Selection and impact of different topologies in multi-layered hierarchical fuzzy systems

Applied Intelligence

Volumn 36, Issue 3, 2012, Pages 564-584

  Zajaczkowski, Juliusz ^a   Verma, Brijesh ^a  

^a CENTRAL QUEENSLAND UNIVERSITY   (Australia)

Author keywords

Evolutionary algorithms; Fuzzy logic; Inverted pendulum

Indexed keywords

CONTROL PROCESS; CONTROLLER PERFORMANCE; FUZZY RULE BASE; HIERARCHICAL DECOMPOSITIONS; HIERARCHICAL FUZZY SYSTEMS; INVERTED PENDULUM; INVERTED PENDULUM SYSTEM; MULTI-LAYERED; MULTI-LAYERED STRUCTURE; TEST CONTROLLERS;

DYNAMICAL SYSTEMS; EVOLUTIONARY ALGORITHMS; FUZZY LOGIC; PENDULUMS; TOPOLOGY;

FUZZY SYSTEMS;

EID: 84862125535     PISSN: 0924669X     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10489-011-0277-0     Document Type: Article

References (60)

1. Cordon O, Herrera F, Hoffmann F, Magdalena L (2001) Genetic fuzzy systems: evolutionary tuning and learning of fuzzy knowledge bases. Advances in fuzzy systems applications and theory, vol 19. World Scientific, Singapore
2. Cordon O, Herrera F, Zwir I (2001) Linguistic modeling of hierarchical systems of linguistic rules. IEEE Trans Fuzzy Syst 10(1):2-20
3. Konar A (2005) Computational intelligence. Springer, Berlin
4. Babuska R (2009) Computational intelligence in modelling and control. Delft University of Technology. http://www.dcsc. tudelft.nl/~rbabuska/CTU/ transp/lecture-notes-ctu.pdf
5. Zadeh LA (1973) Outline of a new approach to the analysis of complex systems and decision processes. IEEE Trans Syst Man Cybern 3(1):177-200
6. Pedrycz W (1984) An identification algorithm in fuzzy relational systems. Fuzzy Sets Syst 13:153-167 (Pubitemid 14604942)
7. Takagi T, Sugeno M (1985) Fuzzy identification of systems and its applications to modelling and control. IEEE Trans Syst Man Cybern 15(1):116-132
8. Raju GVS, Zhou J, Kisner RA (1991) Hierarchical fuzzy control. Int J Control, 54(5):1201-1216 (Pubitemid 21706885)
9. Zajaczkowski J, Verma B (2010) An evolutionary algorithm based approach for selection of topologies in hierarchical fuzzy systems. In: WCCI 2010 IEEE World congress on computational intelligence, CCIB, Barcelona, Spain, July 18-23, 2010, pp 976-983
10. Zajaczkowski J, Stonier RJ (2008) Analysis of hierarchical control for the inverted pendulum. Complex Int 12:msid49. http://www.complexity.org.au/ vol12/msid49/
11. Stonier RJ, Stacey AJ, Messom C (1998) Learning fuzzy controls for the inverted pendulum. In: Proceedings of ISCA 7th international conference on intelligent systems, Melun, pp 64-67
12. Chen CS, Chen WL (1998) Robust adaptive sliding-mode control using fuzzy modelling for an inverted-pendulum system. IEEE Trans Ind Electron 45(2):297-306
13. Chen BS, Uang HJ, Tseng CS (1999) Robustness design of nonlinear dynamic systems via fuzzy linear control. IEEE Trans Fuzzy Syst 7(5):571-585
14. Zhong W, Rock H (2001) Energy and passivity based control of the double inverted pendulum on a cart. In: 2001 IEEE conference on control applications, pp 896-901 (Pubitemid 34090015)
15. Durr P, Mattiussi C (2010) Genetic representation and evolvability of modular neural controllers. IEEE Comput Intell Mag, 11-19. doi:10.1109/MCI.2010. 937319
16. Acampora G (2010) Exploiting timed automata-based fuzzy controllers and data mining to detect computer network intrusions. In: WCCI 2010 IEEE World congress on computational intelligence, FUZZ, Barcelona, Spain, July 18-23, 2010, pp 1381-1388
17. Acampora G, Loia V, Vitiello A (2010) Hybridizing fuzzy control and timed automata for modeling variable structure fuzzy systems. In: WCCI 2010 IEEE World congress on computational intelligence, FUZZ, Barcelona, Spain, July 18-23, 2010, pp 1894-1901
