Type-2 fuzzy logic aggregation of multiple fuzzy controllers for airplane flight control

Information Sciences

Volumn 324, Issue , 2015, Pages 247-256

  Cervantes, Leticia ^a   Castillo, Oscar ^a  

^a TIJUANA INSTITUTE OF TECHNOLOGY   (Mexico)

Author keywords

fuzzy control; fuzzy systems; Genetic algorithms; Type 2 fuzzy logic

Indexed keywords

AIRCRAFT; COMPUTER CIRCUITS; CONTROLLERS; FLIGHT CONTROL SYSTEMS; FUZZY LOGIC; FUZZY SYSTEMS; GENETIC ALGORITHMS; HIERARCHICAL SYSTEMS; MULTIVARIABLE CONTROL SYSTEMS;

CONTROL APPROACH; CONTROL STRATEGIES; FUZZY CONTROLLERS; HIERARCHICAL ARCHITECTURES; OPTIMIZATION METHOD; STATISTICAL COMPARISONS; STUDENT - TESTS; TYPE-2 FUZZY LOGIC;

FUZZY CONTROL;

EID: 84940666732     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2015.06.047     Document Type: Article

References (48)

1. Attia A.-F. Hierarchical fuzzy controllers for an astronomical telescope tracking Appl. Soft Comput. 9 1 2009 135 141
2. Azar A. Overview of type-2 fuzzy logic systems Int. J. Fuzzy System Appl. 2 4 2012 1 28
3. Caughey D. Introduction of aircrafts stability and control course notes for M&AE 5070 Sibbley School of Mechanical & Aerospace Engineering 2011 Cornell University New York 1 147
4. Castillo O., Martinez-Marroquin R., Melin P., Valdez F., Soria J. Comparative study of bio-inspired algorithms applied to the optimization of type-1 and type-2 fuzzy controllers for an autonomous mobile robot Inf. Sci 192 2012 19 38
5. Castillo O., Melin P. A review on the design and optimization of interval type-2 fuzzy controllers Appl. Soft Comput. 12 4 2012 1267 1278
6. Castillo O., Melin P. New fuzzy-fractal-genetic method for automated mathematical modelling and simulation of robotic dynamic systems Proceedings of IEEE International Conference on Fuzzy Systems vol. 2 1998 1182 1187
7. O. Castillo, P. Melin, Type-2 fuzzy logic: theory and applications, in: Studies in Fuzziness and Soft Computing, Springer, Berlin, 2008.
8. Cázarez N., Aguilar L., Castillo O. Fuzzy logic control with genetic membership function parameters optimization for the output regulation of a servomechanism with nonlinear backlash Expert Syst. Appl 37 6 2010 4368 4378
9. Cervantes L., Castillo O. Design of a fuzzy system for the longitudinal control of an F-14 airplane Soft Computing for Intelligent Control and Mobile Robotics 2011 Springer 213 224 318/2011
10. Cervantes L., Castillo O. Intelligent control of nonlinear dynamic plants using a hierarchical modular approach and type-2 fuzzy logic Lecture Notes in Computer Science 2011 Springer 1 12 7095/2011
11. Cervantes L., Castillo O. Hierarchical genetic algorithms for optimal type-2 fuzzy system design Proceedings of Annual Meeting of the North American Fuzzy Information Processing Society 2011 324 329
12. Cervantes L., Castillo O. Automatic design of fuzzy systems for control of aircraft dynamic systems with genetic optimization Proceedings of World Congress and AFSS International Conference 2011 OS-413-1-OS-413-7
13. Cervantes L., Castillo O. Comparative study of type-1 and type-2 fuzzy systems for the three-tank water control problem LNAI 7630 2013 362 373 2013.Springer
14. Cervantes L., Castillo O. Genetic design of optimal type-1 and type-2 fuzzy systems for longitudinal control of an airplane J. Intell. Autom. Soft Comput. 20 2 2014 213 227
15. Chalupa P., Novák J., Bobál V. Detailed simulink model of real time three tank system Proceedings of the 2nd international conference on Circuits, Systems, Communications & Computers, CSCC'11 2011 161 166
16. C.R. Chalk et al., Background Information and Users Guide for MIL-F-8785B(ASG), 'Military Specification - Flying Qualities of Piloted Airplanes, AFFDL-TR-69-72, Air Force Flight Dynamics Laboratory, Wright-Patterson AFB, Ohio, August 1969.
17. Chen G., Pham T. Introduction to Fuzzy Sets, Fuzzy Logic, and Fuzzy Control Systems 2001 CRC Press
18. Dadios E. Fuzzy Logic-Controls, Concepts, Theories and Applications 2012 Intech Press
19. Federal Aviation Administration Pilot's Handbook of Aeronautical Knowledge U.S. Department of Transportation Book 2013
20. Haupt R., Haupt S. Practical Genetic Algorithm 2004 Wiley Interscience
21. Hidalgo D., Melin P., Castillo O. An optimization method for designing type-2 fuzzy inference systems based on the footprint of uncertainty using genetic algorithms Expert Syst. Appl. 39 4 2012 4590 4598
