High-order fully actuated system approaches: Part IV. Adaptive control and high-order backstepping

References

• Astolfi, A., Karagiannis, D., & Ortega, R. (2008). Nonlinear and adaptive control with applications. Springer-Verlag.
   Google Scholar
• Aström, K. J. (1980). Design principles for self-tuning regulators. In Methods and applications in adaptive control. Springer.
   Google Scholar
• Aström, K. J., & Wittenmark, B. (1995). Adaptive control (2nd ed.). Addison-Wesley.
   Google Scholar
• Brown, M., & Harris, C. (1994). Neuro fuzzy adaptive modelling and control. Prentice Hall.
   Google Scholar
• Chan, S. W., & Goodwin, G. C. (1982). On the role of the interactor matrix in MIMO adaptive control. IEEE Transactions on Automatic Control, 27(6), 713–714. https://doi.org/10.1109/TAC.1982.1102960
   Web of Science ®Google Scholar
• Cui, G. Y. (2010). Ordinary differential equations: Theory, modeling and development. Tsinghua University Press.
   Google Scholar
• Ding, Z. T. (2013). Nonlinear and adaptive control systems. IET.
   Google Scholar
• Duan, G. R. (1992). Simple algorithm for robust pole assignment in linear output feedback. IEE Proceedings D: Control Theory and Applications, 139(5), 465–470. https://doi.org/10.1049/ip-d.1992.0058
   Google Scholar
• Duan, G. R. (1993). Robust eigenstructure assignment via dynamical compensators. Automatica, 29(2), 469–474. https://doi.org/10.1016/0005-1098(93)90140-O
   Web of Science ®Google Scholar
• Duan, G. R. (2015). Generalized Sylvester equations: Unified parametric solutions. CRC Press.
   Google Scholar
• Duan, G. R. (2020a). High-order system approaches – I. Full-actuation and parametric design. Acta Automatica Sinica, 46(7), 1333–1345. (in Chinese). https://doi.org/10.16383/j.aas.c200234
   Google Scholar
• Duan, G. R. (2020b). High-order system approaches – II. Controllability and fully-actuation. Acta Automatica Sinica, 46(8), 1571–1581. (in Chinese). https://doi.org/10.16383/j.aas.c200369
   Google Scholar
• Duan, G. R. (2020c). High-order system approaches – III. Super-observability and observer design. Acta Automatica Sinica, 46(9). (in Chinese). https://doi.org/10.16383/j.aas.c200370
   Google Scholar
• Duan, G. R. (2020d). High-order fully-actuated system approaches: I. Models and basic procedure. International Journal of System Sciences. https://doi.org/10.1080/00207721.2020.1829167
   Web of Science ®Google Scholar
• Duan, G. R. (2020e). High-order fully-actuated system approaches: II. Generalized strict-feedback systems. International Journal of System Sciences. https://doi.org/10.1080/00207721.2020.1829168
   Web of Science ®Google Scholar
• Duan, G. R. (2020f). High-order fully-actuated system approaches: III. Robust control and high-order backstepping. International Journal of System Sciences.
   Web of Science ®Google Scholar
• Duan, G. R., Irwin, G. W., & Liu, G. P. (2002). Disturbance attenuation in linear systems via dynamical compensators: A parametric eigenstructure assignment approach. IEE Proceedings-Control Theory and Applications, 147(2), 129–136. https://doi.org/10.1049/ip-cta:20000135
   Google Scholar
• Duan, G. R., Liu, G. P., & Thompson, S. (2000). Disturbance attenuation in luenberger function observer designs – A parametric approach. IFAC Proceedings Volumes, 33(14), 41–46. https://doi.org/10.1016/S1474-6670(17)36202-X
   Google Scholar
• Duan, G. R., & Zhao, T. Y. (2020). Observer-based multi-objective parametric design for spacecraft with super flexible netted antennas. Science China Information Sciences, 63(172002), 1–21. https://doi.org/10.1007/s11432-020-2916-8
   Google Scholar
• Fantoni, I., & Lozano, R. (2002). Nonlinear control for underactuated mechanical systems. Springer-Verlag.
   Google Scholar
• Farrell, J. A., & Polycarpou, M. M. (2006). Adaptive approximation based control: Unifying neural, fuzzy, and traditional adaptive approximation approaches. John Wiley and Sons.
   Google Scholar
• Feuer, A., & Morse, A. S. (1978). Adaptive control of single-input single-output linear systems. IEEE Transactions on Automatic Control, 23(4), 557–569. https://doi.org/10.1109/TAC.1978.1101822
   Web of Science ®Google Scholar
• Fradkov, A. L., Miroshnik, I. V., & Nikiforov, V. O. (1999). Nonlinear and adaptive control of complex systems. Springer.
   Google Scholar
• Ge, S. S., Hang, C. C., Lee, T. H., & Zhang, T. (2001). Stable adaptive neural network control. Kluwer Academic.
