Abstract
In this chapter we present some basic concepts about the work to understand better the idea and the context of this book.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Cervantes, L., Castillo, O.: Design of a fuzzy system for the longitudinal control of an F-14 airplane. In: Soft Computing for Intelligent Control and Mobile Robotics, vol. 318, pp. 213–224. Springer, Berlin (2011)
Cervantes, L., Castillo, O.: Intelligent control of nonlinear dynamic plants using a hierarchical modular approach and type-2 fuzzy logic. In: Lecture Notes in Computer Science, vol. 7095, pp. 1–12. Springer, Berlin (2011)
Cervantes, L., Castillo, O.: Hierarchical genetic algorithms for optimal type-2 fuzzy system design. In: Annual Meeting of the North American Fuzzy Information Processing Society, pp. 324–329 (2011)
Cervantes, L., Castillo, O.: Automatic design of fuzzy systems for control of aircraft dynamic systems with genetic optimization. In: World Congress and AFSS International Conference, pp. OS-413-1–OS-413-7 (2011)
Cervantes, L., Castillo, O.: Comparative study of type-1 and type-2 fuzzy systems for the three-tank water control problem. In: LNAI, vol. 7630, pp. 362–373. Springer, Berlin (2013)
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), 213–227 (2014)
Chalupa, P., Novák, J., Bobál, V.: Detailed Simulink model of real time three tank system. In: Proceedings of the 2nd International Conference on Circuits, Systems, Communications and Computers 2011, CSCC’11, pp. 161–166 (2011)
Holland, J.H.: Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor (1975)
Lam, H., Leung, F.: Stability analysis of discrete-time fuzzy-model-based control systems with time delay: time delay-independent approach. Fuzzy Sets Syst. 159(8), 990–1000 (2008)
Lam, H., Leung, F.: Fuzzy rule-based combination of linear and switching state-feedback controllers. Fuzzy Sets Syst. 156(2), 153–184 (2005)
Li, I.-H., Lee, L.-W.: A hierarchical structure of observer-based adaptive fuzzy-neural controller for MIMO systems. Fuzzy Sets Syst. 185(1), 52–82 (2011)
Malla, S., Bhende, C.: Voltage control of stand-alone wind and solar energy system. Int. J. Electr. Power Energy Syst. 56, 361–373 (2014)
Niemann, H., Stoustrup, J.: Passive fault tolerant control of a double inverted pendulum a case study. Control Eng. Pract. 13(8), 1047–1059 (2005)
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), 11641–11651 (2009)
Ornelas-Tellez, F., Sanchez, E., Loukianov, A., Rico, J.: Robust inverse optimal control for discrete-time nonlinear system stabilization. Eur. J. Control 20(1), 38–44 (2014)
Sung, H., Kim, D., Park, J., Joo, Y.: Robust digital control of fuzzy systems with parametric uncertainties: LMI-based digital redesign approach. Fuzzy Sets Syst. 161(6), 919–933 (2010)
Warren, P.: Mechanics of Flight, 2nd edn. Wiley, Hoboken, New Jersey (2010)
Castillo, O., Melin, P.: A review on the design and optimization of interval type-2 fuzzy controllers. Appl. Soft Comput. 12(4), 1267–1278 (2012)
Castillo, O., Melin, P.: New fuzzy-fractal-genetic method for automated mathematical modelling and simulation of robotic dynamic systems. In: IEEE International Conference on Fuzzy Systems, vol. 2, pp. 1182–1187 (1998)
Chen, G., Pham, T.: Introduction to Fuzzy Sets, Fuzzy Logic, and Fuzzy Control Systems. CRC Press, Boca Raton (2001)
Dadios, E.: Fuzzy Logic-Controls, Concepts, Theories and Applications (2012)
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), 1229–1234 (2010)
Sepulveda, R., Castillo, O., Melin, P., Montiel, O.: An efficient computational method to implement type-2 fuzzy logic in control application. In: Analysis and Design of Intelligent System Using Soft Computing Techniques 2007, pp. 45–52 (2007)
Zadeh, L.: Fuzzy Sets and Fuzzy Information Granulation Theory. Beijing Normal University Press, Beijing (2000)
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, 23–25 (1998)
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), 1–10 (2005)
Ouyang, P.R., Acob, J., Pano, V.: PD with sliding mode control for trajectory tracking of robotic system. Robot. Comput. Integr. Manuf. 30(2), 189–200 (2014)
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, 19–38 (2012)
Cázarez, N., Aguilar, L., Castillo, O.: Fuzzy logic control with genetic parameters optimization for the output regulation of a servomechanism with nonlinear backlash. Expert Syst. Appl. 37(6), 4368–4378 (2010)
Haupt, R., Haupt, S.: Practical Genetic Algorithm. Wiley Interscience, Hoboken (2004)
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), 4590–4598 (2012)
No, T.S., Mina, B.M., Stone, R.H., Wong, K.C.: Control and Simulation of Arbitrary Flight Trajectory-Tracking, pp. 560–756. Department of Aerospace Engineering, Chonbuk National University, Deokjin Dong, Chonju NSW (2006)
Caughey, D.: Introduction of Aircrafts Stability and Control Course Notes for M&AE 5070. Sibbley School of Mechanical and Aerospace Engineering, Cornell University, New York, pp. 14853–17501 (2011)
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), 2124–21322 (2009)
Pedrycz, W., Chen, S.: Granular Computing and Intelligent System, Design with Information Granules of Higher Order and Higher Type. Intelligent Systems Reference Library, vol. 13 (2011)
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), 47–60 (2004)
Sanchez, E., Becerra, H., Velez, C.: Combining fuzzy, PID and regulation control for an autonomous mini-helicopter. J. Inf. Sci. 177(10), 1999–2022 (2007)
Schmidt, D.: Modern Flight Dynamics. McGraw Hill, New York (2012)
Song, Q., Song, Y.D.: Generalized PI control design for a class of unknown nonaffine systems with sensor and actuator faults. Syst. Control Lett. 64, 86–95 (2014)
Song, Y., Wang, H.: Design of flight control system for a small unmanned tilt rotor aircraft. Chin. J. Aeronaut. 22(3), 250–256 (2009)
Tao, C., Taur, J., Wang, C., Chen, U.: Fuzzy hierarchical swing-up and sliding position controller for the inverted pendulum–cart system. Fuzzy Sets Syst. 159(20), 2763–2784 (2008)
Zadeh, L.A.: Outline of a new approach to the analysis of complex systems and decision processes. IEEE Trans. Syst. ManCybern. SMC 3, 28–44 (1973)
Zhang, Y., Wang, Q., Dong, Ch., Jiang, Y.: H∞ output tracking control for flight control systems with time-varying delay. Chin. J. Aeronaut. 26(5), 1251–1258 (2013)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2016 The Author(s)
About this chapter
Cite this chapter
Cervantes, L., Castillo, O. (2016). Theory and Background. In: Hierarchical Type-2 Fuzzy Aggregation of Fuzzy Controllers . SpringerBriefs in Applied Sciences and Technology(). Springer, Cham. https://doi.org/10.1007/978-3-319-26671-8_2
Download citation
DOI: https://doi.org/10.1007/978-3-319-26671-8_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-26670-1
Online ISBN: 978-3-319-26671-8
eBook Packages: EngineeringEngineering (R0)