Subscribe Now Subscribe Today
Research Article

An Optimal Backstepping Design for Blended Aero and Reaction-Jet Missile Autopilot

Liu Zhong , Xiao-Geng Liang , Bing-Gang Cao and Jun-Yi cao
Facebook Twitter Digg Reddit Linkedin StumbleUpon E-mail

A novel robust adaptive backstepping control approach is presented to design a pitch controller for missiles employing blended aerodynamic control and Reaction-jet Control System (RCS). The main features of this study are that a certain type of control Lyapunov function is obtained by function reconstruction to decrease the control-input fluctuation caused by mismatched controller parameters, optimal backstepping parameter set and Lyapunov function choice are gotten by Genetic Algorithm (GA). So both system stability and dynamic performance are guaranteed. Since the model of a missile with RCS is inaccurate with uncertain effect of RCS and aerodynamic parameters, a Fuzzy Cerebellar Model Articulation Controller (FCMAC) neural network is used to guarantee controller robustness, thus the bounds of model uncertainties are not needed. Finally, simulation results demonstrate the efficiency and advantages of the proposed method.

Related Articles in ASCI
Similar Articles in this Journal
Search in Google Scholar
View Citation
Report Citation

  How to cite this article:

Liu Zhong , Xiao-Geng Liang , Bing-Gang Cao and Jun-Yi cao , 2006. An Optimal Backstepping Design for Blended Aero and Reaction-Jet Missile Autopilot . Journal of Applied Sciences, 6: 2623-2628.

DOI: 10.3923/jas.2006.2623.2628


1:  Cheng, F.Z., Z.M. Wang and S.L. Chen and B.S. Yu, 2003. Side jet and aerodynamics compound control system design of air defense missiles. Flight Dyn., 21: 49-52.
Direct Link  |  

2:  Chen, X. and T.X. Ying, 2004. Study on parameter designing and performance for genetic algorithm. Comput. Eng. Design, 25: 1309-1311.

3:  Chamberlain, R.R., 1990. Calculation of three-dimensional jet interact-tion flowfields. Proceedings of the 26th AIAA and ASEE Joint Propulsion Conference, Jul. 16-18, Orlando, USA., pp: 993-998.

4:  Kim, D., 2002. A design of CMAC-based fuzzy logic cotroller with fast learning and accurate approximation. Fuzzy Set Syst., 125: 48-56.

5:  Kokotovic, P., 1999. Constructure nonlinear control: Progress in the 90`s. Proceedings of IFAC 14th Word Congress, 1999, Beijing, China, pp: 49-78.

6:  Krstic, M. and P. Kokotovic, 1996. Modular approach to adaptive stabilization. Automatica, 32: 625-629.
Direct Link  |  

7:  Kwan, C.M. and H. Xu, 1996. Robust spacecraft attitude control using cmac. Proceedings of the IEEE International Symposium on Intelligent Control, Sept. 15-18, Dearborn, MI., USA., pp: 43-48.

8:  Polycarpou, M.M. and P.A. Ioannou, 1996. A robust adaptive nonlinear control design. Automatica, 32: 423-427.
CrossRef  |  Direct Link  |  

9:  Qian, X.F., R.X. Lin and Y.N. Zhao, 2000. Missile Flight Dynamics. Beijing Institute of Technology Press, Beijing, pp: 88-111.

10:  Rui, H. and S. Koichi, 2001. Autopilot design for a missile with reaction-jet using coeffient diagram method. AIAA Guidance, Navigation, and Control Conference and Exhibit, Aug. 6-9, Canada, USA.

11:  Thukral, A. and M. Innocenti, 1998. A sliding mode missile pitch autopilot synthesis for high angle of attack maneuvering. IEEE Trans. Control Syst. Technol., 6: 231-238.

©  2021 Science Alert. All Rights Reserved