Abedi, Fakhreddin; Hassan, Malik Abu; Suleiman, Mohammed Feedback stabilization and adaptive stabilization of stochastic nonlinear systems by the control Lyapunov function. (English) Zbl 1222.60039 Stochastics 83, No. 2, 179-201 (2011). Summary: Our aims of this paper are twofold: On one hand, we study the asymptotic stability in probability of stochastic differential system, when both the drift and diffusion terms are affine in the control. We derive sufficient conditions for the existence of control Lyapunov functions (CLFs) leading to the existence of stabilizing feedback laws which are smooth, except possibly at the equilibrium state. On the other hand, we consider the previous systems with an unknown constant parameters in the drift and introduce the concept of an adaptive CLF for stochastic system and use the stochastic version of Florchinger’s control law to design an adaptive controller. In this framework, the problem of adaptive stabilization of nonlinear stochastic system is reduced to the problem of non-adaptive stabilization of a modified system. Cited in 4 Documents MSC: 60H10 Stochastic ordinary differential equations (aspects of stochastic analysis) 93C10 Nonlinear systems in control theory 93D05 Lyapunov and other classical stabilities (Lagrange, Poisson, \(L^p, l^p\), etc.) in control theory 93D15 Stabilization of systems by feedback 93D21 Adaptive or robust stabilization 93E15 Stochastic stability in control theory Keywords:stochastic differential systems; control Lyapunov function; globally asymptotically stable in probability; feedback stabilization; adaptive stabilization PDF BibTeX XML Cite \textit{F. Abedi} et al., Stochastics 83, No. 2, 179--201 (2011; Zbl 1222.60039) Full Text: DOI Link References: [1] Abedi F., Int. J. Math. Anal. 5 pp 175– (2011) [2] DOI: 10.1016/0362-546X(83)90049-4 · Zbl 0525.93053 [3] DOI: 10.1109/9.940927 · Zbl 1008.93068 [4] DOI: 10.1080/07362999308809308 · Zbl 0770.60058 [5] DOI: 10.1137/S0363012993252309 · Zbl 0845.93085 [6] DOI: 10.1080/07362990008809675 · Zbl 1001.93087 [7] DOI: 10.1081/SAP-100002024 · Zbl 0997.93096 [8] DOI: 10.1081/SAP-120026106 · Zbl 1048.93094 [9] DOI: 10.1137/040618850 · Zbl 1124.34033 [10] DOI: 10.1016/0022-0396(78)90135-3 · Zbl 0417.93012 [11] Khasminskii R.Z., Stochastic Stability of Differential Equation (1980) [12] Kolmanovskii V.B., Differ. Uravn 31 pp 1851– (1995) [13] Krstic M., Stabilization of Uncertain Nonlinear Systems (1998) [14] DOI: 10.1016/0167-6911(94)00107-7 · Zbl 0877.93119 [15] DOI: 10.1016/0167-6911(92)90111-5 · Zbl 0763.93043 [16] DOI: 10.1137/0305015 · Zbl 0183.19401 [17] DOI: 10.1007/BFb0064937 [18] DOI: 10.2307/1969558 · Zbl 0038.25003 [19] DOI: 10.2307/1969955 · Zbl 0070.31003 [20] Rogers, L.C.G. and Williams, D. 1994.Diffusions, Markov Processes and Martingales, 2nd ed., 1New York: Wiley. · Zbl 0826.60002 [21] DOI: 10.1137/080744165 · Zbl 1235.34212 [22] DOI: 10.1016/0167-6911(89)90028-5 · Zbl 0684.93063 [23] DOI: 10.1137/0329025 · Zbl 0785.93080 [24] Wilson, F.W. 1966.Smoothing Derivatives of Functions and Applications, Tech. Report 66–3 413–428. Providence, RI: Brown University. · Zbl 0175.20203 [25] DOI: 10.1016/0022-0396(67)90035-6 · Zbl 0152.28701 This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.