22. Lam H., Leung F. Stability analysis of discrete-time fuzzy-model-based control systems with time delay: time delay-independent approach Fuzzy Sets and Syst. 159 8 2008 990 1000
23. Lam H., Leung F. Fuzzy rule-based combination of linear and switching state-feedback controllers Fuzzy Sets and Syst. 156 2 2005 153 184
24. Li I.-H., Lee L.-W. A hierarchical structure of observer-based adaptive fuzzy-neural controller for MIMO systems Fuzzy Sets and Syst. 185 1 2011 52 82
25. Malla S., Bhende C. Voltage control of stand-alone wind and solar energy system Int. J. Electr. Power & Energy Syst. 56 2014 361 373
26. Niemann H, Stoustrup J Passive fault tolerant control of a double inverted pendulum a case study Control Eng. Pract. 13 8 2005 1047 1059
27. No T.S., Kim J-E., Moon J.H., Kim S.J. Modeling, control, and simulation of dual rotor wind turbine generator system Renew. Energy 34 10 2009 2124-2132 2
28. No T.S., Mina B.M., Stone R.H., Wong K.C. Control and simulation of arbitrary flight trajectory-tracking 2006 Department of Aerospace Engineering, Chonbuk National University Deokjin Dong, Chonju NSW 560 756
29. Oh S.-k., Jung S.-H., Pedrycz W. Design of optimized fuzzy cascade controllers by means of hierarchical fair competition-based genetic algorithms Expert Syst. Appl. 36 9 2009 11641 11651
30. Ornelas-Tellez F., Sanchez E., Loukianov A., Rico J. Robust inverse optimal control for discrete-time nonlinear system stabilization Eur. J. Control 20 1 2014 38 44
31. Ouyang P.R., Acob J., Pano V. PD with sliding mode control for trajectory tracking of robotic system Robotics and Compu. Integr. Manuf. 30 2 2014 189 200
32. Pedrycz W., Chen S. Granular computing and Intelligent system, design with information granules of higher order and higher type Intell. Syst. Ref. libr. 13 2011
33. Rachman E., Jaam J., Hasnah A. Non-linear simulation of controller for longitudinal control augmentation system of F-16 using numerical approach Inf. Sci. J. 164 1-4 2 2004 47 60
34. R. Rojas, Neural Networks, Springer, Berlin, 1996.
35. Sanchez E., Becerra H., Velez C. Combining fuzzy, PID and regulation control for an autonomous mini-helicopter J. Inf. Sci. 177 10 2007 1999 2022
36. D. Schmidt, Modern Flight Dynamics, Mc Graw Hill, New York, 2012.
37. Sefer K., Omer C., Okyay K. Adaptive neuro-fuzzy inference system based autonomous flight control of unmanned air vehicles Expert Syst. Appl. J. 37 2 2010 1229 1234
38. Sepulveda R., Castillo O., Melin P., Montiel O. An efficient computational method to implement type-2 fuzzy logic in control application Anal. Des. Intell. Syst. using soft comput. Tech. 41 2007 45 52
39. R. Sepúlveda et al., Optimizing the MFs in type-2 fuzzy logic controllers, using the human evolutionary model, Int. Rev. Autom. Control (IREACO), Theory and Appl., 3 (1), 1-10.
40. Song Q., Song Y.D. Generalized PI control design for a class of unknown non affine systems with sensor and actuator faults Syst. Control Lett. 64 2014 86 95
41. Song Y., Wang H. Design of flight control system for a small unmanned tilt rotor aircraft Chin. J. Aeronaut. 22 3 2009 250 256
42. Sung H., Kim D., Park J., Joo Y. Robust digital control of fuzzy systems with parametric uncertainties: LMI-based digital redesign approach Fuzzy Sets and Syst. 161 6 16 2010 919 933
43. Tao C., Taur J., Wang C., Chen U. Fuzzy hierarchical swing-up and sliding position controller for the inverted pendulum-cart system Fuzzy Sets and Syst. 159 20 16 October 2008 2763 2784
44. Yu Y., Chen L., Sun F., Wu C. Matlab/Simulink-based simulation for digital-control system of marine three-shaft gas-turbine Appl. Energy 80 1 2005 1 10
45. Zadeh L. Fuzzy Sets and Fuzzy Information Granulation Theory 2000 Normal University Press Beijing Beijing
46. Zadeh L.A. Some reflections on soft computing, granular computing and their roles in the conception, design and utilization of information/intelligent systems Soft Comput 2 1998 23 25
47. Zadeh L.A. Outline of a new approach to the analysis of complex systems and decision processes IEEE Trans. Syst. Man Cybern. SMC-3 3 1973 28 44
48. ∞ output tracking control for flight control systems with time-varying delay Chin. J. Aeronaut. 26 5 2013 1251 1258