<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">ICA</journal-id><journal-title-group><journal-title>Intelligent Control and Automation</journal-title></journal-title-group><issn pub-type="epub">2153-0653</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/ica.2013.41005</article-id><article-id pub-id-type="publisher-id">ICA-27703</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Computer Science&amp;Communications</subject></subj-group></article-categories><title-group><article-title>
 
 
  Optimal Control for Time-Delay Bilinear Systems with Sinusoidal Disturbances
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>exin</surname><given-names>Gao</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Min</surname><given-names>Wang</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Leilei</surname><given-names>Li</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib></contrib-group><aff id="aff1"><addr-line>College of Automation and Electronic engineer, Qingdao University of Science &amp;amp; Technology, Qingdao, China</addr-line></aff><author-notes><corresp id="cor1">* E-mail:<email>qdgaodexin@126.com(EG)</email>;</corresp></author-notes><pub-date pub-type="epub"><day>05</day><month>02</month><year>2013</year></pub-date><volume>04</volume><issue>01</issue><fpage>32</fpage><lpage>35</lpage><history><date date-type="received"><day>October</day>	<month>18,</month>	<year>2012</year></date><date date-type="rev-recd"><day>November</day>	<month>18,</month>	<year>2012</year>	</date><date date-type="accepted"><day>November</day>	<month>25,</month>	<year>2012</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
   This paper considers the optimal control problem for time-delay bilinear systems affected by sinusoidal disturbances with known frequency and measurable amplitude and phase. Firstly, using the differential homeomorphism, a time-delay bilinear system affected by sinusoidal disturbances is changed to a time-delay pseudo linear system through the coordinate transformation. Then the system with time-delay in control variable is transformed to a linear controllable system without delay using model transformation. At last based on the theory of linear quadratic optimal control, an optimal control law which is used to eliminate the influence of the disturbances is derived from a Riccati equation and Matrix equations. The simulation results show the effectiveness of the method. 
 
</p></abstract><kwd-group><kwd>Time-Delay Bilinear System; Feedback Linearization; Sinusoidal Disturbances; Optimal Control</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>Bilinear system is a class of systems that is derived by introducing the interactive product term of the state variable and the control variable in the linear state equations. It is a rather special nonlinear system, which exists widely in the engineering community of electric, mechanical, biological, chemical and other fields. The study of the bilinear system starts in the 50’s, then becomes an important branch of nonlinear system and made a series of research results. Fang proposed a method of research the stability of MIMO bilinear system [<xref ref-type="bibr" rid="scirp.27703-ref1">1</xref>]; the output-feedback control for bilinear system was studied by Sasaki [<xref ref-type="bibr" rid="scirp.27703-ref2">2</xref>]; a global feedback stability analysis method of bilinear system was presented by Jerbi [<xref ref-type="bibr" rid="scirp.27703-ref3">3</xref>]. In the real Industrial process control, time-delay is ubiquity and the mathematical models put forward from engineering technology, physical, chemical and biomedical had obvious delay amount, which can not be neglected in some accurate control systems. Tang had studied optimal disturbance rejection problem for time-delay system in recent years [<xref ref-type="bibr" rid="scirp.27703-ref4">4</xref>]. Meanwhile, various forms of external disturbances exist on the control system, such as sinusoidal disturbance, periodic perturbation, step disturbance, etc. So it has important actual meanings to study time-delay bilinear system affected by external disturbance [<xref ref-type="bibr" rid="scirp.27703-ref5">5</xref>].