کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4944246 1437982 2017 45 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Observer-Based adaptive neural network controller for uncertain nonlinear systems with unknown control directions subject to input time delay and saturation
ترجمه فارسی عنوان
کنترل کننده شبکه عصبی تطبیقی ​​مبتنی بر مشاهدات برای سیستم های غیر خطی نامشخص با جهات کنترل ناشناخته با توجه به تاخیر زمان ورودی و اشباع
کلمات کلیدی
شبکه عصبی انعطاف پذیر، کنترل سطح دینامیک، تاخیر ورودی، اشباع ورودی، ناظر شبکه عصبی، جهت کنترل ناشناخته،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی
This paper addresses the design of an observer based adaptive neural controller for a class of strict-feedback nonlinear uncertain systems subject to input delay, saturation and unknown direction. The input delay has been handled using an integral compensator term in the controller design. A neural network observer has been developed to estimate the unmeasured states. In the observer design, the Lipschitz condition has been relaxed. To solve the problem of unknown control directions, the Nussbaum gain function has been applied in the backstepping controller design. “The explosion of complexity” occurred in the traditional backstepping technique has been avoided utilizing the dynamic surface control (DSC) technique and the designed controller is singularity free. It has been shown that all closed-loop signals are semi-globally uniformly ultimately bounded (SGUUB) and the output tracking error converges to a small neighborhood of the origin by choosing the design parameters appropriately. The numerical examples illustrate the effectiveness of the proposed control scheme.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Sciences - Volumes 418–419, December 2017, Pages 717-737
نویسندگان
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