 2009 .

[27]  Yufei Xu,et al.  Adaptive Fault-Tolerant Tracking Control of Near-Space Vehicle Using Takagi–Sugeno Fuzzy Models , 2010, IEEE Transactions on Fuzzy Systems.

[28]  Agathe Girard,et al.  Adaptive, Cautious, Predictive control with Gaussian Process Priors , 2003 .

[29]  Michael A. Bolender,et al.  Approximate Feedback Linearization of an Air-Breathing Hypersonic Vehicle (PREPRINT) , 2005 .

[30]  Fuchun Sun,et al.  Adaptive Kriging control of discrete-time nonlinear systems , 2007 .

[31]  P.V. Kokotovic,et al.  The joy of feedback: nonlinear and adaptive , 1992, IEEE Control Systems.