</p><p>This paper proposed an optimal control design method for time-delay bilinear systems affected by sinusoidal disturbances based on state-feedback linearization [6,7]. Based on the differential homeomorphism, the model of the system that is researched is changed to a time-delay pseudo linear system through the coordinate transition, then through delay-free transform, the time-delay pseudo linear system is converted to an easy pseudo linear system. At last, an optimal control law which is used to eliminate the influence of the disturbances is derived from a Riccati equation and Matrix equations [8,9]. It is shown that the method is easy to realize and has a good convergence.</p></sec><sec id="s2"><title>2. Problem Statement</title><p>Consider time-delay bilinear system affected by sinusoidal disturbances</p><disp-formula id="scirp.27703-formula115989"><label>(1)</label><graphic position="anchor" xlink:href="5-7900232\9fb8c315-6934-41c5-97bd-91a1c58db448.jpg"  xlink:type="simple"/></disp-formula><p>where, <img src="5-7900232\46f81297-881b-481d-942a-243fd6fd6090.jpg" />is the state vector; <img src="5-7900232\543ab032-ab33-4526-b315-8a4bc31a0bea.jpg" />is the control vector; <img src="5-7900232\b6b14a10-484a-4b33-8488-e0803b645a8f.jpg" />is the external disturbances vector; <img src="5-7900232\76ab190d-3774-46ed-9a5d-df0e48c20fd8.jpg" />is the output vector; A, B, D, N<sub>j</sub> are scalar matrixes of appropriate dimensions; x<sub>j</sub> is the j-th component of state vector; <img src="5-7900232\81fe5a36-fabf-45c4-8e58-4fe251d050a0.jpg" />is the bilinear term; <img src="5-7900232\e7386837-8792-4e67-8373-d96fe3ab3b22.jpg" />is the scalar function of x.</p><p>Assumption 1 The external disturbances can be expressed as</p><disp-formula id="scirp.27703-formula115990"><label>(2)</label><graphic position="anchor" xlink:href="5-7900232\19378205-1445-42ba-9d5d-5643ba91929d.jpg"  xlink:type="simple"/></disp-formula><p>which is an m-dimensional sinusoidal vector with known frequencies<img src="5-7900232\71ebf842-c8a1-46e1-a022-dfca3115f572.jpg" />, amplitudes <img src="5-7900232\c5122faf-1d7d-4c75-bacd-9adb1f8b5b55.jpg" /> and phases <img src="5-7900232\901915aa-0e62-4387-8038-483dc56b64dd.jpg" /> are measurable. By transformation, time-delay bilinear system could be changed as</p><disp-formula id="scirp.27703-formula115991"><label>(3)</label><graphic position="anchor" xlink:href="5-7900232\00931d4e-2e9f-4da6-ac19-1c0c508c6b93.jpg"  xlink:type="simple"/></disp-formula><p>Change the bilinear system to the general expression of nonlinear system</p><disp-formula id="scirp.27703-formula115992"><label>(4)</label><graphic position="anchor" xlink:href="5-7900232\2c88ed95-f6a6-4829-bcd6-607551e0f0a7.jpg"  xlink:type="simple"/></disp-formula><p>where, <img src="5-7900232\5e739905-2e1c-4774-9f79-98281e4595e9.jpg" />,<img src="5-7900232\8bf9c49b-ccb9-47c0-9153-085882cc4c69.jpg" /> and j, g are continuously differentiable functions.</p><p>Assumption 2 The relation degree of the nonlinear system is r, that is</p><disp-formula id="scirp.27703-formula115993"><label>(5)</label><graphic position="anchor" xlink:href="5-7900232\06fca6d4-1f80-451b-93a3-3bc40e556656.jpg"  xlink:type="simple"/></disp-formula><p>Through exact delay-free transformation, the nonlinear system (4) can be converted to an easy pseudo linear system (6)&#160;&#160;&#160;</p><disp-formula id="scirp.27703-formula115994"><label>(6)</label><graphic position="anchor" xlink:href="5-7900232\179f9981-c074-4057-b4f2-9bc42330907e.jpg"  xlink:type="simple"/></disp-formula><p><img src="5-7900232\77fc9b1d-7438-4118-b0d8-1588bbec9e42.jpg" />is the new state vector.