The present monograph offers a detailed and in-depth analysis of the topic of Intelligent Control for Electric Power Systems and Electric Vehicles. The monograph provides a comprehensive analysis of various control methods, including nonlinear optimal control, Lie algebra-based control, and differential flatness theory. It addresses the control of electric motors, VSI-fed PMSMs, and energy conversion chains based on PMSMs and induction machines. The work also explores multi-phase machines in gas processing, spherical permanent magnet synchronous motors, traction systems in electric and hybrid vehicles, and renewable power units alongside heat management systems. Key Features: Proposes new control methods meant to treat the control problem of the complex nonlinear dynamics of electric power systems and electric vehicles without the need for complicated state-space model transformations and changes of state variables. Contains modular and scalable control schemes which can be applied to a large class of dynamic models of electric power systems and electric vehicles. They have a clear and easy-to- implement algorithmic part, while they also exhibit a moderate computational load. Fosters the optimized exploitation of renewable energy sources and the reliable integration of renewable energy units in the power grid. Suitable for teaching nonlinear control, estimation and fault diagnosis topics with emphasis to electric power systems and to electric vehicle traction and propulsion systems both at late undergraduate and postgraduate levels.