2015
DOI: 10.4236/ica.2015.62011
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Constrained Feedback Stabilization for Bilinear Parabolic Systems

Abstract: In this paper, we shall study the stabilization and the robustness of a constrained feedback control for bilinear parabolic systems defined on a Hilbert state space. Then, we shall show that stabilizing such a system reduces stabilization only in its projection on a suitable subspace. For this purpose, a new constrained stabilizing feedback control that allows a polynomial decay estimate of the stabilized state is given. Also, the robustness of the considered control is discussed. An illustrating example and s… Show more

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Cited by 3 publications
(4 citation statements)
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“…This article presents the control design of a non-minimum phase bilinear control system containing a disturbance function. The main difference with previous studies in [12]- [14], [16], [18] is in terms of the presence of a disturbance function in the system and the type of system and in [15], [34]- [36] is in terms of the use of the control design method used. The method used in this article is the backstepping method, which develops the previous results in [37].…”
Section: Introductionmentioning
confidence: 94%
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“…This article presents the control design of a non-minimum phase bilinear control system containing a disturbance function. The main difference with previous studies in [12]- [14], [16], [18] is in terms of the presence of a disturbance function in the system and the type of system and in [15], [34]- [36] is in terms of the use of the control design method used. The method used in this article is the backstepping method, which develops the previous results in [37].…”
Section: Introductionmentioning
confidence: 94%
“…Because max(𝑑) > 𝑑(𝑑) then sign(𝑀)𝑑(𝑑) βˆ’ max (𝑑) < 0 and 𝑉 Μ‡2(𝑑) < 0 apply to every 𝑑 β‰₯ 0. Furthermore, the variable control 𝜈(𝑑) is obtained from (15) and using the relation between the state variables {𝑒 1 (𝑑) , 𝑒 2 (𝑑) , 𝑀(𝑑)} in (12), the following control function is obtained (18).…”
Section: Control Design For the System With Exact Linearisationmentioning
confidence: 99%
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