This chapter presents a personal view on the development of identification theory in the
control community, starting from the year 1965. We show how two landmark papers,(Ho and …

In this brief, a cooperative control system with data-driven biointelligent controller is
proposed. First, the neuroendocrine ultrashort feedback controller (NUC) is adopted to …

We consider the problem of extracting safe environments and controllers for reach-avoid
objectives for systems with known state and control spaces, but unknown dynamics. In a …

Manufacturing equipment and scientific instruments, including wafer scanners, printers,
microscopes, and medical imaging scanners, require accurate and fast motions. Increasing …

This paper presents a probabilistic model validation methodology for nonlinear systems in
time-domain. The proposed formulation is simple, intuitive, and accounts both deterministic …

One method includes obtaining a preliminary model associated with a system to be
controlled and constructing a weighted model using one or more weighting factors. The …

This paper presents the author's personal view on the development of identification theory in
the control community, starting from the year 1965. We show how two landmark papers,(Ho …

Iterative Feedback Tuning is a purely data driven tuning algorithm for optimizing control
parameters based on closed loop data. The algorithm is designed to produce an unbiased …

This paper addresses robust deconvolution filtering when the system and noise dynamics
are obtained by parametric system identification. Consistent with standard identification …

Suppose an unknown plant is stabilized by a known controller. Suppose also that some
knowledge of the closed-loop system is available and on the basis of that knowledge, the …