To effectively control complex dynamical systems, accurate nonlinear models are typically
needed. However, these models are not always known. In this paper, we present a data …

Applications that require multirobot systems to operate independently for extended periods
of time in unknown or unstructured environments face a broad set of challenges, such as …

This paper presents a data-driven method for designing optimal controllers and robust
controllers for unknown nonlinear systems. Mathematical models for the realization of the …

As the Chinese proverb says,“when you drink water, think of its source”. I cannot finish this
PhD dissertation without all the help from many individuals along the way. Firstly, I would …

This paper solves nonlinear optimal control problems for a class of Gaussian kernel-based
nonlinear systems. The optimal control problems reduce to solving the Hamilton-Jacobi …

Recently, control theory using machine learning, which is useful for the control of unknown
systems, has attracted significant attention. This study focuses on such a topic with optimal …