18. Hsu YC, Chen G, Li HX (2001) A fuzzy adaptive variable structure controller with applications to robot manipulators. IEEE Trans Syst Man Cybern, Part B, Cybern 31(3):331-340 (Pubitemid 32676837)
19. Huang YP, Wang SF (2000) Designing a fuzzy model by adaptive macroevolution genetic algorithms. Fuzzy Sets Syst 113:367-379
20. Abraham A (2005) Adaptation of fuzzy inference system using neural learning, fuzzy system engineering: theory and practice. In: Nedjah N et al (eds) Studies in fuzziness and soft computing, Chap. 3. Springer, Berlin, pp 53-83
21. Chen Y, Yang B, Abraham A, Peng L (2007) Automatic design of hierarchical Takagi-Sugeno type fuzzy systems using evolutionary algorithms. IEEE Trans Fuzzy Syst 15(3):385-397. doi:10.1016/S0020-0255(01)00140-2 (Pubitemid 46971551)
22. Torra V (2002) A review of the construction of hierarchical fuzzy systems. Int J Intell Syst 17(5):531-543. doi:10.1002/int.10036 (Pubitemid 34491735)
23. Tunstel E, de Oliveira MAA, Berman S (2002) Fuzzy behavior hierarchies for multi-robot control. Int J Intell Syst 17(5):449-470. doi:10.1002/int.10032 (Pubitemid 34491731)
24. Magdalena L (2002) On the role of context in hierarchical fuzzy controllers. Int J Intell Syst 17(5):471-493. doi:10.1002/int.10033 (Pubitemid 34491732)
25. Tachibana K, Furuhashi T (2002) A structure identification method of submodels for hierarchical fuzzy modeling using the multiple objective genetic algorithm. Int J Intell Syst 17(5):495-513. doi:10.1002/int.10034 (Pubitemid 34491733)
26. Kikuchi H, Takagi N (2002) Hierarchical fuzzy modeling and jointly expandable functions. Int J Intell Syst 17(5):515-529. doi:10.1002/int.10035 (Pubitemid 34491734)
27. Lee ML, Chung HY, Yu FM (2003) Modeling of hierarchical fuzzy systems. Fuzzy Sets Syst 138(2):343-361. doi:10.1016/S0165-0114(02)00517-1
28. Cordon O, Herrera F, Zwir I (2002) A hierarchical knowledge-based environment for linguistic modeling: models and iterative methodology. Fuzzy Sets Syst 138(2):307-341. doi:10.1016/j.asoc.2006.12.001
29. Delgado MR, von Zuben F, Gomide F (2003) Hierarchical genetic fuzzy systems. Fuzzy Sets Syst 138(2):307-341. doi:10.1016/S0165-0114(02)00388-3
30. Sushmita S, Chaudhury S (2007) Hierarchical fuzzy case based reasoning with multi-criteria decision making for financial applications. In: Pattern recognition and machine intelligence. Lecture notes in computer science, vol 4815/2007. Springer, Berlin, pp 226-234 doi:10.1007/978-3-540-77046-6-28
31. Cheong F (2008) A hierarchical fuzzy system with high input dimensions for forecasting foreign exchange rates. International J Artif Intell Soft Comput 1(1):15-24
32. Stonier RJ, Mohammadian M (2004) Multi-layered and hierarchical fuzzy modelling using evolutionary algorithms. In: Proceedings of CIMCA'2004, Gold Coast, pp 321-344
33. Yager RR (1998) On the construction of hierarchical fuzzy systems models. IEEE Trans Syst Man Cybern 28(1):55-66 (Pubitemid 128748607)
34. Holve R (1997) Rule generation for hierarchical fuzzy systems. In: Fuzzy information processing society, 1997, NAFIPS '97, pp 444-449. doi:10.1109/NAFIPS.1997.624082
35. Sindelar R (2005) Hierarchical fuzzy systems. In: Proceedings of the 16th IFAC World congress, 2005, vol 15(1). doi:10.3182/20050703-6-CZ-1902.01119
36. Mon YJ, Lin CM (2002) Hierarchical fuzzy sliding-mode control. In: Proceedings of the 2002 IEEE World congress on computational intelligence, pp 656-661. doi:10.1109/FUZZ.2002.1005070
37. Yeh ZM, Li KH (2004) A systematic approach for designing multistage fuzzy control systems. Fuzzy Sets Syst 143(2):251-273
