Применение квантовых мягких вычислений: надежная программно-аппаратная поддержка робастных интеллектуальных контроллеров
Боковая панель статьи
Основное содержимое статьи
Аннотация
Описана обобщенная стратегия проектирования интеллектуальных робастных систем управления на основе технологий квантовых / мягких вычислений, которые повышают надежность гибридных интеллектуальных контроллеров, обеспечивая возможность самоорганизации. Основное внимание уделено свойствам робастности интеллектуальных систем управления в непредвиденных ситуациях управления с помощью моделирования типовых объектов управления.
Скачивания
Информация о статье
Библиографические ссылки
L.V. Litvintseva, K. Takahashi, and S.V. Ulyanov, “Intelligent robust control design based on new types of computation,” Note del Polo Ricerca, Università degli Studi di Milano (Polo Didattico e di Ricerca di Crema) Publ., Vol. 60, 2004; European Patent (EP) PCT 023970, 2005.
L.V. Litvintseva, S.V. Ulyanov, and S. S. Ulyanov, “Design of robust knowledge bases of fuzzy controllers for intelligent control of substantially nonlinear dynamic systems: II A soft computing optimizer and robustness of intelligent control systems,” J. of Computer and Systems Sciences Intern., vol. 45, № 5, pp. 744 – 771; 2006
US Patent No 6,578,018B1, “System and method for control using quantum soft computing” (Inventor: S.V. Ulyanov), US Patent No 7,383,235 B1, 2003; EP PCT 1 083 520 A2, 2001.
L.V. Litvintseva and S.V. Ulyanov, “Quantum fuzzy inference for knowledge base design in robust intelligent controllers,” J. of Computer and Systems Sciences Intern, vol. 46, № 6, pp. 908 – 961, 2007.
L.V. Litvintseva and S.V. Ulyanov, Quantum information and quantum computational intelligence: Quantum optimal control and filtering – stability, robustness, and self-organization models in nanotechnologies. Note del Polo Ricerca, Università degli Studi di Milano (Polo Didattico e di Ricerca di Crema) Publ., vols 81&82, 2005 – 2007.
M.A. Nielsen and L. Chuang, Quantum computation and quantum information, Cambridge Univ. Press, UK, 2000.
S.V. Ulyanov, L.V. Litvintseva, I.S. Ulyanov and S.S. Ulyanov, Quantum information and quantum computational intelligence: Quantum information, decision making and search algorithms, Note del Polo Ricerca, Università degli Studi di Milano (Polo Didattico e di Ricerca di Crema) Publ., vols 83 – 85, Milan, 2005 – 2008.
S.V. Ulyanov, “Self-organization of robust intelligent controller using quantum fuzzy inference,” Proc. of IEEE Intern. Conference ISKE’2008 (3rd Intern. Conf. on Intelligent System and Knowledge Engineering), Xiamen, China, vol.. 1, pp. 726 – 732, 2008.
D.P. DiVincenzo, M. Horodecki, D.W, Leung, J.A. Smolin, and B.M. Terhal, “Locking classical correlation in quantum states,” Physical Review Letters, vol. 92, No 6, pp. 067902, 2004.
S.V. Ulyanov, K. Takahashi, L.V. Litvintseva and T. Hagiwara, “Design of self-organized intelligent control systems based on quantum fuzzy inference: Intelligent system of systems engineering approach,” Proc. of IEEE Intern. Conf. SMC’ 2005, Hawaii, USA,, vol. 4, pp. 3835 – 3840.
S.V. Ulyanov, “Self-organized intelligent robust control based on quantum fuzzy inference,” Recent Advances in Robust Control – Novel Approaches and Design Methods / A. Mueller (Ed.), Ch. 9, In Tech, 2011. pp. 187 – 220.
S.V. Ulyanov, “Quantum soft computing in control processes design: Quantum genetic algorithms and quantum neural network approaches,” In Proc. WAC (ISSCI’) 2004 (5th Intern. Symp. on Soft Computing for Industry), Seville Spain, 2004, vol. 17, pp. 99 – 104.
S. Ulyanov and A. Mishin, “Intelligent robust control of dynamic systems with partial unstable generalized coordinates based on quantum fuzzy inference,” Lecture Notes on AI (LNAI) № 7095, 2011 (MICAI 2011, I. Batyrshin and G. Sidorov (Eds.):), Part II, pp. 24 – 36.
D. Dong, Z. - L., Chen, Z.- H. Chen and C.- B. Zhang,“Quantum mechanics helps in learning for more intelligent robots,” Chin. Phys. Lett., vol. 23, No 7, 2006, pp. 1691 – 1694.
M. Lukac and M Perkowski, “Inductive learning of quantum behaviors,” Facta Universitatis, vol. 20, No 3, 2007, pp. 561 – 586.
E. Kagan and Gal I Ben,. “Navigation of quantum-controlled mobile robots,” Recent Advances in Mobile Robotics. Ch. 15, In Tech, 2011. pp. 311 – 220.
A. Bannikov, S. Egerton, V. Callaghan, B.D Jonson. and M. Shaukat, “Quantum computing: Non – deterministic controllers for artificial intelligent agents,” Proc. 5th Intern. Wokshop Artif. Intell. Techniques for Ambient Intelligence (AITAm’10), Kuala Lumpur, Malasia, 2010.
S.P Chatzis, D. Korkinof and Y Demiris, “A quantum-statistical approach toward robot learning by demonstration,” IEEE Transactions on Robotics, vol. 28, No 6, 2012, pp. 1371 – 1381.
Kouda N., Matsui N. “An examination of qubit neural network in controlling an inverted pendulum,” Neural Processing Letters. 2005, Vol. 22, No 3. pp. 277 – 290.
Panella M., Martinelli G. “Neurofuzzy networks with nonlinear quantum learning,” IEEE Transactions on Fuzzy Systems. 2009, Vol. 17, No 3. pp. 698 – 710.
Chen F., Hou R., Tao G. “Adaptive controller design for faulty UAVs via quantum information technology,” Intern. J. of Adv. Robotic Systems (In Tech). – 2012. – Vol. 9. – Pp. 256:2012.
Gyongyosi L. and Imre S. “Quantum cellular automata controlled self-organizing networks, Cellular automata,” Innovative Modelling for Science and Engineering / Dr. A. Salcido (Ed.). InTech, 2011.
Kim Y.H. and Kim J.H. “Multiobjective quantum-inspired evolutionary algorithm for fuzzy path planning of mobile robot,” IEEE Congress on Evolutionary Computation (CEC 2009). 2009. pp. 1185 – 1192.
Masood A. “A perspective on whether robot localization can be effectively simulated by quantum mechanics,” Intern. J. of Multidisciplinary Sciences and Engineering. 2012, Vol. 3, No 9. pp. 15 – 18.
Dong D., Chen C. “Quantum robot: Structure, algorithms and applications,” Robotica. 2006, Vol. 24, No 4. pp 513 – 521.
Chen C., Dong D. “Quantum intelligent mobile system,” Quantum Inspired Intelligent Systems Studies in Computational Intelligence. 2008, Vol. 121. pp 77 – 102.
Nedjah N., Coelho L., Mourelle L. (Eds) “Quantum Inspired Intelligent Systems.” Springer Verlag, 2008.
Kim S.S., Choia H.J., Kwak K., “Knowledge extraction and representation using quantum mechanics and intelligent models,” Expert Systems with Applications. 2012, Vol. 39, No 3. pp. 3572–3581.