</p><p><img src="5-7900232\4ee467f3-820f-490d-92ab-02bfdd5f22ed.jpg" />&#160; <img src="5-7900232\4d525939-f705-45b4-b548-f31e164b18a2.jpg" />&#160; <img src="5-7900232\a6cf2dc4-f1d1-4536-b3fb-1bfd375cd1b3.jpg" /></p><p>Then based on the theory of linear quadratic optimal control, an optimal control law which is used to eliminate the influence of the disturbances is derived.</p></sec><sec id="s3"><title>3. Exact Delay-Free Linearization</title><sec id="s3_1"><title>3.1. State Feedback Linearization</title><p>State Feedback Linearization is a method of nonlinear controlling design, the design idea of which is to select a coordinate transformation <img src="5-7900232\b0c6c96f-60e5-4263-b5fd-f5b065278b29.jpg" /> and made a mapping from x coordinate space to z coordinate space, thus the nonlinear system is changed to a linear time-invariant system as<img src="5-7900232\49fe3522-c6a8-4257-bbe3-c3cabcf3c2c8.jpg" />. Let</p><disp-formula id="scirp.27703-formula115995"><label>(7)</label><graphic position="anchor" xlink:href="5-7900232\bf3471a7-d046-422b-a29f-7beefeb5b101.jpg"  xlink:type="simple"/></disp-formula><p><img src="5-7900232\a465caea-b51b-4245-9cad-e2fd52e4ce1e.jpg" />is the partial differential homeomorphism, according to assumption 2, then get</p><disp-formula id="scirp.27703-formula115996"><label>(8)</label><graphic position="anchor" xlink:href="5-7900232\355ffedd-2c3c-4c0a-86d7-71a1b5473670.jpg"  xlink:type="simple"/></disp-formula><p>by operation, the system is changed to a new standard form</p><disp-formula id="scirp.27703-formula115997"><label>(9)</label><graphic position="anchor" xlink:href="5-7900232\525e5fa9-6d0f-4b6a-bde2-d3d8381a6344.jpg"  xlink:type="simple"/></disp-formula><p>r-step time-delay linear system with disturbances can be obtained as follow</p><disp-formula id="scirp.27703-formula115998"><label>(10)</label><graphic position="anchor" xlink:href="5-7900232\af79a6c3-49c4-47e5-b478-1a4badb87a49.jpg"  xlink:type="simple"/></disp-formula><p>where</p><p><img src="5-7900232\19e73236-9649-4253-9b34-d5774287329f.jpg" /></p><p><img src="5-7900232\ff71b6a3-6815-41b7-bee6-7239f183cb2c.jpg" />&#160; <img src="5-7900232\8eaec983-4936-4535-909b-51597d4572e7.jpg" />&#160; <img src="5-7900232\e21a8a53-f148-4ebd-bd7f-f59bad936500.jpg" /></p></sec><sec id="s3_2"><title>3.2. Exact Delay-Free Transformation</title><p>Definite transformation for the time-delay linear system, let</p><disp-formula id="scirp.27703-formula115999"><label>(11)</label><graphic position="anchor" xlink:href="5-7900232\e8b7c1ed-8df3-43f9-8b68-519983127f07.jpg"  xlink:type="simple"/></disp-formula><p>The expression (10) is converted to delay-free system</p><disp-formula id="scirp.27703-formula116000"><label>(12)</label><graphic position="anchor" xlink:href="5-7900232\026881d7-5ec5-41f5-afbd-479922e2fb60.jpg"  xlink:type="simple"/></disp-formula><p>where<img src="5-7900232\bdce771b-d28e-4a92-a2b7-4f9c3c7fbcfd.jpg" />.</p></sec></sec><sec id="s4"><title>4. Design of Optimal Control</title><p>The time-delay bilinear system (1) is changed to the equivalent delay-free linear system affected by disturbances</p><disp-formula id="scirp.27703-formula116001"><label>(13)</label><graphic position="anchor" xlink:href="5-7900232\365436c4-ec37-48e8-985e-b88d63d29028.jpg"  xlink:type="simple"/></disp-formula><p>where, <img src="5-7900232\2b1ba0a5-91fb-459b-9ed4-5604fa852a6e.jpg" />is the new state vector; <img src="5-7900232\41681d6f-7b88-4899-a058-88872b3fcf5e.jpg" />is the new control vector; A is state coefficient matrix; B is control coefficient matrix; the system (6) is completely controllable.</p><p>When <img src="5-7900232\a4464f57-553d-4214-9d91-9b40814570d7.jpg" /> select the quadratic performance index of system (6) as</p><disp-formula id="scirp.27703-formula116002"><label>(14)</label><graphic position="anchor" xlink:href="5-7900232\9fa4ab27-a93e-430f-b1dc-91936e4e14f7.jpg"  xlink:type="simple"/></disp-formula><p>where Q is a <img src="5-7900232\109ce608-560a-4db6-8f52-633230ea3664.jpg" /> positive semi-definite matrix, R is a <img src="5-7900232\89fa394a-f1b6-408e-8549-0ac135d8bc4d.jpg" /> positive definite symmetric matrix.