System Identification and Advanced Tracking Strategies for Linear and Nonlinear Control Systems
2019-12
Loading...
Persistent link to this item
Statistics
View StatisticsJournal Title
Journal ISSN
Volume Title
Title
System Identification and Advanced Tracking Strategies for Linear and Nonlinear Control Systems
Authors
Published Date
2019-12
Publisher
Type
Thesis or Dissertation
Abstract
The research in the master dissertation addresses development of an appropriate model of a dynamic system using observed data combined with basic mechanics and dynamics, prior knowledge of relationships between parameters.The main idea of system identification is studying the behavior of existing structures by recording the output or inputoutput in discrete time signals. The input-output description of a discrete-time system consists of a mathematical expression which explicitly defines the relation between the input and output signals. Further evaluating the key points for the model accuracy requirements to control estimate and predict according to the input. Also shedding light on different types of tools and techniques can be utilized to determine the dynamics of a system. Next, this research presents a new and computationally efficient online technique for infinite-horizon and finite-horizon for linear and nonlinear dynamical systems. This technique is based on change of variables that converts the nonlinear differential Riccati equation to a linear Lyapunov differential equation. During online implementation, the Lyapunov equation is solved in a closed form at any given time step. Further, an online technique is presented for finite-horizon nonlinear tracking problems. The idea of the proposed technique is to integrate the Kalman filter algorithm and the finitehorizon SDRE technique. Unlike the ordinary methods which deal with the linearized system, this technique estimates the unmeasured states of the nonlinear system directly by converting into SDC (state dependent coefficient)form for each time step, and this makes the proposed technique effective for a wide range of operating points. Further, the proposed infinite-horizon nonlinear technique is used to regulate the states of Mathieu equation, tracking of force damped pendulum system states and regulating the angle of an inverted pendulum on a cart pole system. Moreover, finite-horizon nonlinear tracking technique is used to regulate the ball position and gear angle of a ball and beam system and angle tracking of the flight dynamics and control of vertical lift-off vehicle system to demonstrate the effectiveness of the developed technique. Regulation and tracking of the its roll and pitch angles keeping the yaw constant are further presented to demonstrate the effectiveness of the developed technique
Keywords
Description
University of Minnesota M.S.E.E. thesis. December 2019. Major: Electrical/Computer Engineering. Advisor: Dr. Desineni Naidu. 1 computer file (PDF); viii, 65 pages + 2 supplemental files.
Related to
Replaces
License
Series/Report Number
Funding information
Isbn identifier
Doi identifier
Previously Published Citation
Other identifiers
Suggested citation
Hafeez`, Syed. (2019). System Identification and Advanced Tracking Strategies for Linear and Nonlinear Control Systems. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/213070.
Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.