This paper provides an overview of singular perturbations in control theory, focusing on their application to model order reduction and the separation of time scales in control system design. The authors discuss the conceptual and computational simplifications that result from these techniques, which are particularly useful for high-dimensional systems where the "curse of dimensionality" poses significant challenges. The paper covers various aspects of singular perturbations, including initial and boundary value problems, stability and stabilizability, optimal regulators, trajectory optimization, filtering and smoothing, and applications to cheap control and singular arcs. It also explores the extension of these methods to distributed parameter systems and time-delay systems. The content is presented in a tutorial form, making it accessible to engineers and applied mathematicians interested in control, estimation, and optimization of dynamic systems. The paper concludes by highlighting areas where further research is needed, such as relaxing restrictions on boundary layer jumps in trajectory optimization and extending the methods to other types of control problems.This paper provides an overview of singular perturbations in control theory, focusing on their application to model order reduction and the separation of time scales in control system design. The authors discuss the conceptual and computational simplifications that result from these techniques, which are particularly useful for high-dimensional systems where the "curse of dimensionality" poses significant challenges. The paper covers various aspects of singular perturbations, including initial and boundary value problems, stability and stabilizability, optimal regulators, trajectory optimization, filtering and smoothing, and applications to cheap control and singular arcs. It also explores the extension of these methods to distributed parameter systems and time-delay systems. The content is presented in a tutorial form, making it accessible to engineers and applied mathematicians interested in control, estimation, and optimization of dynamic systems. The paper concludes by highlighting areas where further research is needed, such as relaxing restrictions on boundary layer jumps in trajectory optimization and extending the methods to other types of control problems.