</p><p>Theorem: Consider the optimal control problem of system (6) with the quadratic performance index (14). Suppose the system is completely controllable and observable, the optimal disturbance rejection control law is unique existence and can be expressed as</p><disp-formula id="scirp.27703-formula116003"><label>(15)</label><graphic position="anchor" xlink:href="5-7900232\cda2407e-2a4f-4058-8649-f03d0b438cfb.jpg"  xlink:type="simple"/></disp-formula><p>P is the unique positive definite solution of the matrix Equation (16)</p><disp-formula id="scirp.27703-formula116004"><label>(16)</label><graphic position="anchor" xlink:href="5-7900232\93dbb976-965e-4628-b5cd-801dd3422d3b.jpg"  xlink:type="simple"/></disp-formula><p>P<sub>1</sub> is the unique solution of the matrix Equation (17)</p><disp-formula id="scirp.27703-formula116005"><label>(17)</label><graphic position="anchor" xlink:href="5-7900232\4411c27d-62bd-4c95-8d2f-db38d1672009.jpg"  xlink:type="simple"/></disp-formula><p>P<sub>2</sub> is the unique solution of the matrix Equation (18)</p><disp-formula id="scirp.27703-formula116006"><label>(18)</label><graphic position="anchor" xlink:href="5-7900232\afcc2c67-b340-4580-bdef-d44712fe4d3e.jpg"  xlink:type="simple"/></disp-formula><p>where</p><p><img src="5-7900232\be7861f9-4d36-4fe9-8ff3-1a5efbccdb63.jpg" /></p><p><img src="5-7900232\f65ce571-3d4d-410f-a6c0-cf1fb479c92f.jpg" /></p><p><img src="5-7900232\6695d931-4bc1-4a6e-96d3-f142d7d78a62.jpg" /></p><p>Proof: According to the necessary conditions of the optimal control problem based on maximum principle, the optimal control law of system (6) with the quadratic performance index (14) can be expressed as</p><disp-formula id="scirp.27703-formula116007"><label>(19)</label><graphic position="anchor" xlink:href="5-7900232\5c209144-0cc9-4a14-b365-6f352ca82893.jpg"  xlink:type="simple"/></disp-formula><p>where <img src="5-7900232\abdf59ca-c655-46a4-8807-79971bffd12e.jpg" /> is the solution of the following two-point boundary value problem</p><disp-formula id="scirp.27703-formula116008"><label>(20)</label><graphic position="anchor" xlink:href="5-7900232\06028554-d816-4055-be3f-3197871f0d11.jpg"  xlink:type="simple"/></disp-formula><p>In order to obtain the solution to the problem in (14), let</p><disp-formula id="scirp.27703-formula116009"><label>(21)</label><graphic position="anchor" xlink:href="5-7900232\dd092691-a948-4294-b841-cfea3de6f4c0.jpg"  xlink:type="simple"/></disp-formula><p>where<img src="5-7900232\553a8495-8b70-450e-996b-46e7be754b61.jpg" />, <img src="5-7900232\cd51a69a-fa37-4b5e-bcf3-972071aa5605.jpg" />are both undetermined matrix.</p><p>From expression (2), the vector function <img src="5-7900232\e714de9f-f44c-4bb2-a1d6-1aedbac06683.jpg" /> satisfies the following vector differential equation</p><disp-formula id="scirp.27703-formula116010"><label>(22)</label><graphic position="anchor" xlink:href="5-7900232\180df14b-755e-4f3b-bbcb-26da89ee30e9.jpg"  xlink:type="simple"/></disp-formula><p>Taking the derivatives to the sides in (21) and substituting (22) into it get (23)</p><disp-formula id="scirp.27703-formula116011"><label>(23)</label><graphic position="anchor" xlink:href="5-7900232\152747db-b097-442c-b080-1e43d5b98a6a.jpg"  xlink:type="simple"/></disp-formula><p>Add (23) into the first expression of (20), obtain (24)</p><disp-formula id="scirp.27703-formula116012"><label>(24)</label><graphic position="anchor" xlink:href="5-7900232\ef11ce4e-f804-4b70-a13e-eea7c07d8c59.jpg"  xlink:type="simple"/></disp-formula><p>Considering for any <img src="5-7900232\09d42700-27f7-4aef-bd20-199b49328413.jpg" /> and<img src="5-7900232\9554633d-1f28-41cc-9dd1-95a70c272552.jpg" />, Equation (24) is all hold, so we can get matrix Equations (16)-(18). The optimal control law of the bilinear systems