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    IMPROVED ROBUST ADAPTIVE CONTROL OF HIGH-ORDER NONLINEAR SYSTEMS WITH GUARANTEED PERFORMANCE

    IMPROVED ROBUST ADAPTIVE CONTROL OF HIGH-ORDER NONLINEAR SYSTEMS WITH GUARANTEED PERFORMANCE. Masters thesis, King Fahd University of Petroleum and Minerals.

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    Arabic Abstract

    فى هذة الأطروحة البحثية سيتم استعراض نوعين جديدين من التحكم وهما المتحكم المتأقلم (ل1) مع المتحكم الحائم و متحكم التأقلم ذات نموذج الأشارة مع دالة الأداء المحدد. يمتاز المتحكم المتأقلم (ل1) بوجود مرشح منخفض المرورية مع ثابت يحدد قيمة الدورة المغلقة. المفاضلة بين الأداء ومعدل ثبات المتحكم عنصر أساسى فى تحديد قيم المرشح. فى هذا العمل سيتم استعراض المتحكم المتأقلم (ل1) فى وجود حائم ليحدد ضبط عناصر المرشح. المتحكم الحائم سوف يضبط عن طريق الجزيئات الحائمة المثلى. ثانيا سوف يتم عرض متحكم متأقلم جديد لنظام ذات عدة مداخل و عدة مخارج مع متحكم التأقلم ذات نموذج الأشارة باستخدام دالة الأداء المحددة. فى هذا العمل يفترض ان يبدأ الخطأ بين الخرج الحقيقى والخرج المرجعى من قيمة كبيرة ثم يقل تدريجيا حتى ينحصر داخل حدود صغيرة محددة مسبقا. ثبات الأستقرا وضمان التحول سيوضح. فى الأخير أمثلة توضيحية لتأكيد ثبات وأستقرار وبساطة كل نوع حيث سيتم عرضهم فى سياق متصل.

    English Abstract

    This thesis presents fuzzy-L1 adaptive controller and Model Reference Adaptive Control (MRAC) with Prescribed Performance Function (PPF) as two adaptive approaches for high nonlinear systems as two original contribution to the literature. Firstly, L1 adaptive controller has a structure that allows decoupling between robustness and adaption owing to the use of a low pass filter with adjustable gain in the feedback loop. The trade-off between performance and robustness is a key factor in the tuning of the filter’s parameters. In fuzzy-L1 adaptive controller, we consider the class of strictly proper low pass filters with fixed structure but with the feedback gain as the only tunable parameter. A practical new fuzzy based approach for the tuning of the feedback filter of L1 adaptive controller is proposed. The fuzzy controller is optimally tuned using Particle Swarm Optimization (PSO) to minimize the tracking error and the control signal range. The main function of the fuzzy logic controller is the on-line tuning of the feedback gain of the filter. Secondly, an adaptive control of multi-input multi-output uncertain high-order nonlinear system capable of guaranteeing a predetermined prescribed performance is presented as MRAC with PPF. In this work, prescribed performance is defined in terms of the tracking error converging to a smaller residual set at a rate no less than a predefined value and exhibiting a maximum overshoot/undershoot less than a sufficiently small fixed constant. The key step in such approach is to transform the constrained system into an equivalent unconstrained one through an adequate transformation of the output error. This will show that the robust stabilization of the transformed error, guaranties the stability and convergence of the constrained tracking error within the set of time varying constraints representing the performance limits. Finally, simulations are presented to illustrate the simplicity, the performance and the robustness of each new technique.

    Item Type: Thesis (Masters)
    Subjects: Computer
    Systems
    Engineering
    Aerospace
    Department: College of Computing and Mathematics > lndustrial and Systems Engineering
    Committee Advisor: El-Ferik, Sami
    Committee Members: Abido, MUhammed and Elshafei, Moustafa
    Depositing User: HASHIM ABDELLAH HASHIM MOHAM (g201207380)
    Date Deposited: 14 Jan 2015 11:02
    Last Modified: 01 Nov 2019 15:44
    URI: http://eprints.kfupm.edu.sa/id/eprint/139427

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