Limited authority adaptive flight control for reusable launch vehicles

In the application of adaptive e ight control, signie cant issues arise due to limitations in the plant inputs, such as actuator displacement limits, actuator rate limits, linear input dynamics, and time delay. A method is introduced that allows an adaptive law to be designed for the system without theseinput characteristicsand then to be applied to the system with these characteristics, without affecting adaptation. This includes allowing correct adaptation while the plant input is saturated and allows the adaptation law to function when not actually in control of the plant. To apply the method, estimates of actuator positions must be found. However, the adaptation law can correct for errors in these estimates. Proof of boundedness of system signals is provided for a single hidden-layer perceptron neural network adaptive law. Simulation results utilizing the methods introduced for neural network adaptive control of a reusable launch vehicle are presented for nominal e ight and under failure cases that require considerable adaptation.

[1]  Andrew R. Teel,et al.  Control of linear systems with saturating actuators , 1995, Proceedings of 1995 American Control Conference - ACC'95.

[2]  Yuri B. Shtessel,et al.  Reusable Launch Vehicle Control in Multiple Time Scale Sliding Modes , 2000 .

[3]  Anuradha M. Annaswamy,et al.  Adaptive control in the presence of saturation non-linearity , 1997 .

[4]  Ping Lu,et al.  Tracking control of nonlinear systems with bounded controls and control rates , 1996, Autom..

[5]  Kevin A. Wise,et al.  Flight Testing of Reconfigurable Control Law on the X-36 Tailless Aircraft , 2001 .

[6]  Y. B. Shtessel,et al.  Multiple time scale flight control using re-configurable sliding modes , 1998, Proceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171).

[7]  M. Bodson,et al.  Flight testing of a reconfigurable control system on an unmanned aircraft , 2004, Proceedings of the 2004 American Control Conference.

[8]  Frank L. Lewis,et al.  Feedback linearization using neural networks , 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

[9]  Michel Kinnaert,et al.  Conditioning technique, a general anti-windup and bumpless transfer method , 1987, Autom..

[10]  Anthony J. Calise,et al.  Adaptive output feedback control of nonlinear systems using neural networks , 2001, Autom..

[11]  Anthony J. Calise,et al.  Experimental results on adaptive output feedback control using a laboratory model helicopter , 2002, IEEE Transactions on Control Systems Technology.

[12]  Ali Saberi,et al.  Output regulation of linear plants subject to constraints , 2003 .

[13]  Kurt Hornik,et al.  Multilayer feedforward networks are universal approximators , 1989, Neural Networks.

[14]  Manfredi Maggiore,et al.  Adaptive Output Feedback Control , 2002 .

[15]  Taeyoung Lee,et al.  Nonlinear Adaptive Flight Control Using Neural Networks and Backstepping , 2000 .

[16]  Jing Sun,et al.  Modified model reference adaptive control with saturated inputs , 1992, [1992] Proceedings of the 31st IEEE Conference on Decision and Control.

[17]  D. Bernstein,et al.  A chronological bibliography on saturating actuators , 1995 .

[18]  Anthony J. Calise,et al.  Adaptive Autopilot Design for Guided Munitions , 1998 .

[19]  Tingshu Hu,et al.  An analysis and design method for linear systems subject to actuator saturation and disturbance , 2002, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).

[20]  Fujio Ohkawa,et al.  A discrete model reference adaptive control system for a plant with input amplitude constraints , 1982 .

[21]  Anthony J. Calise,et al.  Adaptive output feedback for high-bandwidth flight control , 2002 .

[22]  O. A. Sebakhy,et al.  A discrete model reference adaptive system design , 1976 .

[23]  Frank L. Lewis,et al.  Neural net robot controller with guaranteed tracking performance , 1995, IEEE Trans. Neural Networks.

[24]  G. Rovithakis.  Nonlinear adaptive control in the presence of unmodelled dynamics using neural networks , 1999, Proceedings of the 38th IEEE Conference on Decision and Control (Cat. No.99CH36304).

[25]  Craig A. Kluever.  Unpowered Approach and Landing Guidance Using Trajectory Planning , 2004 .

[26]  Richard Monopoli,et al.  Adaptive control for systems with hard saturation , 1975, 1975 IEEE Conference on Decision and Control including the 14th Symposium on Adaptive Processes.

[27]  Anthony J. Calise,et al.  Augmenting Adaptive Approach to Control of Flexible Systems , 2002 .

[28]  Frank L. Lewis,et al.  High-Level Feedback Control with Neural Networks , 1998, World Scientific Series in Robotics and Intelligent Systems.

[29]  Anthony J. Calise,et al.  Nonlinear flight control using neural networks , 1994 .

[30]  Anthony J. Calise,et al.  Development of a Reconfigurable Flight Control Law for Tailless Aircraft , 2001 .

[31]  Anthony J. Calise,et al.  Hierarchical Approach to Adaptive Control for Improved Flight Safety , 2001 .

[32]  Luca Zaccarian,et al.  Anti-windup design for manual flight control , 1999, Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251).

[33]  John M. Hanson,et al.  ASCENT, TRANSITION, ENTRY, AND ABORT GUIDANCE ALGORITHM DESIGN FOR THE X-33 VEHICLE , 1998 .

[34]  K. Narendra,et al.  A New Adaptive Law for Robust Adaptation without Persistent Excitation , 1986, 1986 American Control Conference.

[35]  Frank L. Lewis,et al.  Multilayer neural-net robot controller with guaranteed tracking performance , 1996, IEEE Trans. Neural Networks.

[36]  Ming Xin,et al.  New Nonlinear Control Technique for Ascent Phase of Reusable Launch Vehicles , 2004 .

[37]  David B. Doman,et al.  Dynamic Inversion-Based Adaptive/Reconfigurable Control of the X-33 on Ascent , 2002 .

[38]  Key Words-Nonlinear,et al.  Tracking Control of Nonlinear Systems with Bounded Controls and Control Rates , 1997 .

[39]  S. P. Kárason,et al.  Adaptive Control in the Presence of Input Constraints , 1993, American Control Conference.

[40]  J. R. Thibodeau,et al.  Space Shuttle ascent guidance, navigation, and control , 1979 .

[41]  J. M. Wohletz,et al.  Retrofit Reconfiguration System for a Commercial Transport , 2000 .

[42]  Ali Saberi,et al.  Output regulation of linear plants with actuators subject to amplitude and rate constraints , 1999 .

[43]  Charles Hall,et al.  X-33 Attitude Control System Design for Ascent, Transition, and Entry Flight Regimes , 1998 .

[44]  Zongli Lin,et al.  Control of Linear Systems with Saturating ActuatorsAli , 1996 .

[45]  Anthony J. Calise,et al.  Multilayer neural network and adaptive nonlinear control of agile anti-air missiles , 1997 .

[46]  Manfred Morari,et al.  A unified framework for the study of anti-windup designs , 1994, Autom..

[47]  Yuri B. Shtessel,et al.  Multiple Timescale Flight Control Using Reconfigurable Sliding Modes , 1999 .

[48]  John M. Hanson,et al.  Advanced Guidance and Control Project for Reusable Launch Vehicles , 2000 .

[49]  Eric N. Johnson,et al.  Limited authority adaptive flight control , 2000 .

[50]  Anthony J. Calise,et al.  Nonlinear adaptive flight control using neural networks , 1998 .