"Optimal control of nonlinear systems is in fact difficult since it requires the solution to the Hamilton-Jacobi-Bellman (HJB) equation which has no closed-form solution. In contrast to offline and/or online iterative schemes for optimal control, this dissertation in the form of five papers focuses on the design of iteration free, online optimal adaptive controllers for nonlinear discrete and continuous-time systems whose dynamics are completely or partially unknown even when the states not measurable. Thus, in Paper I, motivated by homogeneous charge compression ignition (HCCI) engine dynamics, a neural network-based infinite horizon robust optimal controller is introduced for uncertain nonaffine nonlinear discrete-time systems. First, the nonaffine system is transformed into an affine-like representation while the resulting higher order terms are mitigated by using a robust term. The optimal adaptive controller for the affinelike system solves HJB equation and identifies the system dynamics provided a target set point is given. Since it is difficult to define the set point a priori in Paper II, an extremum seeking control loop is designed while maximizing an uncertain output function. On the other hand, Paper III focuses on the infinite horizon online optimal tracking control of known nonlinear continuous-time systems in strict feedback form by using state and output feedback by relaxing the initial admissible controller requirement. Paper IV applies the optimal controller from Paper III to an underactuated helicopter attitude and position tracking problem. In Paper V, the optimal control of nonlinear continuous-time systems in strict feedback form from Paper III is revisited by using state and output feedback when the internal dynamics are unknown. Closed-loop stability is demonstrated for all the controller designs developed in this dissertation by using Lyapunov analysis"--Abstract, page iv.
Sarangapani, Jagannathan, 1965-
Balakrishnan, S. N.
Erickson, Kelvin T.
Drallmeier, J. A.
Dagli, Cihan H., 1949-
Electrical and Computer Engineering
Ph. D. in Electrical Engineering
Missouri University of Science and Technology. Intelligent Systems Center
National Science Foundation (U.S.)
Missouri University of Science and Technology
Journal article titles appearing in thesis/dissertation
- Robust optimal control of uncertain nonaffine multi-input and multi-output nonlinear discrete systems with application to HCCI engines
- Discrete-time extremum seeking method coupled with optimal adaptive controller for nonlinear discrete time systems with application to efficiency optimization of HCCI engines
- Adaptive neural network-based optimal control of nonlinear continuous-time system in strict feedback form
- Neural network-based optimal adaptive output feedback control of a helicopter UAV
- Optimal adaptive control of nonlinear continuous-time systems in strictfeedback form with unknown internal dynamics
xiii, 244 pages
© 2012 Hassan Zargarzadeh, All rights reserved.
Dissertation - Open Access
Library of Congress Subject Headings
Internal combustion engines -- Ignition
Neural networks (Computer science)
Print OCLC #
Electronic OCLC #
Link to Catalog Recordhttp://laurel.lso.missouri.edu/record=b9639120~S5
Zargarzadeh, Hassan, "Lyapunov based optimal control of a class of nonlinear systems" (2012). Doctoral Dissertations. 1976.