Accession Number : ADA257595


Title :   Identification and Control of Non-Linear Time-Varying Dynamical Systems Using Artificial Neural Networks


Descriptive Note : Doctoral thesis


Corporate Author : NAVAL POSTGRADUATE SCHOOL MONTEREY CA


Personal Author(s) : Dror, Shahar


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a257595.pdf


Report Date : Sep 1992


Pagination or Media Count : 285


Abstract : Identification and control of non-linear dynamical systems is a very complex task which requires new methods of approaching. This research addresses the problem of emulation and control via the use of distributed parallel processing, namely artificial neural networks. Four models for describing non- linear MIMO dynamical system are presented. Based on these models a combined feedforward and recurrent neural networks are structured to emulate the dynamical system. Further, a procedure to emulate multiple systems in a single network is suggested. A method for finding a minimal realization of a network is introduced. The minimization greatly reduces the complexity of the network without degrading the operating performance of the network. This work also examines the application of artificial neural networks for adaptive control. The multiple-system approach is used to find an adaptive neural network controller for non-linear MIMO time-varying system in a direct model reference control scheme. The controller network is trained using a procedure called bock- propagation through the plant, which was extended in this work. The application of neural networks is demonstrated on a longitudinal model of the F/A-18A fighter aircraft both with the undamaged aircraft and with a the mechanism as a time-varying MIMO dynamical system. Neural networks, Identification, Adaptive control, Non-Linear systems, Tim-Varying dynamical systems.


Descriptors :   *FIGHTER AIRCRAFT , *NEURAL NETS , *FLIGHT CONTROL SYSTEMS , *PARALLEL PROCESSING , *ADAPTIVE CONTROL SYSTEMS , LINEAR SYSTEMS , NETWORKS , IDENTIFICATION , APPROACH , WORK , TIME , PROCESSING , MODELS , AIRCRAFT , PROPAGATION , CONTROL


Subject Categories : Flight Control and Instrumentation
      Cybernetics


Distribution Statement : APPROVED FOR PUBLIC RELEASE