Model predictive control of nonlinear processes using transfer learning-based recurrent neural networks
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Alhajeri, Mohammed S.↗
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Sparse-identification-based model predictive control of nonlinear two-time-scale processes
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Abdullah, Fahim (ORCID:000000025094788X)↗
Model predictive control of nonlinear processes using neural ordinary differential equation models
Not Available
Luo, Junwei (ORCID:000900072609629X)↗
Dynamic Nonlinear Droop Control (DNDC): A Novel Primary Control Method for DC Microgrids
Not provided.
Engineering↗
Transfer learning of Gaussian processes to capture unmodeled physics: application to control of nonlinear dynamical systems.
Abstract not provided.
Swansen, Erin↗
Time-parallel optimal control of nonlinear dynamical systems
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Ridzal, Denis [Sandia National Laboratories (SNL-N↗
Dissipativity in the large of a three- dimensional nonautonomous nonlinear automatic control system
Dissipativity of phase trajectories for automatic control system
AUTOPILOT↗
A Transformation Approach to Optimal Control Problems with Bounded State Variables
A technique is described and utilized in the study of the solutions to various general problems in optimal control theory, which are converted in to Lagrange problems in the calculus of variations. This is accomplished by mapping certain properties in Euclidean space onto closed control and state regions. Nonlinear control problems with a unit m cube as control region and unit n cube as state region are considered.
Hanafy, Lawrence Hanafy↗
Functional inclusion and controllability of nonlinear neutral functional differential systems
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Chukwu, E. N.↗
Nonlinear natural control of an experimental beam
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Meirovitch, L.↗
Synthesis of system responses: A nonlinear multivariable control design approach
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Peczkowski, J. L.↗
Solution of nonlinear optimal control problems using the algebraic tensor: An example
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Hill, J. P.↗
The computer implementation of the tensor solution to the nonlinear optimal control problem
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Osullivan, J. A.↗
Nonlinear optimal control with tensors: Some computational issues
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Osullivan, J. A.↗
A canonical form for nonlinear systems
The concepts of transformation and canonical form have been used in analyzing linear systems. These ideas are extended to nonlinear systems. A coordinate system and a corresponding canonical form are developed for general nonlinear control systems. Their usefulness is demonstrated by showing that every feedback linearizable system becomes a system with only feedback paths in the canonical form. For control design involving a nonlinear system, one approach is to put the system in its canonical form and approximate by that part having only feedback paths.
Su, R.↗