38. Dasgupta D (1998) Evolving neuro-controllers for a dynamic system using structured genetic algorithm. Appl Intell 8:113-121 (Pubitemid 128512695)
39. Wang W, Yi J, Zhao DX, Liu X (2005) Design of cascade fuzzy sliding-mode controller. In: 2005 American control conference, Portland, USA, pp 4649-4654 (Pubitemid 41188737)
40. Cheong F, Lai R (2007) Designing a hierarchical fuzzy controller using the differential evolution approach. Appl Soft Com-put 7(2):481-491 (Pubitemid 46205479)
41. Magdalena L (1998) Hierarchical fuzzy control of a complex system using meta-knowledge. In: Proceedings of the 7th international conference on information processing and management of uncertainty in knowledge-based systems, pp 630-637
42. Lei S, Langari R (2003) Synthesis and approximation of fuzzy logic controllers for nonlinear systems. Int J Fuzzy Syst 5(2):98-105
43. Lin CM, Mon YJ (2005) Decoupling control by hierarchical fuzzy sliding-mode controller. IEEE Trans Control Syst Technol 13(4):593-589
44. Shuliang L, Langari R (2000) Hierarchical fuzzy logic control of a double inverted pendulum. In: Fuzzy system 2000, FUZZ IEEE 2000, 9th IEEE international conference, vol 2, pp 1074-1077
45. Castillo O, Cazarez N, Rico D (2006) Intelligent control of dynamic systems using type-2 fuzzy logic and stability issues. Int Math Forum 1(28):1371-1382
46. Raju S, Zhou J (1993) Adaptive hierarchical fuzzy controller. IEEE Trans Syst Man Cybern 23(4):973-980
47. Yi J, Yubazaki N (2000) Stabilization fuzzy control of inverted pendulum systems. Artif Intell Eng 14:153-163
48. Yu WS, Sun CJ (2001) Fuzzy model based adaptive control for a class of nonlinear systems. IEEE Trans Fuzzy Syst 9:413-425
49. Chang W, Park JB, Joo YH, Chen G (2002) Design of robust fuzzy-model based controller with sliding mode control for SISO nonlinear systems. Fuzzy Sets Syst 125:1-22 (Pubitemid 33089109)
50. Koo TJ (2001) Stable model reference adaptive fuzzy control of a class of nonlinear systems. IEEE Trans Fuzzy Syst 9(4):624-636 (Pubitemid 32933047)
51. Qiao F, Zhu QM, Winfield A, Melhuish C (2003) Fuzzy sliding mode control for discrete nonlinear systems. Trans China Autom Soc 22(2):313-315
52. Wang LX (1997) A course in fuzzy systems and control. Prentice Hall, New York
53. Khan SA, Engelbrecht AP (2010) A fuzzy particle swarm optimization algorithm for computer communication network topology design. Appl Intell. doi:10.1007/s10489-010-0251-2
54. Gacto MJ, Alcala R, Herrera F (2010) A multi-objective evolutionary algorithm for an effective tuning of a fuzzy logic controllers in heating, ventilating and air conditioning systems. Appl Intell. doi:10.1007/s10489-010- 0264-x
55. Erus G, Polat F (2007) A layered approach to learning coordination knowledge in multiagent environments. Appl Intell 27:249-267. doi:10.1007/s10489-006-0034-y (Pubitemid 47518989)
56. Chen CM (2005) A hierarchical neural network document classifier with linguistic feature selection. Appl Intell 23:277-294
57. Hong TP, KY Lin, Chien BC (2003) Mining fuzzy multiple-level association rules from quantitative data. Appl Intell 18:79-90
58. Cho SB, Shimohara K (1998) Evolutionary learning of modular neural networks with genetic programming. Appl Intell 9:191-200 (Pubitemid 128512700)
59. Akole M, Tyagi B (2008) Design of fuzzy logic controller for nonlinear model of inverted pendulum-cart system. In: XXXII national systems conference NSC 2008, pp 750-755
60. Beceriklia Y, Celik BK (2007) Fuzzy control of inverted pendulum and concept of stability using Java application. Math Comput Model 46(1-2):24-37 (Pubitemid 46660507)