   Google Scholar
• Goodwin, G. C., & Long, R. S. (1980). Generalization of results on multivariable adaptive control. IEEE Transactions on Automatic Control, 25(6), 1241–1245. https://doi.org/10.1109/TAC.1980.1102523
   Web of Science ®Google Scholar
• Goodwin, G. C., Ramadge, P. J., & Caines, P. E. (1980). Discrete-time multivariable adaptive control. IEEE Transactions on Automatic Control, 25(6), 449–456. https://doi.org/10.1109/TAC.1980.1102363
   Web of Science ®Google Scholar
• Goodwin, G. C., & Sin, K. S. (1984). Adaptive filtering prediction and control. Prentice-Hall.
   Google Scholar
• Isidori, A. (1995). Nonlinear control systems (3rd ed.). Springer-Verlag.
   Google Scholar
• Jiang, Z. P., & Praly, L. (1991). Iterative designs of adaptive controllers for systems with nonlinear integrators. In Proceedings of the 30th IEEE Conference on Decision and Control (pp. 2482–2487).
   Google Scholar
• Kanellakopoulos, I., Kokotović , P. V., & Morse, A. S. (1991). Systematic design of adaptive controllers for feedback linearizable systems. IEEE Transactions on Automatic Control, 36(11), 1241–1253. https://doi.org/10.1109/9.100933
   Web of Science ®Google Scholar
• Kokotović, P. V. (1991). Foundations of adaptive control. Springer-Verlag.
   Google Scholar
• Kokotović, P. V., & Arcak, M. (2001). Constructive nonlinear control: A historical perspective. Automatica, 37(5), 637–662. https://doi.org/10.1016/S0005-1098(01)00002-4
   Web of Science ®Google Scholar
• Kokotović, P. V., Kanellakopoulos, I., & Morse, A. S. (1991). Adaptive feedback linearization of nonlinear systems. In Foundations of adaptive control (pp. 309–346). Springer.
   Google Scholar
• Kokotović, P. V., & Kanellakopoulos, I. (1990). Adaptive nonlinear control: A critical appraisal. In Proceedings of the Sixth Yale Workshop on Adaptive and Learning Systems (pp. 1–6).
   Google Scholar
• Krstić, M., Kanellakopoulos, I., & Kokotović, P. V. (1992). Adaptive nonlinear control without overparametrization. Systems and Control Letters, 19(3), 177–185. https://doi.org/10.1016/0167-6911(92)90111-5
   Web of Science ®Google Scholar
• Krstić, M., Kanellakopoulos, I., & Kokotović, P. V. (1995). Nonlinear and adaptive control design. John Wiley and Sons.
   Google Scholar
• Landau, Y. D. (1979). Adaptive control: The model reference approaches. Marcel Dekker.
   Google Scholar
• Lewis, F. L., Campos, J., & Selmic, R. (2002). Frontiers in applied mathematics, neurofuzzy control of industrial systems with actuator nonlinearities. SIAM.
   Google Scholar
• Marino, R., & Tomei, P. (1995). Nonlinear control design: Geometric, adaptive and robust. Prentice-Hall.
   Google Scholar
• Monopoli, R. V., & Hsing, C. C. (1975). Parameter adaptive control of multivariable systems. International Journal of Control, 22(3), 313–327. https://doi.org/10.1080/00207177508922087
   Web of Science ®Google Scholar
• Morris, K. (1978). Mathematical thought from ancient to modern times. Oxford University Press.
   Google Scholar
• Mosca, E. (1995). Optimal, predictive, and adaptive control. Prentice-Hall.
   Google Scholar
• Nassiri-Toussi, K., & Ren, W. (1997). Indirect adaptive pole-placement control of MIMO stochastic systems: self-tuning results. IEEE Transactions on Automatic Control, 42(1), 38–52. https://doi.org/10.1109/9.553686
   Web of Science ®Google Scholar
• Sastry, S., & Isidori, A. (1989). Adaptive control of linearizable systems. IEEE Transactions on Automatic Control, 34(11), 1123–1131. https://doi.org/10.1109/9.40741
   Web of Science ®Google Scholar
• Seto, D., Annaswamy, A., & Baillieul, J. (1994). Adaptive control of nonlinear systems with a triangular structure. IEEE Transactions on Automatic Control, 39(7), 1411–1428. https://doi.org/10.1109/9.299624
   Web of Science ®Google Scholar
• Seto, D., & Baillieul, J. (1994). Control problems in super-articulated mechanical systems. IEEE Transactions on Automatic Control, 39(12), 2442–2453. https://doi.org/10.1109/9.362851
   Web of Science ®Google Scholar
• Spooner, J. T., Maggiore, M., Ordsqez, R., & Passino, K. M. (2002). Stable adaptive control and estimation for nonlinear systems: Neural and fuzzy approximator techniques. John Wiley and Sons.
   Google Scholar
• Tao, G. (2003). Adaptive control design and analysis. John Wiley and Sons.
   Google Scholar
• Tao, G. (2014). Multivariable adaptive control: A survey. Automatica, 50(11), 2737–2764. https://doi.org/10.1016/j.automatica.2014.10.015
   Web of Science ®Google Scholar
• Zhang, H. G., & Liu, D. R. (2006). Fuzzy modelling and fuzzy control. Birkhauser.
   Google Scholar
• Zhou, J., & Wen, C. (2008). Adaptive backstepping control of uncertain systems, nonsmooth nonlinerities, interactions or time-variations. Springer-Verlag.
   Google Scholar