affected by sinusoidal disturbances is as follow</p><disp-formula id="scirp.27703-formula116013"><label>(25)</label><graphic position="anchor" xlink:href="5-7900232\317f2afa-80a0-426e-bc1e-3356cfd24798.jpg"  xlink:type="simple"/></disp-formula></sec><sec id="s5"><title>5. Simulation Example</title><p>Consider a time-delay bilinear system with sinusoidal disturbances, system parameters as follows</p><disp-formula id="scirp.27703-formula116014"><label>(26)</label><graphic position="anchor" xlink:href="5-7900232\ffdf11cd-8559-44f0-8cc7-37e41e1a0db5.jpg"  xlink:type="simple"/></disp-formula><p><img src="5-7900232\f1d0c1ea-25eb-481b-b88f-a8f50a4b8163.jpg" /></p><p>According to calculation<img src="5-7900232\fc0ccd58-520e-44f8-9b76-675870a7e516.jpg" />, through local linearization, we can get a two-step linear system affected by sinusoidal disturbances</p><disp-formula id="scirp.27703-formula116015"><label>(27)</label><graphic position="anchor" xlink:href="5-7900232\0749fa3a-6513-44de-91c0-cdc88d8d201a.jpg"  xlink:type="simple"/></disp-formula><p>where</p><p><img src="5-7900232\4eeaff31-acec-4f54-b5b1-52d70fb5c406.jpg" /></p><p>The form of the disturbances described as follows</p><disp-formula id="scirp.27703-formula116016"><label>(28)</label><graphic position="anchor" xlink:href="5-7900232\831e7c9e-717a-42fe-a559-0f2515bbeae6.jpg"  xlink:type="simple"/></disp-formula><p>Using model transformation, change the system with time-delay to a linear controllable system without delay</p><disp-formula id="scirp.27703-formula116017"><label>(29)</label><graphic position="anchor" xlink:href="5-7900232\e0e5da51-7a63-4818-9397-391e9a04cea5.jpg"  xlink:type="simple"/></disp-formula><p>where<img src="5-7900232\aec58981-e365-4568-bf8e-55527ec630e4.jpg" />,<img src="5-7900232\7e57ddb0-0b5f-4fea-b451-0c5e4ef55ff6.jpg" />.</p><p>Select<img src="5-7900232\134c8dcb-ae67-4aaf-841b-97cb08934753.jpg" />, <img src="5-7900232\9d27e518-fdc9-49ec-a190-e17eb076c3f7.jpg" />, we get</p><p><img src="5-7900232\16126353-4777-4b34-ad19-ce3abc616e63.jpg" /></p><p>The simulation results of<img src="5-7900232\e78e20ab-088d-48ca-bebb-6aa8c4382639.jpg" />, <img src="5-7900232\7cf1a7aa-06f3-4aaa-b14f-35061cebf7b3.jpg" />and <img src="5-7900232\21be746f-c984-4377-b50a-1a5af4e9e84e.jpg" /> are presented in Figures 1 and 2.</p><p>It is shown that the optimal control design method for the system affected by sinusoidal disturbances based on state-feedback linearization is easily realized, and has a good convergence through the simulation results.</p></sec><sec id="s6"><title>6. Conclusion</title><p>This paper concentrates on the solution of the optimal control problem for time-delay bilinear system affected by sinusoidal disturbances with known frequency and measurable amplitude and phase based on state feedback, a method of optimal control law is given. Simulation re-</p><p>sults show that the designed control law is accurate and easy to implement.</p></sec><sec id="s7"><title>REFERENCES</title></sec><sec id="s8"><title>NOTES</title></sec></body><back><ref-list><title>References</title><ref id="scirp.27703-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">Y. W. Fang, L. C. Jiao and Z. Z. Han, “The New Method of Stability of MIMO Bilinear System,” Journal of Automation, Vol. 27, No. 6, 2001, pp. 845-849.</mixed-citation></ref><ref id="scirp.27703-ref2"><label>2</label><mixed-citation publication-type="other" xlink:type="simple">S. Sasaki and K. Uchida, “Quadratic Cost Output Feedback Control for Bilinear Systems,” International Journal of Systems Science, Vol. 34, No. 5, 2003, pp. 345-355.  
doi:10.1080/00207720310001600984</mixed-citation></ref><ref id="scirp.27703-ref3"><label>3</label><mixed-citation publication-type="other" xlink:type="simple">H. Jerbi, “Global Feedback Stabilization of New Class of Bilinear Systems,” Systems and Control Letters, Vol. 42, No. 4, 2001, pp. 313-320.  
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