Deep Neural Networks With Koopman Operators for Modeling and Control of Autonomous Vehicles

Modeling and Intelligent Control System Design for Overtaking Maneuver in Autonomous Vehicles

The purpose of this study is to design an intelligent control system to guide the overtaking maneuver with a higher performance than the existing systems. Unlike the existing models which consider constant values for some of the effective variables of this behavior, in this paper, a neural network model is designed based on the real overtaking data using instantaneous values for variables. A fu...

Neural Control System for Autonomous Vehicles

Neural networks have been used in a number of robotic applications (Das & Kar, 2006; Fierro & Lewis, 1998), including both manipulators and mobile robots. A typical approach is to use neural networks for nonlinear system modelling, including for instance the learning of forward and inverse models of a plant, noise cancellation, and other forms of nonlinear control (Fierro & Lewis, 1998). An alt...

Modeling and Control of Gas Turbine Combustor with Dynamic and Adaptive Neural Networks (TECHNICAL NOTE)

Learning Deep Neural Network Representations for Koopman Operators of Nonlinear Dynamical Systems

The Koopman operator has recently garnered much attention for its value in dynamical systems analysis and data-driven model discovery. However, its application has been hindered by the computational complexity of extended dynamic mode decomposition; this requires a combinatorially large basis set to adequately describe many nonlinear systems of interest, e.g. cyber-physical infrastructure syste...

Model-Based Control Using Koopman Operators

This paper explores the application of Koopman operator theory to the control of robotic systems. The operator is introduced as a method to generate data-driven models that have utility for model-based control methods. We then motivate the use of the Koopman operator towards augmenting modelbased control. Specifically, we illustrate how the operator can be used to obtain a linearizable data-dri...