<p>This research aims to advance the concept of fractional controllability with constraints in the context of fractional systems in the Caputo sense, where the output function is described by a fractional Riemann-Liouville derivative of order <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40435_2025_1654_Article_IEq1.gif" Format="GIF" Height="19" Rendition="HTML" Resolution="72" Type="Linedraw" Width="65" /> </InlineMediaObject> <EquationSource Format="TEX">\(\gamma \in [0,1]\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>γ</mi> <mo>∈</mo> <mo stretchy="false">[</mo> <mn>0</mn> <mo>,</mo> <mn>1</mn> <mo stretchy="false">]</mo> </mrow> </math></EquationSource> </InlineEquation>. Consequently, the objective is to characterize optimal control by two distinct methods, ensuring that the fractional Riemann-Liouville derivative of the final state remains between two prescribed functions <i>p</i>(.) and <i>q</i>(.). In particular, if <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40435_2025_1654_Article_IEq2.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="42" /> </InlineMediaObject> <EquationSource Format="TEX">\(\gamma = 0\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>γ</mi> <mo>=</mo> <mn>0</mn> </mrow> </math></EquationSource> </InlineEquation>, we obtain global enlarged controllability over the evolution domain. On the other hand, with <InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40435_2025_1654_Article_IEq3.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="42" /> </InlineMediaObject> <EquationSource Format="TEX">\(\gamma =1\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>γ</mi> <mo>=</mo> <mn>1</mn> </mrow> </math></EquationSource> </InlineEquation>, we obtain the enlarged controllability of the gradient of the output system. What’s more, when <InlineEquation ID="IEq4"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40435_2025_1654_Article_IEq4.gif" Format="GIF" Height="19" Rendition="HTML" Resolution="72" Type="Linedraw" Width="75" /> </InlineMediaObject> <EquationSource Format="TEX">\(p(.) = q(.)\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>p</mi> <mo stretchy="false">(</mo> <mo>.</mo> <mo stretchy="false">)</mo> <mo>=</mo> <mi>q</mi> <mo stretchy="false">(</mo> <mo>.</mo> <mo stretchy="false">)</mo> </mrow> </math></EquationSource> </InlineEquation>, we’re talking about exact controllability. The problem is approached in two ways: the first uses the Lagrangian method, and the second the subdifferential theory. To validate the theoretical results, we develop an Uzawa-type algorithm and demonstrate its application through numerical simulations.</p>

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Fractional enlarged controllability for a class of Caputo fractional time linear systems

  • Rachid Larhrissi,
  • Mustapha Benoudi

摘要

This research aims to advance the concept of fractional controllability with constraints in the context of fractional systems in the Caputo sense, where the output function is described by a fractional Riemann-Liouville derivative of order \(\gamma \in [0,1]\) γ [ 0 , 1 ] . Consequently, the objective is to characterize optimal control by two distinct methods, ensuring that the fractional Riemann-Liouville derivative of the final state remains between two prescribed functions p(.) and q(.). In particular, if \(\gamma = 0\) γ = 0 , we obtain global enlarged controllability over the evolution domain. On the other hand, with \(\gamma =1\) γ = 1 , we obtain the enlarged controllability of the gradient of the output system. What’s more, when \(p(.) = q(.)\) p ( . ) = q ( . ) , we’re talking about exact controllability. The problem is approached in two ways: the first uses the Lagrangian method, and the second the subdifferential theory. To validate the theoretical results, we develop an Uzawa-type algorithm and demonstrate its application through numerical simulations.